{"kind": "plan", "major": "18", "item": {"slug": "result", "name": "Result", "name_zh": "Result", "category": "\u63a7\u5236", "summary": "\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002", "aliases": ["Result", "T_Result"], "content_hash": "ca6d35e30aa553b798199237f294caa88a79c2982e1869b00207e7f3210a8630", "versions": {"10": {"facts": [{"label": "\u6838\u5fc3\u8282\u70b9\u6807\u7b7e", "value": "T_Result"}, {"label": "\u7ed3\u6784\u5316 EXPLAIN \u8282\u70b9\u7c7b\u578b", "value": "\u7ed3\u679c"}, {"label": "\u8f93\u5165", "value": "\u53ef\u9009\u7684\u5b50\u8ba1\u5212"}, {"label": "\u8f93\u51fa", "value": "\u6295\u5f71\u540e\u7684\u5143\u7ec4"}, {"label": "\u6267\u884c\u5668\u521d\u59cb\u5316\u51fd\u6570", "value": "ExecInitResult"}, {"label": "\u5185\u5b58\u673a\u5236", "value": "unclassified"}], "memory": {"evidence": [{"url": "https://ftp.postgresql.org/pub/source/v10.23/postgresql-10.23.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "b461ce1e6557bb4743c2b110bad55b5e737c4fd01b088b4e411a64632a4e0722", "archive_sha256": "94a4b2528372458e5662c18d406629266667c437198160a18cdfd2c4a4d6eee9"}], "mechanism": "unclassified", "description": "\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002", "source_notes": []}, "tables": [{"key": "explain-labels", "rows": [{"label": "\u7ed3\u679c", "identity": "\u7ed3\u679c"}], "title": "\u672c\u6784\u5efa\u4e2d\u7684 EXPLAIN \u6807\u7b7e", "columns": [{"key": "label", "label": "\u6587\u672c\u683c\u5f0f\u6807\u7b7e"}, {"key": "identity", "label": "\u7ed3\u6784\u5316\u8282\u70b9\u6807\u8bc6"}]}], "related": [{"url": "/wiki/sql/explain/?v=10", "label": "EXPLAIN"}, {"url": "/docs/10/using-explain.html", "label": "\u4f7f\u7528 EXPLAIN"}, {"url": "/docs/10/parallel-plans.html", "label": "\u5e76\u884c\u8ba1\u5212"}], "release": {"ref": "PostgreSQL 10.23 source archive", "label": "10.23", "major": "10", "channel": "historical", "revision": "94a4b2528372458e5662c18d406629266667c437198160a18cdfd2c4a4d6eee9", "source_url": "https://ftp.postgresql.org/pub/source/v10.23/postgresql-10.23.tar.bz2", "source_snapshot_utc": ""}, "sources": [{"url": "https://ftp.postgresql.org/pub/source/v10.23/postgresql-10.23.tar.bz2", "line": 882, "path": "src/backend/commands/explain.c", "label": "src/backend/commands/explain.c:882", "sha256": "a785298532047cfeda969e78c3597a343dc1c56d61ba85830b0f16a02a14b5a1", "archive_sha256": "94a4b2528372458e5662c18d406629266667c437198160a18cdfd2c4a4d6eee9"}, {"url": "https://ftp.postgresql.org/pub/source/v10.23/postgresql-10.23.tar.bz2", "line": 164, "path": "src/backend/executor/execProcnode.c", "label": "src/backend/executor/execProcnode.c:164", "sha256": "cea76648bb38ae55f18f989768bee1a4ee025691ceea0f86bccb29dcdc166acc", "archive_sha256": "94a4b2528372458e5662c18d406629266667c437198160a18cdfd2c4a4d6eee9"}, {"url": "https://ftp.postgresql.org/pub/source/v10.23/postgresql-10.23.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "b461ce1e6557bb4743c2b110bad55b5e737c4fd01b088b4e411a64632a4e0722", "archive_sha256": "94a4b2528372458e5662c18d406629266667c437198160a18cdfd2c4a4d6eee9"}, {"url": "https://ftp.postgresql.org/pub/source/v10.23/postgresql-10.23.tar.bz2", "path": "src/include/nodes/plannodes.h", "label": "src/include/nodes/plannodes.h", "sha256": "d562c321108844798cd234303fffb618f13d4ee3f3a5ac79bfd963b077e47c22", "archive_sha256": "94a4b2528372458e5662c18d406629266667c437198160a18cdfd2c4a4d6eee9"}, {"url": "https://pg.center/docs/10/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 10.23 \u00b7 using-explain", "sha256": "a4b4304aedb0a2da0145cc7c35b03b319a5c7ee3df35a8ef84ab6d3a610f98f3", "language": "en", "original_url": "/docs/10/using-explain.html#USING-EXPLAIN-BASICS"}, {"url": "https://pg.center/docs/10/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 10.23 \u00b7 using-explain", "sha256": "a4b4304aedb0a2da0145cc7c35b03b319a5c7ee3df35a8ef84ab6d3a610f98f3", "language": "en", "original_url": "/docs/10/using-explain.html#USING-EXPLAIN-ANALYZE"}, {"url": "https://pg.center/docs/10/parallel-plans.html#PARALLEL-PLANS", "path": "parallel-plans.html", "label": "PostgreSQL 10.23 \u00b7 parallel-plans", "sha256": "cd37ed0ef7e2cf177707f50d9a7258574b4cefdcc087e6ee99a3bf377d960fcb", "language": "en", "original_url": "/docs/10/parallel-plans.html#PARALLEL-PLANS"}, {"url": "https://pg.center/docs/10/parallel-plans.html#PARALLEL-AGGREGATION", "path": "parallel-plans.html", "label": "PostgreSQL 10.23 \u00b7 parallel-plans", "sha256": "cd37ed0ef7e2cf177707f50d9a7258574b4cefdcc087e6ee99a3bf377d960fcb", "language": "en", "original_url": "/docs/10/parallel-plans.html#PARALLEL-AGGREGATION"}], "node_tag": "T_Result", "sections": [{"title": "EXPLAIN \u540d\u79f0\u4e0e\u5c5e\u6027", "paragraphs": ["\u7ed3\u6784\u5316\u683c\u5f0f\u4f7f\u7528\u4e0a\u8ff0 Node Type\u3002\u6587\u672c\u683c\u5f0f\u540d\u79f0\u8fd8\u53ef\u80fd\u5305\u542b\u64cd\u4f5c\u3001\u7b56\u7565\u3001\u8fde\u63a5\u7c7b\u578b\u3001\u626b\u63cf\u65b9\u5411\u6216\u805a\u5408\u9636\u6bb5\u5c5e\u6027\u3002", "\u6b64\u6e90\u7801\u8bb0\u5f55\u7684\u6587\u672c\u540d\u79f0\uff1aResult.", "\u5e76\u884c\u611f\u77e5\u4e0e\u5e76\u884c\u5b89\u5168\u662f\u4e0d\u540c\u7684\u8ba1\u5212\u5c5e\u6027\u3002\u5728\u5e76\u884c\u5de5\u4f5c\u8fdb\u7a0b\u5185\u8fd0\u884c\u7684\u8282\u70b9\u4e0d\u4e00\u5b9a\u662f\u5e76\u884c\u611f\u77e5\u8282\u70b9\u3002"]}, {"title": "\u5185\u5b58\u4e0e\u4e34\u65f6\u5b58\u50a8", "paragraphs": ["\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002"]}, {"title": "\u5e76\u884c\u6267\u884c\u4e0e\u8fd0\u884c\u4fe1\u606f\u91c7\u96c6", "paragraphs": ["\u4ee5\u4e0b\u6e90\u7801\u56de\u8c03\u53ef\u4ee5\u534f\u8c03\u6267\u884c\u6216\u6536\u96c6\u5de5\u4f5c\u8fdb\u7a0b\u7684\u6d4b\u91cf\u6570\u636e\u3002\u56de\u8c03\u5b58\u5728\u4e0d\u4ee3\u8868\u8be5\u8282\u70b9\u666e\u904d\u652f\u6301\u5171\u4eab\u5e76\u884c\u626b\u63cf\u6216\u5171\u4eab\u72b6\u6001\u3002", "\u6b64\u6784\u5efa\u7684\u56de\u8c03\uff1anone extracted from this node implementation."]}, {"title": "\u540c\u7248\u672c\u624b\u518c\u8bf4\u660e", "paragraphs": ["\u9700\u8981\u7406\u89e3\uff0c\u4e0a\u5c42\u8282\u70b9\u7684\u4ee3\u4ef7\u5305\u542b\u5176\u5168\u90e8\u5b50\u8282\u70b9\u7684\u4ee3\u4ef7\u3002\u540c\u65f6\uff0c\u4ee3\u4ef7\u4ec5\u53cd\u6620\u89c4\u5212\u5668\u5173\u6ce8\u7684\u56e0\u7d20\u3002\u5c24\u5176\u662f\uff0c\u4ee3\u4ef7\u4e0d\u5305\u542b\u5411\u5ba2\u6237\u7aef\u4f20\u8f93\u7ed3\u679c\u884c\u6240\u82b1\u8d39\u7684\u65f6\u95f4\uff0c\u5c3d\u7ba1\u5b83\u53ef\u80fd\u663e\u8457\u5f71\u54cd\u5b9e\u9645\u8017\u65f6\uff1b\u89c4\u5212\u5668\u5ffd\u7565\u5b83\uff0c\u662f\u56e0\u4e3a\u6539\u53d8\u8ba1\u5212\u65e0\u6cd5\u6539\u53d8\u8fd9\u90e8\u5206\u65f6\u95f4\u3002\uff08\u6211\u4eec\u76f8\u4fe1\u6bcf\u4e2a\u6b63\u786e\u8ba1\u5212\u90fd\u4f1a\u8f93\u51fa\u540c\u6837\u7684\u884c\u96c6\u3002\uff09", "rows \u5bb9\u6613\u4ee4\u4eba\u8bef\u89e3\uff1a\u5b83\u8868\u793a\u8282\u70b9\u8f93\u51fa\u7684\u884c\u6570\uff0c\u800c\u4e0d\u662f\u5904\u7406\u6216\u626b\u63cf\u7684\u884c\u6570\u3002\u8282\u70b9\u5e94\u7528 WHERE \u6761\u4ef6\u7b5b\u9009\u540e\uff0c\u8f93\u51fa\u884c\u6570\u901a\u5e38\u5c0f\u4e8e\u626b\u63cf\u884c\u6570\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u9876\u5c42 rows \u4f30\u8ba1\u5e94\u63a5\u8fd1\u67e5\u8be2\u5b9e\u9645\u8fd4\u56de\u3001\u66f4\u65b0\u6216\u5220\u9664\u7684\u884c\u6570\u3002", "\u6b64\u8ba1\u5212\u5305\u542b\u4e00\u4e2a\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\uff0c\u4ee5\u4e24\u4e2a\u8868\u626b\u63cf\u4f5c\u4e3a\u8f93\u5165\uff0c\u5373\u5b50\u8282\u70b9\u3002\u8282\u70b9\u6458\u8981\u884c\u7684\u7f29\u8fdb\u53cd\u6620\u8ba1\u5212\u6811\u7ed3\u6784\u3002\u8fde\u63a5\u7684\u7b2c\u4e00\u4e2a\u5b50\u8282\u70b9\uff08\u5916\u4fa7\u5b50\u8282\u70b9\uff09\u662f\u524d\u9762\u89c1\u8fc7\u7684\u4f4d\u56fe\u626b\u63cf\u3002\u5b83\u7684\u4ee3\u4ef7\u548c\u884c\u6570\u4e0e SELECT ... WHERE unique1 < 10 \u76f8\u540c\uff0c\u56e0\u4e3a\u8be5\u8282\u70b9\u5e94\u7528\u4e86 WHERE \u6761\u4ef6 unique1 < 10\u3002t1.unique2 = t2.unique2 \u6761\u4ef6\u6b64\u65f6\u5c1a\u4e0d\u76f8\u5173\uff0c\u56e0\u6b64\u4e0d\u4f1a\u5f71\u54cd\u5916\u4fa7\u626b\u63cf\u7684\u884c\u6570\u3002\u5bf9\u4e8e\u4ece\u5916\u4fa7\u5b50\u8282\u70b9\u83b7\u53d6\u7684\u6bcf\u4e00\u884c\uff0c\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\u90fd\u4f1a\u6267\u884c\u4e00\u6b21\u7b2c\u4e8c\u4e2a\u5b50\u8282\u70b9\uff08\u5185\u4fa7\u5b50\u8282\u70b9\uff09\u3002\u5f53\u524d\u5916\u4fa7\u884c\u7684\u5217\u503c\u53ef\u4ee5\u4ee3\u5165\u5185\u4fa7\u626b\u63cf\uff1b\u8fd9\u91cc\u53ef\u4f7f\u7528\u5916\u4fa7\u884c\u7684 t1.unique2 \u503c\uff0c\u56e0\u6b64\u5f97\u5230\u7684\u8ba1\u5212\u548c\u4ee3\u4ef7\u4e0e\u4e0a\u6587\u7b80\u5355\u7684 SELECT ... WHERE t2.unique2 = constant \u60c5\u51b5\u7c7b\u4f3c\u3002\uff08\u4f30\u8ba1\u4ee3\u4ef7\u5b9e\u9645\u7565\u4f4e\u4e8e\u4e0a\u4f8b\uff0c\u8fd9\u662f\u56e0\u4e3a\u9884\u8ba1\u53cd\u590d\u626b\u63cf t2 \u7d22\u5f15\u65f6\u4f1a\u4ea7\u751f\u7f13\u5b58\u6536\u76ca\u3002\uff09\u5faa\u73af\u8282\u70b9\u7684\u4ee3\u4ef7\u7531\u5916\u4fa7\u626b\u63cf\u4ee3\u4ef7\u3001\u6bcf\u4e2a\u5916\u4fa7\u884c\u6267\u884c\u4e00\u6b21\u5185\u4fa7\u626b\u63cf\u7684\u4ee3\u4ef7\uff08\u672c\u4f8b\u4e3a 10 * 7.91\uff09\uff0c\u4ee5\u53ca\u5c11\u91cf\u8fde\u63a5\u5904\u7406\u6240\u9700\u7684 CPU \u65f6\u95f4\u7ec4\u6210\u3002", "\u53ef\u4f7f\u7528 EXPLAIN \u7684 ANALYZE \u9009\u9879\u68c0\u67e5\u89c4\u5212\u5668\u4f30\u7b97\u662f\u5426\u51c6\u786e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\uff0cEXPLAIN \u4f1a\u5b9e\u9645\u6267\u884c\u67e5\u8be2\uff0c\u7136\u540e\u663e\u793a\u6bcf\u4e2a\u8ba1\u5212\u8282\u70b9\u7d2f\u8ba1\u7684\u771f\u5b9e\u884c\u6570\u548c\u771f\u5b9e\u8fd0\u884c\u65f6\u95f4\uff0c\u4ee5\u53ca\u666e\u901a EXPLAIN \u6240\u663e\u793a\u7684\u4f30\u7b97\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u80fd\u5f97\u5230\u5982\u4e0b\u7ed3\u679c\uff1a", "\u7531\u4e8e\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u5c06\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u6267\u884c\u5230\u5e95\uff0c\u56e0\u6b64\u4e0d\u80fd\u7b80\u5355\u5730\u62ff\u4e00\u4e2a\u666e\u901a\u67e5\u8be2\u8ba1\u5212\u5e76\u8ba9\u591a\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u540c\u65f6\u8fd0\u884c\u3002\u90a3\u6837\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u751f\u6210\u5b8c\u6574\u8f93\u51fa\u7ed3\u679c\u96c6\u7684\u4e00\u4efd\u526f\u672c\uff0c\u6240\u4ee5\u67e5\u8be2\u4e0d\u4ec5\u4e0d\u4f1a\u6bd4\u5e73\u5e38\u66f4\u5feb\uff0c\u53cd\u800c\u4f1a\u4ea7\u751f\u9519\u8bef\u7ed3\u679c\u3002\u76f8\u53cd\uff0c\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u5fc5\u987b\u662f\u67e5\u8be2\u4f18\u5316\u5668\u5185\u90e8\u6240\u8bf4\u7684 \u90e8\u5206\u8ba1\u5212 \uff1b\u4e5f\u5c31\u662f\u8bf4\uff0c\u5b83\u5fc5\u987b\u88ab\u6784\u9020\u4e3a\u4f7f\u6267\u884c\u8be5\u8ba1\u5212\u7684\u6bcf\u4e2a\u8fdb\u7a0b\u53ea\u751f\u6210\u8f93\u51fa\u884c\u7684\u4e00\u4e2a\u5b50\u96c6\uff0c\u5e76\u4e14\u4fdd\u8bc1\u6bcf\u4e00\u6761\u6240\u9700\u8f93\u51fa\u884c\u90fd\u6070\u597d\u7531\u67d0\u4e2a\u534f\u4f5c\u8fdb\u7a0b\u751f\u6210\u4e00\u6b21\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u8fd9\u610f\u5473\u7740\u67e5\u8be2\u9a71\u52a8\u8868\u4e0a\u7684\u626b\u63cf\u5fc5\u987b\u662f\u5e76\u884c\u611f\u77e5\u626b\u63cf\u3002", "PostgreSQL \u901a\u8fc7\u5206\u4e24\u4e2a\u9636\u6bb5\u8fdb\u884c\u805a\u5408\u6765\u652f\u6301\u5e76\u884c\u805a\u5408\u3002\u9996\u5148\uff0c\u6bcf\u4e2a\u53c2\u4e0e\u67e5\u8be2\u5e76\u884c\u90e8\u5206\u7684\u8fdb\u7a0b\u6267\u884c\u4e00\u4e2a\u805a\u5408\u6b65\u9aa4\uff0c\u4e3a\u8be5\u8fdb\u7a0b\u6240\u89c1\u5230\u7684\u6bcf\u4e2a\u5206\u7ec4\u4ea7\u751f\u4e00\u4e2a\u90e8\u5206\u7ed3\u679c\u3002\u8fd9\u5728\u8ba1\u5212\u4e2d\u4f53\u73b0\u4e3a\u4e00\u4e2a Partial Aggregate \u8282\u70b9\u3002\u7136\u540e\uff0c\u90e8\u5206\u7ed3\u679c\u901a\u8fc7 Gather \u6216 Gather Merge \u4f20\u9001\u7ed9\u9886\u5bfc\u8005\u3002\u6700\u540e\uff0c\u9886\u5bfc\u8005\u4f1a\u628a\u6765\u81ea\u6240\u6709\u5de5\u4f5c\u8fdb\u7a0b\u7684\u7ed3\u679c\u518d\u6b21\u805a\u5408\uff0c\u4ee5\u4ea7\u751f\u6700\u7ec8\u7ed3\u679c\u3002\u8fd9\u5728\u8ba1\u5212\u4e2d\u4f53\u73b0\u4e3a\u4e00\u4e2a Finalize Aggregate \u8282\u70b9\u3002"]}, {"title": "\u6267\u884c\u5668\u5b9e\u73b0\u8bf4\u660e", "paragraphs": ["nodeResult.c\uff1a\u652f\u6301\u9700\u8981\u7279\u6b8a\u4ee3\u7801\u7684\u5e38\u91cf\u8282\u70b9\u3002", "Result \u8282\u70b9\u7528\u4e8e\u4e0d\u626b\u63cf\u4efb\u4f55\u5173\u7cfb\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\uff08\u8bf7\u8bb0\u4f4f\uff0cINSERT \u6216 UPDATE \u9700\u8981\u4e00\u68f5\u751f\u6210\u65b0\u884c\u7684\u8ba1\u5212\u6811\u3002\uff09", "Result \u8282\u70b9\u4e5f\u7528\u4e8e\u4f18\u5316\u5e26\u6709\u5e38\u91cf\u6761\u4ef6\uff08\u5373\u4e0d\u4f9d\u8d56\u626b\u63cf\u6570\u636e\u7684\u6761\u4ef6\uff09\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\u8fd0\u884c\u65f6\uff0cResult \u8282\u70b9\u53ea\u8ba1\u7b97\u4e00\u6b21\u5e38\u91cf\u6761\u4ef6\uff0cEXPLAIN \u5c06\u5176\u663e\u793a\u4e3a One-Time Filter\u3002\u5982\u679c\u6761\u4ef6\u4e3a\u5047\uff0c\u65e0\u9700\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u4fbf\u53ef\u8fd4\u56de\u7a7a\u7ed3\u679c\u96c6\uff1b\u5982\u679c\u4e3a\u771f\uff0c\u5219\u6b63\u5e38\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u5e76\u4f20\u56de\u7ed3\u679c\u3002"]}, {"code": "case T_Result:\n\t\t\tpname = sname = \"Result\";\n\t\t\tbreak;", "title": "\u6838\u5fc3\u6e90\u7801\u4e2d\u7684 EXPLAIN \u6807\u8bc6"}], "strategies": [], "description": ["\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002"], "localization": {"status": "complete", "sources": [{"url": "/docs/10/functions-array.html", "method": "same-major semantic node", "sha256": "d1e249617f3f66fbbbf43a2b3ea85759849e641428ba63ccdf5d57ce69256854", "language": "zh", "matched_nodes": ["#FUNCTIONS-ARRAY/div[2]/div[1]/table[0]/thead[1]/tr[0]/th[3]"]}, {"url": "/docs/10/parallel-plans.html", "method": "same-major semantic node", "sha256": "885d4ceb10c77809e522baf5c18257546222c5ed3bdeba157ab2356fd6b1cdc7", "language": "zh", "matched_nodes": ["#PARALLEL-PLANS/div[5]/p[1]", "#PARALLEL-PLANS/p[2]"]}], "language": "zh", "original_text": {"/versions/10/description/0": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/versions/10/facts/0/label": "Core node tag", "/versions/10/facts/1/label": "Structured EXPLAIN Node Type", "/versions/10/facts/1/value": "Result", "/versions/10/facts/2/label": "Inputs", "/versions/10/facts/2/value": "Optional child plan", "/versions/10/facts/3/label": "Output", "/versions/10/facts/3/value": "Projected tuples", "/versions/10/facts/4/label": "Executor initializer", "/versions/10/facts/5/label": "Memory mechanism", "/versions/10/tables/0/title": "EXPLAIN labels in this source build", "/versions/10/related/1/label": "Using EXPLAIN", "/versions/10/related/2/label": "Parallel plans", "/versions/10/sections/0/title": "EXPLAIN names and attributes", "/versions/10/sections/1/title": "Memory and temporary storage", "/versions/10/sections/2/title": "Parallel execution and instrumentation", "/versions/10/sections/3/title": "Same-version manual discussion", "/versions/10/sections/4/title": "Executor implementation notes", "/versions/10/sections/5/title": "EXPLAIN identity in core source", "/versions/10/memory/description": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/10/tables/0/rows/0/label": "Result", "/versions/10/sections/0/paragraphs/0": "Structured formats use the Node Type above. Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.", "/versions/10/sections/0/paragraphs/1": "Text names recorded by this source: Result.", "/versions/10/sections/0/paragraphs/2": "Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node.", "/versions/10/sections/1/paragraphs/0": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/10/sections/2/paragraphs/0": "The source callbacks below can coordinate execution or collect worker instrumentation. Their presence is not a blanket claim that this node supports a shared parallel scan or shared state.", "/versions/10/sections/2/paragraphs/1": "Callbacks in this build: none extracted from this node implementation.", "/versions/10/sections/3/paragraphs/0": "It's important to understand that the cost of an upper-level node includes the cost of all its child nodes. It's also important to realize that the cost only reflects things that the planner cares about. In particular, the cost does not consider the time spent transmitting result rows to the client, which could be an important factor in the real elapsed time; but the planner ignores it because it cannot change it by altering the plan. (Every correct plan will output the same row set, we trust.)", "/versions/10/sections/3/paragraphs/1": "The rows value is a little tricky because it is not the number of rows processed or scanned by the plan node, but rather the number emitted by the node. This is often less than the number scanned, as a result of filtering by any WHERE -clause conditions that are being applied at the node. Ideally the top-level rows estimate will approximate the number of rows actually returned, updated, or deleted by the query.", "/versions/10/sections/3/paragraphs/2": "In this plan, we have a nested-loop join node with two table scans as inputs, or children. The indentation of the node summary lines reflects the plan tree structure. The join's first, or \u201c outer \u201d , child is a bitmap scan similar to those we saw before. Its cost and row count are the same as we'd get from SELECT ... WHERE unique1 < 10 because we are applying the WHERE clause unique1 < 10 at that node. The t1.unique2 = t2.unique2 clause is not relevant yet, so it doesn't affect the row count of the outer scan. The nested-loop join node will run its second, or \u201c inner \u201d child once for each row obtained from the outer child. Column values from the current outer row can be plugged into the inner scan; here, the t1.unique2 value from the outer row is available, so we get a plan and costs similar to what we saw above for a simple SELECT ... WHERE t2.unique2 = constant case. (The estimated cost is actually a bit lower than what was seen above, as a result of caching that's expected to occur during the repeated index scans on t2 .) The costs of the loop node are then set on the basis of the cost of the outer scan, plus one repetition of the inner scan for each outer row (10 * 7.91, here), plus a little CPU time for join processing.", "/versions/10/sections/3/paragraphs/3": "It is possible to check the accuracy of the planner's estimates by using EXPLAIN 's ANALYZE option. With this option, EXPLAIN actually executes the query, and then displays the true row counts and true run time accumulated within each plan node, along with the same estimates that a plain EXPLAIN shows. For example, we might get a result like this:", "/versions/10/sections/3/paragraphs/4": "Because each worker executes the parallel portion of the plan to completion, it is not possible to simply take an ordinary query plan and run it using multiple workers. Each worker would produce a full copy of the output result set, so the query would not run any faster than normal but would produce incorrect results. Instead, the parallel portion of the plan must be what is known internally to the query optimizer as a partial plan ; that is, it must be constructed so that each process that executes the plan will generate only a subset of the output rows in such a way that each required output row is guaranteed to be generated by exactly one of the cooperating processes. Generally, this means that the scan on the driving table of the query must be a parallel-aware scan.", "/versions/10/sections/3/paragraphs/5": "PostgreSQL supports parallel aggregation by aggregating in two stages. First, each process participating in the parallel portion of the query performs an aggregation step, producing a partial result for each group of which that process is aware. This is reflected in the plan as a Partial Aggregate node. Second, the partial results are transferred to the leader via Gather or Gather Merge . Finally, the leader re-aggregates the results across all workers in order to produce the final result. This is reflected in the plan as a Finalize Aggregate node.", "/versions/10/sections/4/paragraphs/0": "nodeResult.c support for constant nodes needing special code.", "/versions/10/sections/4/paragraphs/1": "Result nodes are used in queries where no relations are scanned. Examples of such queries are:", "/versions/10/sections/4/paragraphs/2": "(Remember that in an INSERT or UPDATE, we need a plan tree that generates the new rows.)", "/versions/10/sections/4/paragraphs/3": "Result nodes are also used to optimise queries with constant qualifications (ie, quals that do not depend on the scanned data), such as:", "/versions/10/sections/4/paragraphs/4": "At runtime, the Result node evaluates the constant qual once, which is shown by EXPLAIN as a One-Time Filter. If it's false, we can return an empty result set without running the controlled plan at all. If it's true, we run the controlled plan normally and pass back the results.", "/versions/10/tables/0/columns/0/label": "Text-format label", "/versions/10/tables/0/columns/1/label": "Structured node identity", "/versions/10/tables/0/rows/0/identity": "Result"}, "fallback_fields": [], "source_language": "en", "original_snapshot_sha256": "0d8f7d1e329c471c18b94572f7d3f576a9ddbcfddb276eabaca7ae92b9876e18"}, "evidence_kind": "source and documentation", "explain_names": ["Result"], "partial_modes": [], "comparison_data": {"node_tag": "T_Result", "strategies": [], "text_names": ["Result"], "initializer": "ExecInitResult", "partial_modes": [], "memory_mechanism": "unclassified", "parallel_callbacks": []}, "comparison_hash": "7d9e21f5e91321228505ba502e7faa5b9ebdda5ba4d71b8a9b97571a1f87b5f5", "explain_prefixes": ["Parallel"], "runtime_verified": false, "source_inventory": {"explain": "src/backend/commands/explain.c", "executor": "src/backend/executor/execProcnode.c", "implementation": "src/backend/executor/nodeResult.c"}, "parallel_callbacks": []}, "11": {"facts": [{"label": "\u6838\u5fc3\u8282\u70b9\u6807\u7b7e", "value": "T_Result"}, {"label": "\u7ed3\u6784\u5316 EXPLAIN \u8282\u70b9\u7c7b\u578b", "value": "\u7ed3\u679c"}, {"label": "\u8f93\u5165", "value": "\u53ef\u9009\u7684\u5b50\u8ba1\u5212"}, {"label": "\u8f93\u51fa", "value": "\u6295\u5f71\u540e\u7684\u5143\u7ec4"}, {"label": "\u6267\u884c\u5668\u521d\u59cb\u5316\u51fd\u6570", "value": "ExecInitResult"}, {"label": "\u5185\u5b58\u673a\u5236", "value": "unclassified"}], "memory": {"evidence": [{"url": "https://ftp.postgresql.org/pub/source/v11.22/postgresql-11.22.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "bcd5b6e09c4ab8f0a9ec8ed6a377b8d1f8c17e103319494da7d6f4e569dceb81", "archive_sha256": "2cb7c97d7a0d7278851bbc9c61f467b69c094c72b81740b751108e7892ebe1f0"}], "mechanism": "unclassified", "description": "\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002", "source_notes": []}, "tables": [{"key": "explain-labels", "rows": [{"label": "\u7ed3\u679c", "identity": "\u7ed3\u679c"}], "title": "\u672c\u6784\u5efa\u4e2d\u7684 EXPLAIN \u6807\u7b7e", "columns": [{"key": "label", "label": "\u6587\u672c\u683c\u5f0f\u6807\u7b7e"}, {"key": "identity", "label": "\u7ed3\u6784\u5316\u8282\u70b9\u6807\u8bc6"}]}], "related": [{"url": "/wiki/sql/explain/?v=11", "label": "EXPLAIN"}, {"url": "/docs/11/using-explain.html", "label": "\u4f7f\u7528 EXPLAIN"}, {"url": "/docs/11/parallel-plans.html", "label": "\u5e76\u884c\u8ba1\u5212"}], "release": {"ref": "PostgreSQL 11.22 source archive", "label": "11.22", "major": "11", "channel": "historical", "revision": "2cb7c97d7a0d7278851bbc9c61f467b69c094c72b81740b751108e7892ebe1f0", "source_url": "https://ftp.postgresql.org/pub/source/v11.22/postgresql-11.22.tar.bz2", "source_snapshot_utc": ""}, "sources": [{"url": "https://ftp.postgresql.org/pub/source/v11.22/postgresql-11.22.tar.bz2", "line": 1007, "path": "src/backend/commands/explain.c", "label": "src/backend/commands/explain.c:1007", "sha256": "9df8400c1a4377179572ceb916d6020fca4e2760f74bf416d77ed97476523bbd", "archive_sha256": "2cb7c97d7a0d7278851bbc9c61f467b69c094c72b81740b751108e7892ebe1f0"}, {"url": "https://ftp.postgresql.org/pub/source/v11.22/postgresql-11.22.tar.bz2", "line": 164, "path": "src/backend/executor/execProcnode.c", "label": "src/backend/executor/execProcnode.c:164", "sha256": "95ef4d4a5df4c29f14af9763fae2c530449bdacdf3853d9ff297adf1fed6153b", "archive_sha256": "2cb7c97d7a0d7278851bbc9c61f467b69c094c72b81740b751108e7892ebe1f0"}, {"url": "https://ftp.postgresql.org/pub/source/v11.22/postgresql-11.22.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "bcd5b6e09c4ab8f0a9ec8ed6a377b8d1f8c17e103319494da7d6f4e569dceb81", "archive_sha256": "2cb7c97d7a0d7278851bbc9c61f467b69c094c72b81740b751108e7892ebe1f0"}, {"url": "https://ftp.postgresql.org/pub/source/v11.22/postgresql-11.22.tar.bz2", "path": "src/include/nodes/plannodes.h", "label": "src/include/nodes/plannodes.h", "sha256": "5e0511194183800e8d6eb293fd4b40639c7d3118e2d199c8e7865ba4fa4cf67f", "archive_sha256": "2cb7c97d7a0d7278851bbc9c61f467b69c094c72b81740b751108e7892ebe1f0"}, {"url": "https://pg.center/docs/11/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 11.22 \u00b7 using-explain", "sha256": "8411bc78085d4737e32d7cca103d859da6c6539e33ec5e2fba46e74c6f199d8a", "language": "en", "original_url": "/docs/11/using-explain.html#USING-EXPLAIN-BASICS"}, {"url": "https://pg.center/docs/11/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 11.22 \u00b7 using-explain", "sha256": "8411bc78085d4737e32d7cca103d859da6c6539e33ec5e2fba46e74c6f199d8a", "language": "en", "original_url": "/docs/11/using-explain.html#USING-EXPLAIN-ANALYZE"}, {"url": "https://pg.center/docs/11/parallel-plans.html#PARALLEL-PLANS", "path": "parallel-plans.html", "label": "PostgreSQL 11.22 \u00b7 parallel-plans", "sha256": "353df5869034b7665159a74037d9cf3e1800d15efcea3390daaa99aae89fa288", "language": "en", "original_url": "/docs/11/parallel-plans.html#PARALLEL-PLANS"}, {"url": "https://pg.center/docs/11/parallel-plans.html#PARALLEL-AGGREGATION", "path": "parallel-plans.html", "label": "PostgreSQL 11.22 \u00b7 parallel-plans", "sha256": "353df5869034b7665159a74037d9cf3e1800d15efcea3390daaa99aae89fa288", "language": "en", "original_url": "/docs/11/parallel-plans.html#PARALLEL-AGGREGATION"}], "node_tag": "T_Result", "sections": [{"title": "EXPLAIN \u540d\u79f0\u4e0e\u5c5e\u6027", "paragraphs": ["\u7ed3\u6784\u5316\u683c\u5f0f\u4f7f\u7528\u4e0a\u8ff0 Node Type\u3002\u6587\u672c\u683c\u5f0f\u540d\u79f0\u8fd8\u53ef\u80fd\u5305\u542b\u64cd\u4f5c\u3001\u7b56\u7565\u3001\u8fde\u63a5\u7c7b\u578b\u3001\u626b\u63cf\u65b9\u5411\u6216\u805a\u5408\u9636\u6bb5\u5c5e\u6027\u3002", "\u6b64\u6e90\u7801\u8bb0\u5f55\u7684\u6587\u672c\u540d\u79f0\uff1aResult.", "\u5e76\u884c\u611f\u77e5\u4e0e\u5e76\u884c\u5b89\u5168\u662f\u4e0d\u540c\u7684\u8ba1\u5212\u5c5e\u6027\u3002\u5728\u5e76\u884c\u5de5\u4f5c\u8fdb\u7a0b\u5185\u8fd0\u884c\u7684\u8282\u70b9\u4e0d\u4e00\u5b9a\u662f\u5e76\u884c\u611f\u77e5\u8282\u70b9\u3002"]}, {"title": "\u5185\u5b58\u4e0e\u4e34\u65f6\u5b58\u50a8", "paragraphs": ["\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002"]}, {"title": "\u5e76\u884c\u6267\u884c\u4e0e\u8fd0\u884c\u4fe1\u606f\u91c7\u96c6", "paragraphs": ["\u4ee5\u4e0b\u6e90\u7801\u56de\u8c03\u53ef\u4ee5\u534f\u8c03\u6267\u884c\u6216\u6536\u96c6\u5de5\u4f5c\u8fdb\u7a0b\u7684\u6d4b\u91cf\u6570\u636e\u3002\u56de\u8c03\u5b58\u5728\u4e0d\u4ee3\u8868\u8be5\u8282\u70b9\u666e\u904d\u652f\u6301\u5171\u4eab\u5e76\u884c\u626b\u63cf\u6216\u5171\u4eab\u72b6\u6001\u3002", "\u6b64\u6784\u5efa\u7684\u56de\u8c03\uff1anone extracted from this node implementation."]}, {"title": "\u540c\u7248\u672c\u624b\u518c\u8bf4\u660e", "paragraphs": ["\u9700\u8981\u7406\u89e3\uff0c\u4e0a\u5c42\u8282\u70b9\u7684\u4ee3\u4ef7\u5305\u542b\u5176\u5168\u90e8\u5b50\u8282\u70b9\u7684\u4ee3\u4ef7\u3002\u540c\u65f6\uff0c\u4ee3\u4ef7\u4ec5\u53cd\u6620\u89c4\u5212\u5668\u5173\u6ce8\u7684\u56e0\u7d20\u3002\u5c24\u5176\u662f\uff0c\u4ee3\u4ef7\u4e0d\u5305\u542b\u5411\u5ba2\u6237\u7aef\u4f20\u8f93\u7ed3\u679c\u884c\u6240\u82b1\u8d39\u7684\u65f6\u95f4\uff0c\u5c3d\u7ba1\u5b83\u53ef\u80fd\u663e\u8457\u5f71\u54cd\u5b9e\u9645\u8017\u65f6\uff1b\u89c4\u5212\u5668\u5ffd\u7565\u5b83\uff0c\u662f\u56e0\u4e3a\u6539\u53d8\u8ba1\u5212\u65e0\u6cd5\u6539\u53d8\u8fd9\u90e8\u5206\u65f6\u95f4\u3002\uff08\u6211\u4eec\u76f8\u4fe1\u6bcf\u4e2a\u6b63\u786e\u8ba1\u5212\u90fd\u4f1a\u8f93\u51fa\u540c\u6837\u7684\u884c\u96c6\u3002\uff09", "rows \u5bb9\u6613\u4ee4\u4eba\u8bef\u89e3\uff1a\u5b83\u8868\u793a\u8282\u70b9\u8f93\u51fa\u7684\u884c\u6570\uff0c\u800c\u4e0d\u662f\u5904\u7406\u6216\u626b\u63cf\u7684\u884c\u6570\u3002\u8282\u70b9\u5e94\u7528 WHERE \u6761\u4ef6\u7b5b\u9009\u540e\uff0c\u8f93\u51fa\u884c\u6570\u901a\u5e38\u5c0f\u4e8e\u626b\u63cf\u884c\u6570\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u9876\u5c42 rows \u4f30\u8ba1\u5e94\u63a5\u8fd1\u67e5\u8be2\u5b9e\u9645\u8fd4\u56de\u3001\u66f4\u65b0\u6216\u5220\u9664\u7684\u884c\u6570\u3002", "\u6b64\u8ba1\u5212\u5305\u542b\u4e00\u4e2a\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\uff0c\u4ee5\u4e24\u4e2a\u8868\u626b\u63cf\u4f5c\u4e3a\u8f93\u5165\uff0c\u5373\u5b50\u8282\u70b9\u3002\u8282\u70b9\u6458\u8981\u884c\u7684\u7f29\u8fdb\u53cd\u6620\u8ba1\u5212\u6811\u7ed3\u6784\u3002\u8fde\u63a5\u7684\u7b2c\u4e00\u4e2a\u5b50\u8282\u70b9\uff08\u5916\u4fa7\u5b50\u8282\u70b9\uff09\u662f\u524d\u9762\u89c1\u8fc7\u7684\u4f4d\u56fe\u626b\u63cf\u3002\u5b83\u7684\u4ee3\u4ef7\u548c\u884c\u6570\u4e0e SELECT ... WHERE unique1 < 10 \u76f8\u540c\uff0c\u56e0\u4e3a\u8be5\u8282\u70b9\u5e94\u7528\u4e86 WHERE \u6761\u4ef6 unique1 < 10\u3002t1.unique2 = t2.unique2 \u6761\u4ef6\u6b64\u65f6\u5c1a\u4e0d\u76f8\u5173\uff0c\u56e0\u6b64\u4e0d\u4f1a\u5f71\u54cd\u5916\u4fa7\u626b\u63cf\u7684\u884c\u6570\u3002\u5bf9\u4e8e\u4ece\u5916\u4fa7\u5b50\u8282\u70b9\u83b7\u53d6\u7684\u6bcf\u4e00\u884c\uff0c\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\u90fd\u4f1a\u6267\u884c\u4e00\u6b21\u7b2c\u4e8c\u4e2a\u5b50\u8282\u70b9\uff08\u5185\u4fa7\u5b50\u8282\u70b9\uff09\u3002\u5f53\u524d\u5916\u4fa7\u884c\u7684\u5217\u503c\u53ef\u4ee5\u4ee3\u5165\u5185\u4fa7\u626b\u63cf\uff1b\u8fd9\u91cc\u53ef\u4f7f\u7528\u5916\u4fa7\u884c\u7684 t1.unique2 \u503c\uff0c\u56e0\u6b64\u5f97\u5230\u7684\u8ba1\u5212\u548c\u4ee3\u4ef7\u4e0e\u4e0a\u6587\u7b80\u5355\u7684 SELECT ... WHERE t2.unique2 = constant \u60c5\u51b5\u7c7b\u4f3c\u3002\uff08\u4f30\u8ba1\u4ee3\u4ef7\u5b9e\u9645\u7565\u4f4e\u4e8e\u4e0a\u4f8b\uff0c\u8fd9\u662f\u56e0\u4e3a\u9884\u8ba1\u53cd\u590d\u626b\u63cf t2 \u7d22\u5f15\u65f6\u4f1a\u4ea7\u751f\u7f13\u5b58\u6536\u76ca\u3002\uff09\u5faa\u73af\u8282\u70b9\u7684\u4ee3\u4ef7\u7531\u5916\u4fa7\u626b\u63cf\u4ee3\u4ef7\u3001\u6bcf\u4e2a\u5916\u4fa7\u884c\u6267\u884c\u4e00\u6b21\u5185\u4fa7\u626b\u63cf\u7684\u4ee3\u4ef7\uff08\u672c\u4f8b\u4e3a 10 * 7.91\uff09\uff0c\u4ee5\u53ca\u5c11\u91cf\u8fde\u63a5\u5904\u7406\u6240\u9700\u7684 CPU \u65f6\u95f4\u7ec4\u6210\u3002", "\u53ef\u4f7f\u7528 EXPLAIN \u7684 ANALYZE \u9009\u9879\u68c0\u67e5\u89c4\u5212\u5668\u4f30\u7b97\u662f\u5426\u51c6\u786e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\uff0cEXPLAIN \u4f1a\u5b9e\u9645\u6267\u884c\u67e5\u8be2\uff0c\u7136\u540e\u663e\u793a\u6bcf\u4e2a\u8ba1\u5212\u8282\u70b9\u7d2f\u8ba1\u7684\u771f\u5b9e\u884c\u6570\u548c\u771f\u5b9e\u8fd0\u884c\u65f6\u95f4\uff0c\u4ee5\u53ca\u666e\u901a EXPLAIN \u6240\u663e\u793a\u7684\u4f30\u7b97\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u80fd\u5f97\u5230\u5982\u4e0b\u7ed3\u679c\uff1a", "\u7531\u4e8e\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u5c06\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u6267\u884c\u5230\u5e95\uff0c\u56e0\u6b64\u4e0d\u80fd\u7b80\u5355\u5730\u62ff\u4e00\u4e2a\u666e\u901a\u67e5\u8be2\u8ba1\u5212\u5e76\u8ba9\u591a\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u540c\u65f6\u8fd0\u884c\u3002\u90a3\u6837\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u751f\u6210\u5b8c\u6574\u8f93\u51fa\u7ed3\u679c\u96c6\u7684\u4e00\u4efd\u526f\u672c\uff0c\u6240\u4ee5\u67e5\u8be2\u4e0d\u4ec5\u4e0d\u4f1a\u6bd4\u5e73\u5e38\u66f4\u5feb\uff0c\u53cd\u800c\u4f1a\u4ea7\u751f\u9519\u8bef\u7ed3\u679c\u3002\u76f8\u53cd\uff0c\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u5fc5\u987b\u662f\u67e5\u8be2\u4f18\u5316\u5668\u5185\u90e8\u6240\u8bf4\u7684 \u90e8\u5206\u8ba1\u5212 \uff1b\u4e5f\u5c31\u662f\u8bf4\uff0c\u5b83\u5fc5\u987b\u88ab\u6784\u9020\u4e3a\u4f7f\u6267\u884c\u8be5\u8ba1\u5212\u7684\u6bcf\u4e2a\u8fdb\u7a0b\u53ea\u751f\u6210\u8f93\u51fa\u884c\u7684\u4e00\u4e2a\u5b50\u96c6\uff0c\u5e76\u4e14\u4fdd\u8bc1\u6bcf\u4e00\u6761\u6240\u9700\u8f93\u51fa\u884c\u90fd\u6070\u597d\u7531\u67d0\u4e2a\u534f\u4f5c\u8fdb\u7a0b\u751f\u6210\u4e00\u6b21\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u8fd9\u610f\u5473\u7740\u67e5\u8be2\u9a71\u52a8\u8868\u4e0a\u7684\u626b\u63cf\u5fc5\u987b\u662f\u5e76\u884c\u611f\u77e5\u626b\u63cf\u3002", "PostgreSQL \u901a\u8fc7\u5206\u4e24\u4e2a\u9636\u6bb5\u8fdb\u884c\u805a\u5408\u6765\u652f\u6301\u5e76\u884c\u805a\u5408\u3002\u9996\u5148\uff0c\u6bcf\u4e2a\u53c2\u4e0e\u67e5\u8be2\u5e76\u884c\u90e8\u5206\u7684\u8fdb\u7a0b\u6267\u884c\u4e00\u4e2a\u805a\u5408\u6b65\u9aa4\uff0c\u4e3a\u8be5\u8fdb\u7a0b\u6240\u89c1\u5230\u7684\u6bcf\u4e2a\u5206\u7ec4\u4ea7\u751f\u4e00\u4e2a\u90e8\u5206\u7ed3\u679c\u3002\u8fd9\u5728\u8ba1\u5212\u4e2d\u4f53\u73b0\u4e3a\u4e00\u4e2a Partial Aggregate \u8282\u70b9\u3002\u7136\u540e\uff0c\u90e8\u5206\u7ed3\u679c\u901a\u8fc7 Gather \u6216 Gather Merge \u4f20\u9001\u7ed9\u9886\u5bfc\u8005\u3002\u6700\u540e\uff0c\u9886\u5bfc\u8005\u4f1a\u628a\u6765\u81ea\u6240\u6709\u5de5\u4f5c\u8fdb\u7a0b\u7684\u7ed3\u679c\u518d\u6b21\u805a\u5408\uff0c\u4ee5\u4ea7\u751f\u6700\u7ec8\u7ed3\u679c\u3002\u8fd9\u5728\u8ba1\u5212\u4e2d\u4f53\u73b0\u4e3a\u4e00\u4e2a Finalize Aggregate \u8282\u70b9\u3002"]}, {"title": "\u6267\u884c\u5668\u5b9e\u73b0\u8bf4\u660e", "paragraphs": ["nodeResult.c\uff1a\u652f\u6301\u9700\u8981\u7279\u6b8a\u4ee3\u7801\u7684\u5e38\u91cf\u8282\u70b9\u3002", "Result \u8282\u70b9\u7528\u4e8e\u4e0d\u626b\u63cf\u4efb\u4f55\u5173\u7cfb\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\uff08\u8bf7\u8bb0\u4f4f\uff0cINSERT \u6216 UPDATE \u9700\u8981\u4e00\u68f5\u751f\u6210\u65b0\u884c\u7684\u8ba1\u5212\u6811\u3002\uff09", "Result \u8282\u70b9\u4e5f\u7528\u4e8e\u4f18\u5316\u5e26\u6709\u5e38\u91cf\u6761\u4ef6\uff08\u5373\u4e0d\u4f9d\u8d56\u626b\u63cf\u6570\u636e\u7684\u6761\u4ef6\uff09\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\u8fd0\u884c\u65f6\uff0cResult \u8282\u70b9\u53ea\u8ba1\u7b97\u4e00\u6b21\u5e38\u91cf\u6761\u4ef6\uff0cEXPLAIN \u5c06\u5176\u663e\u793a\u4e3a One-Time Filter\u3002\u5982\u679c\u6761\u4ef6\u4e3a\u5047\uff0c\u65e0\u9700\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u4fbf\u53ef\u8fd4\u56de\u7a7a\u7ed3\u679c\u96c6\uff1b\u5982\u679c\u4e3a\u771f\uff0c\u5219\u6b63\u5e38\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u5e76\u4f20\u56de\u7ed3\u679c\u3002"]}, {"code": "case T_Result:\n\t\t\tpname = sname = \"Result\";\n\t\t\tbreak;", "title": "\u6838\u5fc3\u6e90\u7801\u4e2d\u7684 EXPLAIN \u6807\u8bc6"}], "strategies": [], "description": ["\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002"], "localization": {"status": "complete", "sources": [{"url": "/docs/11/functions-array.html", "method": "same-major semantic node", "sha256": "6b76adaf1473bfd63798f62516d1fd7b9f8aaa750e28253b82a779b342c3fdec", "language": "zh", "matched_nodes": ["#FUNCTIONS-ARRAY/div[2]/div[1]/table[0]/thead[1]/tr[0]/th[3]"]}, {"url": "/docs/11/parallel-plans.html", "method": "same-major semantic node", "sha256": "963d71be1a9c27fcc3f5c60b2479c7b94c6d85bfc4e1e20289a1c0e6f284ec85", "language": "zh", "matched_nodes": ["#PARALLEL-PLANS/div[5]/p[1]", "#PARALLEL-PLANS/p[2]"]}], "language": "zh", "original_text": {"/versions/11/description/0": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/versions/11/facts/0/label": "Core node tag", "/versions/11/facts/1/label": "Structured EXPLAIN Node Type", "/versions/11/facts/1/value": "Result", "/versions/11/facts/2/label": "Inputs", "/versions/11/facts/2/value": "Optional child plan", "/versions/11/facts/3/label": "Output", "/versions/11/facts/3/value": "Projected tuples", "/versions/11/facts/4/label": "Executor initializer", "/versions/11/facts/5/label": "Memory mechanism", "/versions/11/tables/0/title": "EXPLAIN labels in this source build", "/versions/11/related/1/label": "Using EXPLAIN", "/versions/11/related/2/label": "Parallel plans", "/versions/11/sections/0/title": "EXPLAIN names and attributes", "/versions/11/sections/1/title": "Memory and temporary storage", "/versions/11/sections/2/title": "Parallel execution and instrumentation", "/versions/11/sections/3/title": "Same-version manual discussion", "/versions/11/sections/4/title": "Executor implementation notes", "/versions/11/sections/5/title": "EXPLAIN identity in core source", "/versions/11/memory/description": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/11/tables/0/rows/0/label": "Result", "/versions/11/sections/0/paragraphs/0": "Structured formats use the Node Type above. Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.", "/versions/11/sections/0/paragraphs/1": "Text names recorded by this source: Result.", "/versions/11/sections/0/paragraphs/2": "Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node.", "/versions/11/sections/1/paragraphs/0": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/11/sections/2/paragraphs/0": "The source callbacks below can coordinate execution or collect worker instrumentation. Their presence is not a blanket claim that this node supports a shared parallel scan or shared state.", "/versions/11/sections/2/paragraphs/1": "Callbacks in this build: none extracted from this node implementation.", "/versions/11/sections/3/paragraphs/0": "It's important to understand that the cost of an upper-level node includes the cost of all its child nodes. It's also important to realize that the cost only reflects things that the planner cares about. In particular, the cost does not consider the time spent transmitting result rows to the client, which could be an important factor in the real elapsed time; but the planner ignores it because it cannot change it by altering the plan. (Every correct plan will output the same row set, we trust.)", "/versions/11/sections/3/paragraphs/1": "The rows value is a little tricky because it is not the number of rows processed or scanned by the plan node, but rather the number emitted by the node. This is often less than the number scanned, as a result of filtering by any WHERE -clause conditions that are being applied at the node. Ideally the top-level rows estimate will approximate the number of rows actually returned, updated, or deleted by the query.", "/versions/11/sections/3/paragraphs/2": "In this plan, we have a nested-loop join node with two table scans as inputs, or children. The indentation of the node summary lines reflects the plan tree structure. The join's first, or \u201c outer \u201d , child is a bitmap scan similar to those we saw before. Its cost and row count are the same as we'd get from SELECT ... WHERE unique1 < 10 because we are applying the WHERE clause unique1 < 10 at that node. The t1.unique2 = t2.unique2 clause is not relevant yet, so it doesn't affect the row count of the outer scan. The nested-loop join node will run its second, or \u201c inner \u201d child once for each row obtained from the outer child. Column values from the current outer row can be plugged into the inner scan; here, the t1.unique2 value from the outer row is available, so we get a plan and costs similar to what we saw above for a simple SELECT ... WHERE t2.unique2 = constant case. (The estimated cost is actually a bit lower than what was seen above, as a result of caching that's expected to occur during the repeated index scans on t2 .) The costs of the loop node are then set on the basis of the cost of the outer scan, plus one repetition of the inner scan for each outer row (10 * 7.91, here), plus a little CPU time for join processing.", "/versions/11/sections/3/paragraphs/3": "It is possible to check the accuracy of the planner's estimates by using EXPLAIN 's ANALYZE option. With this option, EXPLAIN actually executes the query, and then displays the true row counts and true run time accumulated within each plan node, along with the same estimates that a plain EXPLAIN shows. For example, we might get a result like this:", "/versions/11/sections/3/paragraphs/4": "Because each worker executes the parallel portion of the plan to completion, it is not possible to simply take an ordinary query plan and run it using multiple workers. Each worker would produce a full copy of the output result set, so the query would not run any faster than normal but would produce incorrect results. Instead, the parallel portion of the plan must be what is known internally to the query optimizer as a partial plan ; that is, it must be constructed so that each process that executes the plan will generate only a subset of the output rows in such a way that each required output row is guaranteed to be generated by exactly one of the cooperating processes. Generally, this means that the scan on the driving table of the query must be a parallel-aware scan.", "/versions/11/sections/3/paragraphs/5": "PostgreSQL supports parallel aggregation by aggregating in two stages. First, each process participating in the parallel portion of the query performs an aggregation step, producing a partial result for each group of which that process is aware. This is reflected in the plan as a Partial Aggregate node. Second, the partial results are transferred to the leader via Gather or Gather Merge . Finally, the leader re-aggregates the results across all workers in order to produce the final result. This is reflected in the plan as a Finalize Aggregate node.", "/versions/11/sections/4/paragraphs/0": "nodeResult.c support for constant nodes needing special code.", "/versions/11/sections/4/paragraphs/1": "Result nodes are used in queries where no relations are scanned. Examples of such queries are:", "/versions/11/sections/4/paragraphs/2": "(Remember that in an INSERT or UPDATE, we need a plan tree that generates the new rows.)", "/versions/11/sections/4/paragraphs/3": "Result nodes are also used to optimise queries with constant qualifications (ie, quals that do not depend on the scanned data), such as:", "/versions/11/sections/4/paragraphs/4": "At runtime, the Result node evaluates the constant qual once, which is shown by EXPLAIN as a One-Time Filter. If it's false, we can return an empty result set without running the controlled plan at all. If it's true, we run the controlled plan normally and pass back the results.", "/versions/11/tables/0/columns/0/label": "Text-format label", "/versions/11/tables/0/columns/1/label": "Structured node identity", "/versions/11/tables/0/rows/0/identity": "Result"}, "fallback_fields": [], "source_language": "en", "original_snapshot_sha256": "4923c5673f5f2dae8827832b87854cbc62a74b9ddea919fca65339f098c54436"}, "evidence_kind": "source and documentation", "explain_names": ["Result"], "partial_modes": [], "comparison_data": {"node_tag": "T_Result", "strategies": [], "text_names": ["Result"], "initializer": "ExecInitResult", "partial_modes": [], "memory_mechanism": "unclassified", "parallel_callbacks": []}, "comparison_hash": "7d9e21f5e91321228505ba502e7faa5b9ebdda5ba4d71b8a9b97571a1f87b5f5", "explain_prefixes": ["Parallel"], "runtime_verified": false, "source_inventory": {"explain": "src/backend/commands/explain.c", "executor": "src/backend/executor/execProcnode.c", "implementation": "src/backend/executor/nodeResult.c"}, "parallel_callbacks": []}, "12": {"facts": [{"label": "\u6838\u5fc3\u8282\u70b9\u6807\u7b7e", "value": "T_Result"}, {"label": "\u7ed3\u6784\u5316 EXPLAIN \u8282\u70b9\u7c7b\u578b", "value": "\u7ed3\u679c"}, {"label": "\u8f93\u5165", "value": "\u53ef\u9009\u7684\u5b50\u8ba1\u5212"}, {"label": "\u8f93\u51fa", "value": "\u6295\u5f71\u540e\u7684\u5143\u7ec4"}, {"label": "\u6267\u884c\u5668\u521d\u59cb\u5316\u51fd\u6570", "value": "ExecInitResult"}, {"label": "\u5185\u5b58\u673a\u5236", "value": "unclassified"}], "memory": {"evidence": [{"url": "https://ftp.postgresql.org/pub/source/v12.22/postgresql-12.22.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "bf12dbdf3a5a9ce282ed5305b465c8d4af3e04930181b3637b29bf951c5b24a0", "archive_sha256": "8df3c0474782589d3c6f374b5133b1bd14d168086edbc13c6e72e67dd4527a3b"}], "mechanism": "unclassified", "description": "\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002", "source_notes": []}, "tables": [{"key": "explain-labels", "rows": [{"label": "\u7ed3\u679c", "identity": "\u7ed3\u679c"}], "title": "\u672c\u6784\u5efa\u4e2d\u7684 EXPLAIN \u6807\u7b7e", "columns": [{"key": "label", "label": "\u6587\u672c\u683c\u5f0f\u6807\u7b7e"}, {"key": "identity", "label": "\u7ed3\u6784\u5316\u8282\u70b9\u6807\u8bc6"}]}], "related": [{"url": "/wiki/sql/explain/?v=12", "label": "EXPLAIN"}, {"url": "/docs/12/using-explain.html", "label": "\u4f7f\u7528 EXPLAIN"}, {"url": "/docs/12/parallel-plans.html", "label": "\u5e76\u884c\u8ba1\u5212"}], "release": {"ref": "PostgreSQL 12.22 source archive", "label": "12.22", "major": "12", "channel": "historical", "revision": "8df3c0474782589d3c6f374b5133b1bd14d168086edbc13c6e72e67dd4527a3b", "source_url": "https://ftp.postgresql.org/pub/source/v12.22/postgresql-12.22.tar.bz2", "source_snapshot_utc": ""}, "sources": [{"url": "https://ftp.postgresql.org/pub/source/v12.22/postgresql-12.22.tar.bz2", "line": 1078, "path": "src/backend/commands/explain.c", "label": "src/backend/commands/explain.c:1078", "sha256": "d02ea84fdaa201de5d9360645a9f24bfbd2c31f7d45a639e09560ac0e6b6471d", "archive_sha256": "8df3c0474782589d3c6f374b5133b1bd14d168086edbc13c6e72e67dd4527a3b"}, {"url": "https://ftp.postgresql.org/pub/source/v12.22/postgresql-12.22.tar.bz2", "line": 164, "path": "src/backend/executor/execProcnode.c", "label": "src/backend/executor/execProcnode.c:164", "sha256": "311b17379fe54e3f342fe5ad41c43afbdfa1b844978db2bb2eb22b82520d3256", "archive_sha256": "8df3c0474782589d3c6f374b5133b1bd14d168086edbc13c6e72e67dd4527a3b"}, {"url": "https://ftp.postgresql.org/pub/source/v12.22/postgresql-12.22.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "bf12dbdf3a5a9ce282ed5305b465c8d4af3e04930181b3637b29bf951c5b24a0", "archive_sha256": "8df3c0474782589d3c6f374b5133b1bd14d168086edbc13c6e72e67dd4527a3b"}, {"url": "https://ftp.postgresql.org/pub/source/v12.22/postgresql-12.22.tar.bz2", "path": "src/include/nodes/plannodes.h", "label": "src/include/nodes/plannodes.h", "sha256": "b0c4a0aeb48660ce06e5e700d5529ca9066fd16682bd15783d6e71b5420b07b0", "archive_sha256": "8df3c0474782589d3c6f374b5133b1bd14d168086edbc13c6e72e67dd4527a3b"}, {"url": "https://pg.center/docs/12/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 12.22 \u00b7 using-explain", "sha256": "06297525f2180b07e752837a3351be9c871b56559f535bcd0a67dec9baac10c0", "language": "en", "original_url": "/docs/12/using-explain.html#USING-EXPLAIN-BASICS"}, {"url": "https://pg.center/docs/12/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 12.22 \u00b7 using-explain", "sha256": "06297525f2180b07e752837a3351be9c871b56559f535bcd0a67dec9baac10c0", "language": "en", "original_url": "/docs/12/using-explain.html#USING-EXPLAIN-ANALYZE"}, {"url": "https://pg.center/docs/12/parallel-plans.html#PARALLEL-PLANS", "path": "parallel-plans.html", "label": "PostgreSQL 12.22 \u00b7 parallel-plans", "sha256": "fa33380814ee65998f524524f8681d70cf3b1198d54b39847b00462b01517ffb", "language": "en", "original_url": "/docs/12/parallel-plans.html#PARALLEL-PLANS"}, {"url": "https://pg.center/docs/12/parallel-plans.html#PARALLEL-AGGREGATION", "path": "parallel-plans.html", "label": "PostgreSQL 12.22 \u00b7 parallel-plans", "sha256": "fa33380814ee65998f524524f8681d70cf3b1198d54b39847b00462b01517ffb", "language": "en", "original_url": "/docs/12/parallel-plans.html#PARALLEL-AGGREGATION"}], "node_tag": "T_Result", "sections": [{"title": "EXPLAIN \u540d\u79f0\u4e0e\u5c5e\u6027", "paragraphs": ["\u7ed3\u6784\u5316\u683c\u5f0f\u4f7f\u7528\u4e0a\u8ff0 Node Type\u3002\u6587\u672c\u683c\u5f0f\u540d\u79f0\u8fd8\u53ef\u80fd\u5305\u542b\u64cd\u4f5c\u3001\u7b56\u7565\u3001\u8fde\u63a5\u7c7b\u578b\u3001\u626b\u63cf\u65b9\u5411\u6216\u805a\u5408\u9636\u6bb5\u5c5e\u6027\u3002", "\u6b64\u6e90\u7801\u8bb0\u5f55\u7684\u6587\u672c\u540d\u79f0\uff1aResult.", "\u5e76\u884c\u611f\u77e5\u4e0e\u5e76\u884c\u5b89\u5168\u662f\u4e0d\u540c\u7684\u8ba1\u5212\u5c5e\u6027\u3002\u5728\u5e76\u884c\u5de5\u4f5c\u8fdb\u7a0b\u5185\u8fd0\u884c\u7684\u8282\u70b9\u4e0d\u4e00\u5b9a\u662f\u5e76\u884c\u611f\u77e5\u8282\u70b9\u3002"]}, {"title": "\u5185\u5b58\u4e0e\u4e34\u65f6\u5b58\u50a8", "paragraphs": ["\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002"]}, {"title": "\u5e76\u884c\u6267\u884c\u4e0e\u8fd0\u884c\u4fe1\u606f\u91c7\u96c6", "paragraphs": ["\u4ee5\u4e0b\u6e90\u7801\u56de\u8c03\u53ef\u4ee5\u534f\u8c03\u6267\u884c\u6216\u6536\u96c6\u5de5\u4f5c\u8fdb\u7a0b\u7684\u6d4b\u91cf\u6570\u636e\u3002\u56de\u8c03\u5b58\u5728\u4e0d\u4ee3\u8868\u8be5\u8282\u70b9\u666e\u904d\u652f\u6301\u5171\u4eab\u5e76\u884c\u626b\u63cf\u6216\u5171\u4eab\u72b6\u6001\u3002", "\u6b64\u6784\u5efa\u7684\u56de\u8c03\uff1anone extracted from this node implementation."]}, {"title": "\u540c\u7248\u672c\u624b\u518c\u8bf4\u660e", "paragraphs": ["\u9700\u8981\u7406\u89e3\uff0c\u4e0a\u5c42\u8282\u70b9\u7684\u4ee3\u4ef7\u5305\u542b\u5176\u5168\u90e8\u5b50\u8282\u70b9\u7684\u4ee3\u4ef7\u3002\u540c\u65f6\uff0c\u4ee3\u4ef7\u4ec5\u53cd\u6620\u89c4\u5212\u5668\u5173\u6ce8\u7684\u56e0\u7d20\u3002\u5c24\u5176\u662f\uff0c\u4ee3\u4ef7\u4e0d\u5305\u542b\u5411\u5ba2\u6237\u7aef\u4f20\u8f93\u7ed3\u679c\u884c\u6240\u82b1\u8d39\u7684\u65f6\u95f4\uff0c\u5c3d\u7ba1\u5b83\u53ef\u80fd\u663e\u8457\u5f71\u54cd\u5b9e\u9645\u8017\u65f6\uff1b\u89c4\u5212\u5668\u5ffd\u7565\u5b83\uff0c\u662f\u56e0\u4e3a\u6539\u53d8\u8ba1\u5212\u65e0\u6cd5\u6539\u53d8\u8fd9\u90e8\u5206\u65f6\u95f4\u3002\uff08\u6211\u4eec\u76f8\u4fe1\u6bcf\u4e2a\u6b63\u786e\u8ba1\u5212\u90fd\u4f1a\u8f93\u51fa\u540c\u6837\u7684\u884c\u96c6\u3002\uff09", "rows \u5bb9\u6613\u4ee4\u4eba\u8bef\u89e3\uff1a\u5b83\u8868\u793a\u8282\u70b9\u8f93\u51fa\u7684\u884c\u6570\uff0c\u800c\u4e0d\u662f\u5904\u7406\u6216\u626b\u63cf\u7684\u884c\u6570\u3002\u8282\u70b9\u5e94\u7528 WHERE \u6761\u4ef6\u7b5b\u9009\u540e\uff0c\u8f93\u51fa\u884c\u6570\u901a\u5e38\u5c0f\u4e8e\u626b\u63cf\u884c\u6570\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u9876\u5c42 rows \u4f30\u8ba1\u5e94\u63a5\u8fd1\u67e5\u8be2\u5b9e\u9645\u8fd4\u56de\u3001\u66f4\u65b0\u6216\u5220\u9664\u7684\u884c\u6570\u3002", "\u6b64\u8ba1\u5212\u5305\u542b\u4e00\u4e2a\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\uff0c\u4ee5\u4e24\u4e2a\u8868\u626b\u63cf\u4f5c\u4e3a\u8f93\u5165\uff0c\u5373\u5b50\u8282\u70b9\u3002\u8282\u70b9\u6458\u8981\u884c\u7684\u7f29\u8fdb\u53cd\u6620\u8ba1\u5212\u6811\u7ed3\u6784\u3002\u8fde\u63a5\u7684\u7b2c\u4e00\u4e2a\u5b50\u8282\u70b9\uff08\u5916\u4fa7\u5b50\u8282\u70b9\uff09\u662f\u524d\u9762\u89c1\u8fc7\u7684\u4f4d\u56fe\u626b\u63cf\u3002\u5b83\u7684\u4ee3\u4ef7\u548c\u884c\u6570\u4e0e SELECT ... WHERE unique1 < 10 \u76f8\u540c\uff0c\u56e0\u4e3a\u8be5\u8282\u70b9\u5e94\u7528\u4e86 WHERE \u6761\u4ef6 unique1 < 10\u3002t1.unique2 = t2.unique2 \u6761\u4ef6\u6b64\u65f6\u5c1a\u4e0d\u76f8\u5173\uff0c\u56e0\u6b64\u4e0d\u4f1a\u5f71\u54cd\u5916\u4fa7\u626b\u63cf\u7684\u884c\u6570\u3002\u5bf9\u4e8e\u4ece\u5916\u4fa7\u5b50\u8282\u70b9\u83b7\u53d6\u7684\u6bcf\u4e00\u884c\uff0c\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\u90fd\u4f1a\u6267\u884c\u4e00\u6b21\u7b2c\u4e8c\u4e2a\u5b50\u8282\u70b9\uff08\u5185\u4fa7\u5b50\u8282\u70b9\uff09\u3002\u5f53\u524d\u5916\u4fa7\u884c\u7684\u5217\u503c\u53ef\u4ee5\u4ee3\u5165\u5185\u4fa7\u626b\u63cf\uff1b\u8fd9\u91cc\u53ef\u4f7f\u7528\u5916\u4fa7\u884c\u7684 t1.unique2 \u503c\uff0c\u56e0\u6b64\u5f97\u5230\u7684\u8ba1\u5212\u548c\u4ee3\u4ef7\u4e0e\u4e0a\u6587\u7b80\u5355\u7684 SELECT ... WHERE t2.unique2 = constant \u60c5\u51b5\u7c7b\u4f3c\u3002\uff08\u4f30\u8ba1\u4ee3\u4ef7\u5b9e\u9645\u7565\u4f4e\u4e8e\u4e0a\u4f8b\uff0c\u8fd9\u662f\u56e0\u4e3a\u9884\u8ba1\u53cd\u590d\u626b\u63cf t2 \u7d22\u5f15\u65f6\u4f1a\u4ea7\u751f\u7f13\u5b58\u6536\u76ca\u3002\uff09\u5faa\u73af\u8282\u70b9\u7684\u4ee3\u4ef7\u7531\u5916\u4fa7\u626b\u63cf\u4ee3\u4ef7\u3001\u6bcf\u4e2a\u5916\u4fa7\u884c\u6267\u884c\u4e00\u6b21\u5185\u4fa7\u626b\u63cf\u7684\u4ee3\u4ef7\uff08\u672c\u4f8b\u4e3a 10 * 7.91\uff09\uff0c\u4ee5\u53ca\u5c11\u91cf\u8fde\u63a5\u5904\u7406\u6240\u9700\u7684 CPU \u65f6\u95f4\u7ec4\u6210\u3002", "\u53ef\u4f7f\u7528 EXPLAIN \u7684 ANALYZE \u9009\u9879\u68c0\u67e5\u89c4\u5212\u5668\u4f30\u7b97\u662f\u5426\u51c6\u786e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\uff0cEXPLAIN \u4f1a\u5b9e\u9645\u6267\u884c\u67e5\u8be2\uff0c\u7136\u540e\u663e\u793a\u6bcf\u4e2a\u8ba1\u5212\u8282\u70b9\u7d2f\u8ba1\u7684\u771f\u5b9e\u884c\u6570\u548c\u771f\u5b9e\u8fd0\u884c\u65f6\u95f4\uff0c\u4ee5\u53ca\u666e\u901a EXPLAIN \u6240\u663e\u793a\u7684\u4f30\u7b97\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u80fd\u5f97\u5230\u5982\u4e0b\u7ed3\u679c\uff1a", "\u7531\u4e8e\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u5c06\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u6267\u884c\u5230\u5e95\uff0c\u56e0\u6b64\u4e0d\u80fd\u7b80\u5355\u5730\u62ff\u4e00\u4e2a\u666e\u901a\u67e5\u8be2\u8ba1\u5212\u5e76\u8ba9\u591a\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u540c\u65f6\u8fd0\u884c\u3002\u90a3\u6837\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u751f\u6210\u5b8c\u6574\u8f93\u51fa\u7ed3\u679c\u96c6\u7684\u4e00\u4efd\u526f\u672c\uff0c\u6240\u4ee5\u67e5\u8be2\u4e0d\u4ec5\u4e0d\u4f1a\u6bd4\u5e73\u5e38\u66f4\u5feb\uff0c\u53cd\u800c\u4f1a\u4ea7\u751f\u9519\u8bef\u7ed3\u679c\u3002\u76f8\u53cd\uff0c\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u5fc5\u987b\u662f\u67e5\u8be2\u4f18\u5316\u5668\u5185\u90e8\u6240\u8bf4\u7684 \u90e8\u5206\u8ba1\u5212 \uff1b\u4e5f\u5c31\u662f\u8bf4\uff0c\u5b83\u5fc5\u987b\u88ab\u6784\u9020\u4e3a\u4f7f\u6267\u884c\u8be5\u8ba1\u5212\u7684\u6bcf\u4e2a\u8fdb\u7a0b\u53ea\u751f\u6210\u8f93\u51fa\u884c\u7684\u4e00\u4e2a\u5b50\u96c6\uff0c\u5e76\u4e14\u4fdd\u8bc1\u6bcf\u4e00\u6761\u6240\u9700\u8f93\u51fa\u884c\u90fd\u6070\u597d\u7531\u67d0\u4e2a\u534f\u4f5c\u8fdb\u7a0b\u751f\u6210\u4e00\u6b21\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u8fd9\u610f\u5473\u7740\u67e5\u8be2\u9a71\u52a8\u8868\u4e0a\u7684\u626b\u63cf\u5fc5\u987b\u662f\u5e76\u884c\u611f\u77e5\u626b\u63cf\u3002", "PostgreSQL \u901a\u8fc7\u5206\u4e24\u4e2a\u9636\u6bb5\u8fdb\u884c\u805a\u5408\u6765\u652f\u6301\u5e76\u884c\u805a\u5408\u3002\u9996\u5148\uff0c\u6bcf\u4e2a\u53c2\u4e0e\u67e5\u8be2\u5e76\u884c\u90e8\u5206\u7684\u8fdb\u7a0b\u6267\u884c\u4e00\u4e2a\u805a\u5408\u6b65\u9aa4\uff0c\u4e3a\u8be5\u8fdb\u7a0b\u6240\u89c1\u5230\u7684\u6bcf\u4e2a\u5206\u7ec4\u4ea7\u751f\u4e00\u4e2a\u90e8\u5206\u7ed3\u679c\u3002\u8fd9\u5728\u8ba1\u5212\u4e2d\u4f53\u73b0\u4e3a\u4e00\u4e2a Partial Aggregate \u8282\u70b9\u3002\u7136\u540e\uff0c\u90e8\u5206\u7ed3\u679c\u901a\u8fc7 Gather \u6216 Gather Merge \u4f20\u9001\u7ed9\u9886\u5bfc\u8005\u3002\u6700\u540e\uff0c\u9886\u5bfc\u8005\u4f1a\u628a\u6765\u81ea\u6240\u6709\u5de5\u4f5c\u8fdb\u7a0b\u7684\u7ed3\u679c\u518d\u6b21\u805a\u5408\uff0c\u4ee5\u4ea7\u751f\u6700\u7ec8\u7ed3\u679c\u3002\u8fd9\u5728\u8ba1\u5212\u4e2d\u4f53\u73b0\u4e3a\u4e00\u4e2a Finalize Aggregate \u8282\u70b9\u3002"]}, {"title": "\u6267\u884c\u5668\u5b9e\u73b0\u8bf4\u660e", "paragraphs": ["nodeResult.c\uff1a\u652f\u6301\u9700\u8981\u7279\u6b8a\u4ee3\u7801\u7684\u5e38\u91cf\u8282\u70b9\u3002", "Result \u8282\u70b9\u7528\u4e8e\u4e0d\u626b\u63cf\u4efb\u4f55\u5173\u7cfb\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\uff08\u8bf7\u8bb0\u4f4f\uff0cINSERT \u6216 UPDATE \u9700\u8981\u4e00\u68f5\u751f\u6210\u65b0\u884c\u7684\u8ba1\u5212\u6811\u3002\uff09", "Result \u8282\u70b9\u4e5f\u7528\u4e8e\u4f18\u5316\u5e26\u6709\u5e38\u91cf\u6761\u4ef6\uff08\u5373\u4e0d\u4f9d\u8d56\u626b\u63cf\u6570\u636e\u7684\u6761\u4ef6\uff09\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\u8fd0\u884c\u65f6\uff0cResult \u8282\u70b9\u53ea\u8ba1\u7b97\u4e00\u6b21\u5e38\u91cf\u6761\u4ef6\uff0cEXPLAIN \u5c06\u5176\u663e\u793a\u4e3a One-Time Filter\u3002\u5982\u679c\u6761\u4ef6\u4e3a\u5047\uff0c\u65e0\u9700\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u4fbf\u53ef\u8fd4\u56de\u7a7a\u7ed3\u679c\u96c6\uff1b\u5982\u679c\u4e3a\u771f\uff0c\u5219\u6b63\u5e38\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u5e76\u4f20\u56de\u7ed3\u679c\u3002"]}, {"code": "case T_Result:\n\t\t\tpname = sname = \"Result\";\n\t\t\tbreak;", "title": "\u6838\u5fc3\u6e90\u7801\u4e2d\u7684 EXPLAIN \u6807\u8bc6"}], "strategies": [], "description": ["\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002"], "localization": {"status": "complete", "sources": [{"url": "/docs/12/functions-array.html", "method": "same-major semantic node", "sha256": "ac0d003a8f813046fffcac244b765dc49c14a67f834bea6c4e1a3e77623c07ef", "language": "zh", "matched_nodes": ["#FUNCTIONS-ARRAY/div[2]/div[1]/table[0]/thead[1]/tr[0]/th[3]"]}, {"url": "/docs/12/parallel-plans.html", "method": "same-major semantic node", "sha256": "4aaca92475f243dcddffd80d9af558330f8f3b0ac3cbe8872b0d2901e14fe684", "language": "zh", "matched_nodes": ["#PARALLEL-PLANS/div[5]/p[1]", "#PARALLEL-PLANS/p[2]"]}], "language": "zh", "original_text": {"/versions/12/description/0": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/versions/12/facts/0/label": "Core node tag", "/versions/12/facts/1/label": "Structured EXPLAIN Node Type", "/versions/12/facts/1/value": "Result", "/versions/12/facts/2/label": "Inputs", "/versions/12/facts/2/value": "Optional child plan", "/versions/12/facts/3/label": "Output", "/versions/12/facts/3/value": "Projected tuples", "/versions/12/facts/4/label": "Executor initializer", "/versions/12/facts/5/label": "Memory mechanism", "/versions/12/tables/0/title": "EXPLAIN labels in this source build", "/versions/12/related/1/label": "Using EXPLAIN", "/versions/12/related/2/label": "Parallel plans", "/versions/12/sections/0/title": "EXPLAIN names and attributes", "/versions/12/sections/1/title": "Memory and temporary storage", "/versions/12/sections/2/title": "Parallel execution and instrumentation", "/versions/12/sections/3/title": "Same-version manual discussion", "/versions/12/sections/4/title": "Executor implementation notes", "/versions/12/sections/5/title": "EXPLAIN identity in core source", "/versions/12/memory/description": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/12/tables/0/rows/0/label": "Result", "/versions/12/sections/0/paragraphs/0": "Structured formats use the Node Type above. Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.", "/versions/12/sections/0/paragraphs/1": "Text names recorded by this source: Result.", "/versions/12/sections/0/paragraphs/2": "Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node.", "/versions/12/sections/1/paragraphs/0": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/12/sections/2/paragraphs/0": "The source callbacks below can coordinate execution or collect worker instrumentation. Their presence is not a blanket claim that this node supports a shared parallel scan or shared state.", "/versions/12/sections/2/paragraphs/1": "Callbacks in this build: none extracted from this node implementation.", "/versions/12/sections/3/paragraphs/0": "It's important to understand that the cost of an upper-level node includes the cost of all its child nodes. It's also important to realize that the cost only reflects things that the planner cares about. In particular, the cost does not consider the time spent transmitting result rows to the client, which could be an important factor in the real elapsed time; but the planner ignores it because it cannot change it by altering the plan. (Every correct plan will output the same row set, we trust.)", "/versions/12/sections/3/paragraphs/1": "The rows value is a little tricky because it is not the number of rows processed or scanned by the plan node, but rather the number emitted by the node. This is often less than the number scanned, as a result of filtering by any WHERE -clause conditions that are being applied at the node. Ideally the top-level rows estimate will approximate the number of rows actually returned, updated, or deleted by the query.", "/versions/12/sections/3/paragraphs/2": "In this plan, we have a nested-loop join node with two table scans as inputs, or children. The indentation of the node summary lines reflects the plan tree structure. The join's first, or \u201c outer \u201d , child is a bitmap scan similar to those we saw before. Its cost and row count are the same as we'd get from SELECT ... WHERE unique1 < 10 because we are applying the WHERE clause unique1 < 10 at that node. The t1.unique2 = t2.unique2 clause is not relevant yet, so it doesn't affect the row count of the outer scan. The nested-loop join node will run its second, or \u201c inner \u201d child once for each row obtained from the outer child. Column values from the current outer row can be plugged into the inner scan; here, the t1.unique2 value from the outer row is available, so we get a plan and costs similar to what we saw above for a simple SELECT ... WHERE t2.unique2 = constant case. (The estimated cost is actually a bit lower than what was seen above, as a result of caching that's expected to occur during the repeated index scans on t2 .) The costs of the loop node are then set on the basis of the cost of the outer scan, plus one repetition of the inner scan for each outer row (10 * 7.91, here), plus a little CPU time for join processing.", "/versions/12/sections/3/paragraphs/3": "It is possible to check the accuracy of the planner's estimates by using EXPLAIN 's ANALYZE option. With this option, EXPLAIN actually executes the query, and then displays the true row counts and true run time accumulated within each plan node, along with the same estimates that a plain EXPLAIN shows. For example, we might get a result like this:", "/versions/12/sections/3/paragraphs/4": "Because each worker executes the parallel portion of the plan to completion, it is not possible to simply take an ordinary query plan and run it using multiple workers. Each worker would produce a full copy of the output result set, so the query would not run any faster than normal but would produce incorrect results. Instead, the parallel portion of the plan must be what is known internally to the query optimizer as a partial plan ; that is, it must be constructed so that each process that executes the plan will generate only a subset of the output rows in such a way that each required output row is guaranteed to be generated by exactly one of the cooperating processes. Generally, this means that the scan on the driving table of the query must be a parallel-aware scan.", "/versions/12/sections/3/paragraphs/5": "PostgreSQL supports parallel aggregation by aggregating in two stages. First, each process participating in the parallel portion of the query performs an aggregation step, producing a partial result for each group of which that process is aware. This is reflected in the plan as a Partial Aggregate node. Second, the partial results are transferred to the leader via Gather or Gather Merge . Finally, the leader re-aggregates the results across all workers in order to produce the final result. This is reflected in the plan as a Finalize Aggregate node.", "/versions/12/sections/4/paragraphs/0": "nodeResult.c support for constant nodes needing special code.", "/versions/12/sections/4/paragraphs/1": "Result nodes are used in queries where no relations are scanned. Examples of such queries are:", "/versions/12/sections/4/paragraphs/2": "(Remember that in an INSERT or UPDATE, we need a plan tree that generates the new rows.)", "/versions/12/sections/4/paragraphs/3": "Result nodes are also used to optimise queries with constant qualifications (ie, quals that do not depend on the scanned data), such as:", "/versions/12/sections/4/paragraphs/4": "At runtime, the Result node evaluates the constant qual once, which is shown by EXPLAIN as a One-Time Filter. If it's false, we can return an empty result set without running the controlled plan at all. If it's true, we run the controlled plan normally and pass back the results.", "/versions/12/tables/0/columns/0/label": "Text-format label", "/versions/12/tables/0/columns/1/label": "Structured node identity", "/versions/12/tables/0/rows/0/identity": "Result"}, "fallback_fields": [], "source_language": "en", "original_snapshot_sha256": "de8b4660bb9c4fbb66c2bc1ce6a4f21038cda8534f63958aa569e1fd11facfaa"}, "evidence_kind": "source and documentation", "explain_names": ["Result"], "partial_modes": [], "comparison_data": {"node_tag": "T_Result", "strategies": [], "text_names": ["Result"], "initializer": "ExecInitResult", "partial_modes": [], "memory_mechanism": "unclassified", "parallel_callbacks": []}, "comparison_hash": "7d9e21f5e91321228505ba502e7faa5b9ebdda5ba4d71b8a9b97571a1f87b5f5", "explain_prefixes": ["Parallel"], "runtime_verified": false, "source_inventory": {"explain": "src/backend/commands/explain.c", "executor": "src/backend/executor/execProcnode.c", "implementation": "src/backend/executor/nodeResult.c"}, "parallel_callbacks": []}, "13": {"facts": [{"label": "\u6838\u5fc3\u8282\u70b9\u6807\u7b7e", "value": "T_Result"}, {"label": "\u7ed3\u6784\u5316 EXPLAIN \u8282\u70b9\u7c7b\u578b", "value": "Result"}, {"label": "\u8f93\u5165", "value": "\u53ef\u9009\u7684\u5b50\u8ba1\u5212"}, {"label": "\u8f93\u51fa", "value": "\u6295\u5f71\u540e\u7684\u5143\u7ec4"}, {"label": "\u6267\u884c\u5668\u521d\u59cb\u5316\u51fd\u6570", "value": "ExecInitResult"}, {"label": "\u5185\u5b58\u673a\u5236", "value": "unclassified"}], "memory": {"evidence": [{"url": "https://ftp.postgresql.org/pub/source/v13.23/postgresql-13.23.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "6fb1e0c3c13a0f6b6f91ae0edea8e37b05088927dd2e2877bc97bee79639f4a9", "archive_sha256": "6ec3c82726af92b7dec873fa1cdf881eca92a4219787dfad05acb6b10e041fd6"}], "mechanism": "unclassified", "description": "\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002", "source_notes": []}, "tables": [{"key": "explain-labels", "rows": [{"label": "Result", "identity": "Result"}], "title": "\u672c\u6784\u5efa\u4e2d\u7684 EXPLAIN \u6807\u7b7e", "columns": [{"key": "label", "label": "\u6587\u672c\u683c\u5f0f\u6807\u7b7e"}, {"key": "identity", "label": "\u7ed3\u6784\u5316\u8282\u70b9\u6807\u8bc6"}]}], "related": [{"url": "/wiki/sql/explain/?v=13", "label": "EXPLAIN"}, {"url": "/docs/13/using-explain.html", "label": "\u4f7f\u7528 EXPLAIN"}, {"url": "/docs/13/parallel-plans.html", "label": "\u5e76\u884c\u8ba1\u5212"}], "release": {"ref": "PostgreSQL 13.23 source archive", "label": "13.23", "major": "13", "channel": "historical", "revision": "6ec3c82726af92b7dec873fa1cdf881eca92a4219787dfad05acb6b10e041fd6", "source_url": "https://ftp.postgresql.org/pub/source/v13.23/postgresql-13.23.tar.bz2", "source_snapshot_utc": ""}, "sources": [{"url": "https://ftp.postgresql.org/pub/source/v13.23/postgresql-13.23.tar.bz2", "line": 1136, "path": "src/backend/commands/explain.c", "label": "src/backend/commands/explain.c:1136", "sha256": "541713e0e7f1c9cc352c2b6028964d440c19d2678a4463000094c24a88c1e730", "archive_sha256": "6ec3c82726af92b7dec873fa1cdf881eca92a4219787dfad05acb6b10e041fd6"}, {"url": "https://ftp.postgresql.org/pub/source/v13.23/postgresql-13.23.tar.bz2", "line": 164, "path": "src/backend/executor/execProcnode.c", "label": "src/backend/executor/execProcnode.c:164", "sha256": "d085ee99acfa00587e6ade3a1d9f8108a0566beedbbee3f54a50c9fc0cc2e875", "archive_sha256": "6ec3c82726af92b7dec873fa1cdf881eca92a4219787dfad05acb6b10e041fd6"}, {"url": "https://ftp.postgresql.org/pub/source/v13.23/postgresql-13.23.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "6fb1e0c3c13a0f6b6f91ae0edea8e37b05088927dd2e2877bc97bee79639f4a9", "archive_sha256": "6ec3c82726af92b7dec873fa1cdf881eca92a4219787dfad05acb6b10e041fd6"}, {"url": "https://ftp.postgresql.org/pub/source/v13.23/postgresql-13.23.tar.bz2", "path": "src/include/nodes/plannodes.h", "label": "src/include/nodes/plannodes.h", "sha256": "dcb296833777b02008c4b6bae8e8f7c6423b7ffba21f36702597c9d596d039ab", "archive_sha256": "6ec3c82726af92b7dec873fa1cdf881eca92a4219787dfad05acb6b10e041fd6"}, {"url": "https://pg.center/docs/13/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 13.23 \u00b7 using-explain", "sha256": "650fd8629382d5dc8f9f8412c50ec5f32442a9ad2f98ca88e5348a7c2bd0ac7a", "language": "en", "original_url": "/docs/13/using-explain.html#USING-EXPLAIN-BASICS"}, {"url": "https://pg.center/docs/13/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 13.23 \u00b7 using-explain", "sha256": "650fd8629382d5dc8f9f8412c50ec5f32442a9ad2f98ca88e5348a7c2bd0ac7a", "language": "en", "original_url": "/docs/13/using-explain.html#USING-EXPLAIN-ANALYZE"}, {"url": "https://pg.center/docs/13/parallel-plans.html#PARALLEL-PLANS", "path": "parallel-plans.html", "label": "PostgreSQL 13.23 \u00b7 parallel-plans", "sha256": "025ad8564a8461b676c9153f9e084429cca0ef86c968090689b082120060f3d0", "language": "en", "original_url": "/docs/13/parallel-plans.html#PARALLEL-PLANS"}], "node_tag": "T_Result", "sections": [{"title": "EXPLAIN \u540d\u79f0\u4e0e\u5c5e\u6027", "paragraphs": ["\u7ed3\u6784\u5316\u683c\u5f0f\u4f7f\u7528\u4e0a\u8ff0 Node Type\u3002\u6587\u672c\u683c\u5f0f\u540d\u79f0\u8fd8\u53ef\u80fd\u5305\u542b\u64cd\u4f5c\u3001\u7b56\u7565\u3001\u8fde\u63a5\u7c7b\u578b\u3001\u626b\u63cf\u65b9\u5411\u6216\u805a\u5408\u9636\u6bb5\u5c5e\u6027\u3002", "\u6b64\u6e90\u7801\u8bb0\u5f55\u7684\u6587\u672c\u540d\u79f0\uff1aResult.", "\u5e76\u884c\u611f\u77e5\u4e0e\u5e76\u884c\u5b89\u5168\u662f\u4e0d\u540c\u7684\u8ba1\u5212\u5c5e\u6027\u3002\u5728\u5e76\u884c\u5de5\u4f5c\u8fdb\u7a0b\u5185\u8fd0\u884c\u7684\u8282\u70b9\u4e0d\u4e00\u5b9a\u662f\u5e76\u884c\u611f\u77e5\u8282\u70b9\u3002"]}, {"title": "\u5185\u5b58\u4e0e\u4e34\u65f6\u5b58\u50a8", "paragraphs": ["\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002"]}, {"title": "\u5e76\u884c\u6267\u884c\u4e0e\u8fd0\u884c\u4fe1\u606f\u91c7\u96c6", "paragraphs": ["\u4ee5\u4e0b\u6e90\u7801\u56de\u8c03\u53ef\u4ee5\u534f\u8c03\u6267\u884c\u6216\u6536\u96c6\u5de5\u4f5c\u8fdb\u7a0b\u7684\u6d4b\u91cf\u6570\u636e\u3002\u56de\u8c03\u5b58\u5728\u4e0d\u4ee3\u8868\u8be5\u8282\u70b9\u666e\u904d\u652f\u6301\u5171\u4eab\u5e76\u884c\u626b\u63cf\u6216\u5171\u4eab\u72b6\u6001\u3002", "\u6b64\u6784\u5efa\u7684\u56de\u8c03\uff1anone extracted from this node implementation."]}, {"title": "\u540c\u7248\u672c\u624b\u518c\u8bf4\u660e", "paragraphs": ["\u9700\u8981\u7406\u89e3\uff0c\u4e0a\u5c42\u8282\u70b9\u7684\u4ee3\u4ef7\u5305\u542b\u5176\u5168\u90e8\u5b50\u8282\u70b9\u7684\u4ee3\u4ef7\u3002\u540c\u65f6\uff0c\u4ee3\u4ef7\u4ec5\u53cd\u6620\u89c4\u5212\u5668\u5173\u6ce8\u7684\u56e0\u7d20\u3002\u5c24\u5176\u662f\uff0c\u4ee3\u4ef7\u4e0d\u5305\u542b\u5411\u5ba2\u6237\u7aef\u4f20\u8f93\u7ed3\u679c\u884c\u6240\u82b1\u8d39\u7684\u65f6\u95f4\uff0c\u5c3d\u7ba1\u5b83\u53ef\u80fd\u663e\u8457\u5f71\u54cd\u5b9e\u9645\u8017\u65f6\uff1b\u89c4\u5212\u5668\u5ffd\u7565\u5b83\uff0c\u662f\u56e0\u4e3a\u6539\u53d8\u8ba1\u5212\u65e0\u6cd5\u6539\u53d8\u8fd9\u90e8\u5206\u65f6\u95f4\u3002\uff08\u6211\u4eec\u76f8\u4fe1\u6bcf\u4e2a\u6b63\u786e\u8ba1\u5212\u90fd\u4f1a\u8f93\u51fa\u540c\u6837\u7684\u884c\u96c6\u3002\uff09", "rows \u5bb9\u6613\u4ee4\u4eba\u8bef\u89e3\uff1a\u5b83\u8868\u793a\u8282\u70b9\u8f93\u51fa\u7684\u884c\u6570\uff0c\u800c\u4e0d\u662f\u5904\u7406\u6216\u626b\u63cf\u7684\u884c\u6570\u3002\u8282\u70b9\u5e94\u7528 WHERE \u6761\u4ef6\u7b5b\u9009\u540e\uff0c\u8f93\u51fa\u884c\u6570\u901a\u5e38\u5c0f\u4e8e\u626b\u63cf\u884c\u6570\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u9876\u5c42 rows \u4f30\u8ba1\u5e94\u63a5\u8fd1\u67e5\u8be2\u5b9e\u9645\u8fd4\u56de\u3001\u66f4\u65b0\u6216\u5220\u9664\u7684\u884c\u6570\u3002", "\u4e0e\u666e\u901a\u6392\u5e8f\u76f8\u6bd4\uff0c\u589e\u91cf\u6392\u5e8f\u53ef\u5728\u6574\u4e2a\u7ed3\u679c\u96c6\u5c1a\u672a\u6392\u5b8c\u65f6\u5c31\u8fd4\u56de\u5143\u7ec4\uff0c\u5c24\u5176\u6709\u5229\u4e8e\u4f18\u5316\u5e26 LIMIT \u7684\u67e5\u8be2\u3002\u5b83\u8fd8\u53ef\u80fd\u51cf\u5c11\u5185\u5b58\u7528\u91cf\u548c\u6392\u5e8f\u6ea2\u5199\u78c1\u76d8\u7684\u6982\u7387\uff0c\u4f46\u4ee3\u4ef7\u662f\u5c06\u7ed3\u679c\u96c6\u62c6\u6210\u591a\u4e2a\u6392\u5e8f\u6279\u6b21\u6240\u5e26\u6765\u7684\u989d\u5916\u5f00\u9500\u3002", "\u6b64\u8ba1\u5212\u5305\u542b\u4e00\u4e2a\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\uff0c\u4ee5\u4e24\u4e2a\u8868\u626b\u63cf\u4f5c\u4e3a\u8f93\u5165\uff0c\u5373\u5b50\u8282\u70b9\u3002\u8282\u70b9\u6458\u8981\u884c\u7684\u7f29\u8fdb\u53cd\u6620\u8ba1\u5212\u6811\u7ed3\u6784\u3002\u8fde\u63a5\u7684\u7b2c\u4e00\u4e2a\u5b50\u8282\u70b9\uff08\u5916\u4fa7\u5b50\u8282\u70b9\uff09\u662f\u524d\u9762\u89c1\u8fc7\u7684\u4f4d\u56fe\u626b\u63cf\u3002\u5b83\u7684\u4ee3\u4ef7\u548c\u884c\u6570\u4e0e SELECT ... WHERE unique1 < 10 \u76f8\u540c\uff0c\u56e0\u4e3a\u8be5\u8282\u70b9\u5e94\u7528\u4e86 WHERE \u6761\u4ef6 unique1 < 10\u3002t1.unique2 = t2.unique2 \u6761\u4ef6\u6b64\u65f6\u5c1a\u4e0d\u76f8\u5173\uff0c\u56e0\u6b64\u4e0d\u4f1a\u5f71\u54cd\u5916\u4fa7\u626b\u63cf\u7684\u884c\u6570\u3002\u5bf9\u4e8e\u4ece\u5916\u4fa7\u5b50\u8282\u70b9\u83b7\u53d6\u7684\u6bcf\u4e00\u884c\uff0c\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\u90fd\u4f1a\u6267\u884c\u4e00\u6b21\u7b2c\u4e8c\u4e2a\u5b50\u8282\u70b9\uff08\u5185\u4fa7\u5b50\u8282\u70b9\uff09\u3002\u5f53\u524d\u5916\u4fa7\u884c\u7684\u5217\u503c\u53ef\u4ee5\u4ee3\u5165\u5185\u4fa7\u626b\u63cf\uff1b\u8fd9\u91cc\u53ef\u4f7f\u7528\u5916\u4fa7\u884c\u7684 t1.unique2 \u503c\uff0c\u56e0\u6b64\u5f97\u5230\u7684\u8ba1\u5212\u548c\u4ee3\u4ef7\u4e0e\u4e0a\u6587\u7b80\u5355\u7684 SELECT ... WHERE t2.unique2 = constant \u60c5\u51b5\u7c7b\u4f3c\u3002\uff08\u4f30\u8ba1\u4ee3\u4ef7\u5b9e\u9645\u7565\u4f4e\u4e8e\u4e0a\u4f8b\uff0c\u8fd9\u662f\u56e0\u4e3a\u9884\u8ba1\u53cd\u590d\u626b\u63cf t2 \u7d22\u5f15\u65f6\u4f1a\u4ea7\u751f\u7f13\u5b58\u6536\u76ca\u3002\uff09\u5faa\u73af\u8282\u70b9\u7684\u4ee3\u4ef7\u7531\u5916\u4fa7\u626b\u63cf\u4ee3\u4ef7\u3001\u6bcf\u4e2a\u5916\u4fa7\u884c\u6267\u884c\u4e00\u6b21\u5185\u4fa7\u626b\u63cf\u7684\u4ee3\u4ef7\uff08\u672c\u4f8b\u4e3a 10 * 7.91\uff09\uff0c\u4ee5\u53ca\u5c11\u91cf\u8fde\u63a5\u5904\u7406\u6240\u9700\u7684 CPU \u65f6\u95f4\u7ec4\u6210\u3002", "\u53ef\u4f7f\u7528 EXPLAIN \u7684 ANALYZE \u9009\u9879\u68c0\u67e5\u89c4\u5212\u5668\u4f30\u7b97\u662f\u5426\u51c6\u786e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\uff0cEXPLAIN \u4f1a\u5b9e\u9645\u6267\u884c\u67e5\u8be2\uff0c\u7136\u540e\u663e\u793a\u6bcf\u4e2a\u8ba1\u5212\u8282\u70b9\u7d2f\u8ba1\u7684\u771f\u5b9e\u884c\u6570\u548c\u771f\u5b9e\u8fd0\u884c\u65f6\u95f4\uff0c\u4ee5\u53ca\u666e\u901a EXPLAIN \u6240\u663e\u793a\u7684\u4f30\u7b97\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u80fd\u5f97\u5230\u5982\u4e0b\u7ed3\u679c\uff1a", "\u7531\u4e8e\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u5c06\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u6267\u884c\u5230\u5e95\uff0c\u56e0\u6b64\u4e0d\u80fd\u7b80\u5355\u5730\u62ff\u4e00\u4e2a\u666e\u901a\u67e5\u8be2\u8ba1\u5212\u5e76\u8ba9\u591a\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u540c\u65f6\u8fd0\u884c\u3002\u90a3\u6837\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u751f\u6210\u5b8c\u6574\u8f93\u51fa\u7ed3\u679c\u96c6\u7684\u4e00\u4efd\u526f\u672c\uff0c\u6240\u4ee5\u67e5\u8be2\u4e0d\u4ec5\u4e0d\u4f1a\u6bd4\u5e73\u5e38\u66f4\u5feb\uff0c\u53cd\u800c\u4f1a\u4ea7\u751f\u9519\u8bef\u7ed3\u679c\u3002\u76f8\u53cd\uff0c\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u5fc5\u987b\u662f\u67e5\u8be2\u4f18\u5316\u5668\u5185\u90e8\u6240\u8bf4\u7684 \u90e8\u5206\u8ba1\u5212 \uff1b\u4e5f\u5c31\u662f\u8bf4\uff0c\u5b83\u5fc5\u987b\u88ab\u6784\u9020\u4e3a\u4f7f\u6267\u884c\u8be5\u8ba1\u5212\u7684\u6bcf\u4e2a\u8fdb\u7a0b\u53ea\u751f\u6210\u8f93\u51fa\u884c\u7684\u4e00\u4e2a\u5b50\u96c6\uff0c\u5e76\u4e14\u4fdd\u8bc1\u6bcf\u4e00\u6761\u6240\u9700\u8f93\u51fa\u884c\u90fd\u6070\u597d\u7531\u67d0\u4e2a\u534f\u4f5c\u8fdb\u7a0b\u751f\u6210\u4e00\u6b21\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u8fd9\u610f\u5473\u7740\u67e5\u8be2\u9a71\u52a8\u8868\u4e0a\u7684\u626b\u63cf\u5fc5\u987b\u662f\u5e76\u884c\u611f\u77e5\u626b\u63cf\u3002"]}, {"title": "\u6267\u884c\u5668\u5b9e\u73b0\u8bf4\u660e", "paragraphs": ["nodeResult.c\uff1a\u652f\u6301\u9700\u8981\u7279\u6b8a\u4ee3\u7801\u7684\u5e38\u91cf\u8282\u70b9\u3002", "Result \u8282\u70b9\u7528\u4e8e\u4e0d\u626b\u63cf\u4efb\u4f55\u5173\u7cfb\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\uff08\u8bf7\u8bb0\u4f4f\uff0cINSERT \u6216 UPDATE \u9700\u8981\u4e00\u68f5\u751f\u6210\u65b0\u884c\u7684\u8ba1\u5212\u6811\u3002\uff09", "Result \u8282\u70b9\u4e5f\u7528\u4e8e\u4f18\u5316\u5e26\u6709\u5e38\u91cf\u6761\u4ef6\uff08\u5373\u4e0d\u4f9d\u8d56\u626b\u63cf\u6570\u636e\u7684\u6761\u4ef6\uff09\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\u8fd0\u884c\u65f6\uff0cResult \u8282\u70b9\u53ea\u8ba1\u7b97\u4e00\u6b21\u5e38\u91cf\u6761\u4ef6\uff0cEXPLAIN \u5c06\u5176\u663e\u793a\u4e3a One-Time Filter\u3002\u5982\u679c\u6761\u4ef6\u4e3a\u5047\uff0c\u65e0\u9700\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u4fbf\u53ef\u8fd4\u56de\u7a7a\u7ed3\u679c\u96c6\uff1b\u5982\u679c\u4e3a\u771f\uff0c\u5219\u6b63\u5e38\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u5e76\u4f20\u56de\u7ed3\u679c\u3002"]}, {"code": "case T_Result:\n\t\t\tpname = sname = \"Result\";\n\t\t\tbreak;", "title": "\u6838\u5fc3\u6e90\u7801\u4e2d\u7684 EXPLAIN \u6807\u8bc6"}], "strategies": [], "description": ["\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002"], "localization": {"status": "complete", "sources": [{"url": "/docs/13/parallel-plans.html", "method": "same-major semantic node", "sha256": "bbbbbd9cc27db6811c388e9c4951a9641c48871942bc709cec203e4271518c50", "language": "zh", "matched_nodes": ["#PARALLEL-PLANS/p[2]"]}], "language": "zh", "original_text": {"/versions/13/description/0": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/versions/13/facts/0/label": "Core node tag", "/versions/13/facts/1/label": "Structured EXPLAIN Node Type", "/versions/13/facts/2/label": "Inputs", "/versions/13/facts/2/value": "Optional child plan", "/versions/13/facts/3/label": "Output", "/versions/13/facts/3/value": "Projected tuples", "/versions/13/facts/4/label": "Executor initializer", "/versions/13/facts/5/label": "Memory mechanism", "/versions/13/tables/0/title": "EXPLAIN labels in this source build", "/versions/13/related/1/label": "Using EXPLAIN", "/versions/13/related/2/label": "Parallel plans", "/versions/13/sections/0/title": "EXPLAIN names and attributes", "/versions/13/sections/1/title": "Memory and temporary storage", "/versions/13/sections/2/title": "Parallel execution and instrumentation", "/versions/13/sections/3/title": "Same-version manual discussion", "/versions/13/sections/4/title": "Executor implementation notes", "/versions/13/sections/5/title": "EXPLAIN identity in core source", "/versions/13/memory/description": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/13/sections/0/paragraphs/0": "Structured formats use the Node Type above. Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.", "/versions/13/sections/0/paragraphs/1": "Text names recorded by this source: Result.", "/versions/13/sections/0/paragraphs/2": "Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node.", "/versions/13/sections/1/paragraphs/0": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/13/sections/2/paragraphs/0": "The source callbacks below can coordinate execution or collect worker instrumentation. Their presence is not a blanket claim that this node supports a shared parallel scan or shared state.", "/versions/13/sections/2/paragraphs/1": "Callbacks in this build: none extracted from this node implementation.", "/versions/13/sections/3/paragraphs/0": "It's important to understand that the cost of an upper-level node includes the cost of all its child nodes. It's also important to realize that the cost only reflects things that the planner cares about. In particular, the cost does not consider the time spent transmitting result rows to the client, which could be an important factor in the real elapsed time; but the planner ignores it because it cannot change it by altering the plan. (Every correct plan will output the same row set, we trust.)", "/versions/13/sections/3/paragraphs/1": "The rows value is a little tricky because it is not the number of rows processed or scanned by the plan node, but rather the number emitted by the node. This is often less than the number scanned, as a result of filtering by any WHERE -clause conditions that are being applied at the node. Ideally the top-level rows estimate will approximate the number of rows actually returned, updated, or deleted by the query.", "/versions/13/sections/3/paragraphs/2": "Compared to regular sorts, sorting incrementally allows returning tuples before the entire result set has been sorted, which particularly enables optimizations with LIMIT queries. It may also reduce memory usage and the likelihood of spilling sorts to disk, but it comes at the cost of the increased overhead of splitting the result set into multiple sorting batches.", "/versions/13/sections/3/paragraphs/3": "In this plan, we have a nested-loop join node with two table scans as inputs, or children. The indentation of the node summary lines reflects the plan tree structure. The join's first, or \u201c outer \u201d , child is a bitmap scan similar to those we saw before. Its cost and row count are the same as we'd get from SELECT ... WHERE unique1 < 10 because we are applying the WHERE clause unique1 < 10 at that node. The t1.unique2 = t2.unique2 clause is not relevant yet, so it doesn't affect the row count of the outer scan. The nested-loop join node will run its second, or \u201c inner \u201d child once for each row obtained from the outer child. Column values from the current outer row can be plugged into the inner scan; here, the t1.unique2 value from the outer row is available, so we get a plan and costs similar to what we saw above for a simple SELECT ... WHERE t2.unique2 = constant case. (The estimated cost is actually a bit lower than what was seen above, as a result of caching that's expected to occur during the repeated index scans on t2 .) The costs of the loop node are then set on the basis of the cost of the outer scan, plus one repetition of the inner scan for each outer row (10 * 7.91, here), plus a little CPU time for join processing.", "/versions/13/sections/3/paragraphs/4": "It is possible to check the accuracy of the planner's estimates by using EXPLAIN 's ANALYZE option. With this option, EXPLAIN actually executes the query, and then displays the true row counts and true run time accumulated within each plan node, along with the same estimates that a plain EXPLAIN shows. For example, we might get a result like this:", "/versions/13/sections/3/paragraphs/5": "Because each worker executes the parallel portion of the plan to completion, it is not possible to simply take an ordinary query plan and run it using multiple workers. Each worker would produce a full copy of the output result set, so the query would not run any faster than normal but would produce incorrect results. Instead, the parallel portion of the plan must be what is known internally to the query optimizer as a partial plan ; that is, it must be constructed so that each process that executes the plan will generate only a subset of the output rows in such a way that each required output row is guaranteed to be generated by exactly one of the cooperating processes. Generally, this means that the scan on the driving table of the query must be a parallel-aware scan.", "/versions/13/sections/4/paragraphs/0": "nodeResult.c support for constant nodes needing special code.", "/versions/13/sections/4/paragraphs/1": "Result nodes are used in queries where no relations are scanned. Examples of such queries are:", "/versions/13/sections/4/paragraphs/2": "(Remember that in an INSERT or UPDATE, we need a plan tree that generates the new rows.)", "/versions/13/sections/4/paragraphs/3": "Result nodes are also used to optimise queries with constant qualifications (ie, quals that do not depend on the scanned data), such as:", "/versions/13/sections/4/paragraphs/4": "At runtime, the Result node evaluates the constant qual once, which is shown by EXPLAIN as a One-Time Filter. If it's false, we can return an empty result set without running the controlled plan at all. If it's true, we run the controlled plan normally and pass back the results.", "/versions/13/tables/0/columns/0/label": "Text-format label", "/versions/13/tables/0/columns/1/label": "Structured node identity"}, "fallback_fields": [], "source_language": "en", "original_snapshot_sha256": "dd43785140dae35490a8be38c2cc5072821f2e740fb18434eb2979cf24fbf2c1"}, "evidence_kind": "source and documentation", "explain_names": ["Result"], "partial_modes": [], "comparison_data": {"node_tag": "T_Result", "strategies": [], "text_names": ["Result"], "initializer": "ExecInitResult", "partial_modes": [], "memory_mechanism": "unclassified", "parallel_callbacks": []}, "comparison_hash": "7d9e21f5e91321228505ba502e7faa5b9ebdda5ba4d71b8a9b97571a1f87b5f5", "explain_prefixes": ["Parallel"], "runtime_verified": false, "source_inventory": {"explain": "src/backend/commands/explain.c", "executor": "src/backend/executor/execProcnode.c", "implementation": "src/backend/executor/nodeResult.c"}, "parallel_callbacks": []}, "14": {"facts": [{"label": "\u6838\u5fc3\u8282\u70b9\u6807\u7b7e", "value": "T_Result"}, {"label": "\u7ed3\u6784\u5316 EXPLAIN \u8282\u70b9\u7c7b\u578b", "value": "Result"}, {"label": "\u8f93\u5165", "value": "\u53ef\u9009\u7684\u5b50\u8ba1\u5212"}, {"label": "\u8f93\u51fa", "value": "\u6295\u5f71\u540e\u7684\u5143\u7ec4"}, {"label": "\u6267\u884c\u5668\u521d\u59cb\u5316\u51fd\u6570", "value": "ExecInitResult"}, {"label": "\u5185\u5b58\u673a\u5236", "value": "unclassified"}], "memory": {"evidence": [{"url": "https://ftp.postgresql.org/pub/source/v14.24/postgresql-14.24.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "3e3162c02eb2f4ddc96dbf0ce6ba52c63201b109b8f7face3056c982b4c04095", "archive_sha256": "a7fa7ed3d558172355f51406097a7bd4f6b473be80f311ef7cda96bf383d8897"}], "mechanism": "unclassified", "description": "\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002", "source_notes": []}, "tables": [{"key": "explain-labels", "rows": [{"label": "Result", "identity": "Result"}], "title": "\u672c\u6784\u5efa\u4e2d\u7684 EXPLAIN \u6807\u7b7e", "columns": [{"key": "label", "label": "\u6587\u672c\u683c\u5f0f\u6807\u7b7e"}, {"key": "identity", "label": "\u7ed3\u6784\u5316\u8282\u70b9\u6807\u8bc6"}]}], "related": [{"url": "/wiki/sql/explain/?v=14", "label": "EXPLAIN"}, {"url": "/docs/14/using-explain.html", "label": "\u4f7f\u7528 EXPLAIN"}, {"url": "/docs/14/parallel-plans.html", "label": "\u5e76\u884c\u8ba1\u5212"}], "release": {"ref": "PostgreSQL 14.24 source archive", "label": "14.24", "major": "14", "channel": "stable", "revision": "a7fa7ed3d558172355f51406097a7bd4f6b473be80f311ef7cda96bf383d8897", "source_url": "https://ftp.postgresql.org/pub/source/v14.24/postgresql-14.24.tar.bz2", "source_snapshot_utc": ""}, "sources": [{"url": "https://ftp.postgresql.org/pub/source/v14.24/postgresql-14.24.tar.bz2", "line": 1172, "path": "src/backend/commands/explain.c", "label": "src/backend/commands/explain.c:1172", "sha256": "e091be4e2a083b8dea39ccd09beedede22c1716ef974da66c214a44f48be8c41", "archive_sha256": "a7fa7ed3d558172355f51406097a7bd4f6b473be80f311ef7cda96bf383d8897"}, {"url": "https://ftp.postgresql.org/pub/source/v14.24/postgresql-14.24.tar.bz2", "line": 166, "path": "src/backend/executor/execProcnode.c", "label": "src/backend/executor/execProcnode.c:166", "sha256": "72da1c5ad457f1d92a39ab73531701794df858419e3b89d6e6cb7079634e68fa", "archive_sha256": "a7fa7ed3d558172355f51406097a7bd4f6b473be80f311ef7cda96bf383d8897"}, {"url": "https://ftp.postgresql.org/pub/source/v14.24/postgresql-14.24.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "3e3162c02eb2f4ddc96dbf0ce6ba52c63201b109b8f7face3056c982b4c04095", "archive_sha256": "a7fa7ed3d558172355f51406097a7bd4f6b473be80f311ef7cda96bf383d8897"}, {"url": "https://ftp.postgresql.org/pub/source/v14.24/postgresql-14.24.tar.bz2", "path": "src/include/nodes/plannodes.h", "label": "src/include/nodes/plannodes.h", "sha256": "302f51a16b570dba7ec4e7bc045f7df5800d21630280354d1a24025f3baec75d", "archive_sha256": "a7fa7ed3d558172355f51406097a7bd4f6b473be80f311ef7cda96bf383d8897"}, {"url": "https://pg.center/docs/14/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 14.24 \u00b7 using-explain", "sha256": "7f5ab59cb21a035ada45ea3426c5d1cca3f781273483677f73fdd76753555206", "language": "en", "original_url": "/docs/14/using-explain.html#USING-EXPLAIN-BASICS"}, {"url": "https://pg.center/docs/14/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 14.24 \u00b7 using-explain", "sha256": "7f5ab59cb21a035ada45ea3426c5d1cca3f781273483677f73fdd76753555206", "language": "en", "original_url": "/docs/14/using-explain.html#USING-EXPLAIN-ANALYZE"}, {"url": "https://pg.center/docs/14/parallel-plans.html#PARALLEL-PLANS", "path": "parallel-plans.html", "label": "PostgreSQL 14.24 \u00b7 parallel-plans", "sha256": "71fc3525781b74150364925e123cd8598fdebe0e05326706f2bc2e1ffa0b88a4", "language": "en", "original_url": "/docs/14/parallel-plans.html#PARALLEL-PLANS"}], "node_tag": "T_Result", "sections": [{"title": "EXPLAIN \u540d\u79f0\u4e0e\u5c5e\u6027", "paragraphs": ["\u7ed3\u6784\u5316\u683c\u5f0f\u4f7f\u7528\u4e0a\u8ff0 Node Type\u3002\u6587\u672c\u683c\u5f0f\u540d\u79f0\u8fd8\u53ef\u80fd\u5305\u542b\u64cd\u4f5c\u3001\u7b56\u7565\u3001\u8fde\u63a5\u7c7b\u578b\u3001\u626b\u63cf\u65b9\u5411\u6216\u805a\u5408\u9636\u6bb5\u5c5e\u6027\u3002", "\u6b64\u6e90\u7801\u8bb0\u5f55\u7684\u6587\u672c\u540d\u79f0\uff1aResult.", "\u5e76\u884c\u611f\u77e5\u4e0e\u5e76\u884c\u5b89\u5168\u662f\u4e0d\u540c\u7684\u8ba1\u5212\u5c5e\u6027\u3002\u5728\u5e76\u884c\u5de5\u4f5c\u8fdb\u7a0b\u5185\u8fd0\u884c\u7684\u8282\u70b9\u4e0d\u4e00\u5b9a\u662f\u5e76\u884c\u611f\u77e5\u8282\u70b9\u3002"]}, {"title": "\u5185\u5b58\u4e0e\u4e34\u65f6\u5b58\u50a8", "paragraphs": ["\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002"]}, {"title": "\u5e76\u884c\u6267\u884c\u4e0e\u8fd0\u884c\u4fe1\u606f\u91c7\u96c6", "paragraphs": ["\u4ee5\u4e0b\u6e90\u7801\u56de\u8c03\u53ef\u4ee5\u534f\u8c03\u6267\u884c\u6216\u6536\u96c6\u5de5\u4f5c\u8fdb\u7a0b\u7684\u6d4b\u91cf\u6570\u636e\u3002\u56de\u8c03\u5b58\u5728\u4e0d\u4ee3\u8868\u8be5\u8282\u70b9\u666e\u904d\u652f\u6301\u5171\u4eab\u5e76\u884c\u626b\u63cf\u6216\u5171\u4eab\u72b6\u6001\u3002", "\u6b64\u6784\u5efa\u7684\u56de\u8c03\uff1anone extracted from this node implementation."]}, {"title": "\u540c\u7248\u672c\u624b\u518c\u8bf4\u660e", "paragraphs": ["\u9700\u8981\u7406\u89e3\uff0c\u4e0a\u5c42\u8282\u70b9\u7684\u4ee3\u4ef7\u5305\u542b\u5176\u5168\u90e8\u5b50\u8282\u70b9\u7684\u4ee3\u4ef7\u3002\u540c\u65f6\uff0c\u4ee3\u4ef7\u4ec5\u53cd\u6620\u89c4\u5212\u5668\u5173\u6ce8\u7684\u56e0\u7d20\u3002\u5c24\u5176\u662f\uff0c\u4ee3\u4ef7\u4e0d\u5305\u542b\u5411\u5ba2\u6237\u7aef\u4f20\u8f93\u7ed3\u679c\u884c\u6240\u82b1\u8d39\u7684\u65f6\u95f4\uff0c\u5c3d\u7ba1\u5b83\u53ef\u80fd\u663e\u8457\u5f71\u54cd\u5b9e\u9645\u8017\u65f6\uff1b\u89c4\u5212\u5668\u5ffd\u7565\u5b83\uff0c\u662f\u56e0\u4e3a\u6539\u53d8\u8ba1\u5212\u65e0\u6cd5\u6539\u53d8\u8fd9\u90e8\u5206\u65f6\u95f4\u3002\uff08\u6211\u4eec\u76f8\u4fe1\u6bcf\u4e2a\u6b63\u786e\u8ba1\u5212\u90fd\u4f1a\u8f93\u51fa\u540c\u6837\u7684\u884c\u96c6\u3002\uff09", "rows \u5bb9\u6613\u4ee4\u4eba\u8bef\u89e3\uff1a\u5b83\u8868\u793a\u8282\u70b9\u8f93\u51fa\u7684\u884c\u6570\uff0c\u800c\u4e0d\u662f\u5904\u7406\u6216\u626b\u63cf\u7684\u884c\u6570\u3002\u8282\u70b9\u5e94\u7528 WHERE \u6761\u4ef6\u7b5b\u9009\u540e\uff0c\u8f93\u51fa\u884c\u6570\u901a\u5e38\u5c0f\u4e8e\u626b\u63cf\u884c\u6570\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u9876\u5c42 rows \u4f30\u8ba1\u5e94\u63a5\u8fd1\u67e5\u8be2\u5b9e\u9645\u8fd4\u56de\u3001\u66f4\u65b0\u6216\u5220\u9664\u7684\u884c\u6570\u3002", "\u4e0e\u666e\u901a\u6392\u5e8f\u76f8\u6bd4\uff0c\u589e\u91cf\u6392\u5e8f\u53ef\u5728\u6574\u4e2a\u7ed3\u679c\u96c6\u5c1a\u672a\u6392\u5b8c\u65f6\u5c31\u8fd4\u56de\u5143\u7ec4\uff0c\u5c24\u5176\u6709\u5229\u4e8e\u4f18\u5316\u5e26 LIMIT \u7684\u67e5\u8be2\u3002\u5b83\u8fd8\u53ef\u80fd\u51cf\u5c11\u5185\u5b58\u7528\u91cf\u548c\u6392\u5e8f\u6ea2\u5199\u78c1\u76d8\u7684\u6982\u7387\uff0c\u4f46\u4ee3\u4ef7\u662f\u5c06\u7ed3\u679c\u96c6\u62c6\u6210\u591a\u4e2a\u6392\u5e8f\u6279\u6b21\u6240\u5e26\u6765\u7684\u989d\u5916\u5f00\u9500\u3002", "\u6b64\u8ba1\u5212\u5305\u542b\u4e00\u4e2a\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\uff0c\u4ee5\u4e24\u4e2a\u8868\u626b\u63cf\u4f5c\u4e3a\u8f93\u5165\uff0c\u5373\u5b50\u8282\u70b9\u3002\u8282\u70b9\u6458\u8981\u884c\u7684\u7f29\u8fdb\u53cd\u6620\u8ba1\u5212\u6811\u7ed3\u6784\u3002\u8fde\u63a5\u7684\u7b2c\u4e00\u4e2a\u5b50\u8282\u70b9\uff08\u5916\u4fa7\u5b50\u8282\u70b9\uff09\u662f\u524d\u9762\u89c1\u8fc7\u7684\u4f4d\u56fe\u626b\u63cf\u3002\u5b83\u7684\u4ee3\u4ef7\u548c\u884c\u6570\u4e0e SELECT ... WHERE unique1 < 10 \u76f8\u540c\uff0c\u56e0\u4e3a\u8be5\u8282\u70b9\u5e94\u7528\u4e86 WHERE \u6761\u4ef6 unique1 < 10\u3002t1.unique2 = t2.unique2 \u6761\u4ef6\u6b64\u65f6\u5c1a\u4e0d\u76f8\u5173\uff0c\u56e0\u6b64\u4e0d\u4f1a\u5f71\u54cd\u5916\u4fa7\u626b\u63cf\u7684\u884c\u6570\u3002\u5bf9\u4e8e\u4ece\u5916\u4fa7\u5b50\u8282\u70b9\u83b7\u53d6\u7684\u6bcf\u4e00\u884c\uff0c\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\u90fd\u4f1a\u6267\u884c\u4e00\u6b21\u7b2c\u4e8c\u4e2a\u5b50\u8282\u70b9\uff08\u5185\u4fa7\u5b50\u8282\u70b9\uff09\u3002\u5f53\u524d\u5916\u4fa7\u884c\u7684\u5217\u503c\u53ef\u4ee5\u4ee3\u5165\u5185\u4fa7\u626b\u63cf\uff1b\u8fd9\u91cc\u53ef\u4f7f\u7528\u5916\u4fa7\u884c\u7684 t1.unique2 \u503c\uff0c\u56e0\u6b64\u5f97\u5230\u7684\u8ba1\u5212\u548c\u4ee3\u4ef7\u4e0e\u4e0a\u6587\u7b80\u5355\u7684 SELECT ... WHERE t2.unique2 = constant \u60c5\u51b5\u7c7b\u4f3c\u3002\uff08\u4f30\u8ba1\u4ee3\u4ef7\u5b9e\u9645\u7565\u4f4e\u4e8e\u4e0a\u4f8b\uff0c\u8fd9\u662f\u56e0\u4e3a\u9884\u8ba1\u53cd\u590d\u626b\u63cf t2 \u7d22\u5f15\u65f6\u4f1a\u4ea7\u751f\u7f13\u5b58\u6536\u76ca\u3002\uff09\u5faa\u73af\u8282\u70b9\u7684\u4ee3\u4ef7\u7531\u5916\u4fa7\u626b\u63cf\u4ee3\u4ef7\u3001\u6bcf\u4e2a\u5916\u4fa7\u884c\u6267\u884c\u4e00\u6b21\u5185\u4fa7\u626b\u63cf\u7684\u4ee3\u4ef7\uff08\u672c\u4f8b\u4e3a 10 * 7.91\uff09\uff0c\u4ee5\u53ca\u5c11\u91cf\u8fde\u63a5\u5904\u7406\u6240\u9700\u7684 CPU \u65f6\u95f4\u7ec4\u6210\u3002", "\u53ef\u4f7f\u7528 EXPLAIN \u7684 ANALYZE \u9009\u9879\u68c0\u67e5\u89c4\u5212\u5668\u4f30\u7b97\u662f\u5426\u51c6\u786e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\uff0cEXPLAIN \u4f1a\u5b9e\u9645\u6267\u884c\u67e5\u8be2\uff0c\u7136\u540e\u663e\u793a\u6bcf\u4e2a\u8ba1\u5212\u8282\u70b9\u7d2f\u8ba1\u7684\u771f\u5b9e\u884c\u6570\u548c\u771f\u5b9e\u8fd0\u884c\u65f6\u95f4\uff0c\u4ee5\u53ca\u666e\u901a EXPLAIN \u6240\u663e\u793a\u7684\u4f30\u7b97\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u80fd\u5f97\u5230\u5982\u4e0b\u7ed3\u679c\uff1a", "\u7531\u4e8e\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u5c06\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u6267\u884c\u5230\u5e95\uff0c\u56e0\u6b64\u4e0d\u80fd\u7b80\u5355\u5730\u62ff\u4e00\u4e2a\u666e\u901a\u67e5\u8be2\u8ba1\u5212\u5e76\u8ba9\u591a\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u540c\u65f6\u8fd0\u884c\u3002\u90a3\u6837\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u751f\u6210\u5b8c\u6574\u8f93\u51fa\u7ed3\u679c\u96c6\u7684\u4e00\u4efd\u526f\u672c\uff0c\u6240\u4ee5\u67e5\u8be2\u4e0d\u4ec5\u4e0d\u4f1a\u6bd4\u5e73\u5e38\u66f4\u5feb\uff0c\u53cd\u800c\u4f1a\u4ea7\u751f\u9519\u8bef\u7ed3\u679c\u3002\u76f8\u53cd\uff0c\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u5fc5\u987b\u662f\u67e5\u8be2\u4f18\u5316\u5668\u5185\u90e8\u6240\u8bf4\u7684 \u90e8\u5206\u8ba1\u5212 \uff1b\u4e5f\u5c31\u662f\u8bf4\uff0c\u5b83\u5fc5\u987b\u88ab\u6784\u9020\u4e3a\u4f7f\u6267\u884c\u8be5\u8ba1\u5212\u7684\u6bcf\u4e2a\u8fdb\u7a0b\u53ea\u751f\u6210\u8f93\u51fa\u884c\u7684\u4e00\u4e2a\u5b50\u96c6\uff0c\u5e76\u4e14\u4fdd\u8bc1\u6bcf\u4e00\u6761\u6240\u9700\u8f93\u51fa\u884c\u90fd\u6070\u597d\u7531\u67d0\u4e2a\u534f\u4f5c\u8fdb\u7a0b\u751f\u6210\u4e00\u6b21\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u8fd9\u610f\u5473\u7740\u67e5\u8be2\u9a71\u52a8\u8868\u4e0a\u7684\u626b\u63cf\u5fc5\u987b\u662f\u5e76\u884c\u611f\u77e5\u626b\u63cf\u3002"]}, {"title": "\u672c\u7248\u624b\u518c\u4e2d\u7684\u793a\u4f8b", "blocks": [{"code": "EXPLAIN UPDATE parent SET f2 = f2 + 1 WHERE f1 = 101;\n                                              QUERY PLAN\n------------------------------------------------------------------------------------------------------\n Update on parent  (cost=0.00..24.59 rows=0 width=0)\n   Update on parent parent_1\n   Update on child1 parent_2\n   Update on child2 parent_3\n   Update on child3 parent_4\n   ->  Result  (cost=0.00..24.59 rows=4 width=14)\n         ->  Append  (cost=0.00..24.54 rows=4 width=14)\n               ->  Seq Scan on parent parent_1  (cost=0.00..0.00 rows=1 width=14)\n                     Filter: (f1 = 101)\n               ->  Index Scan using child1_pkey on child1 parent_2  (cost=0.15..8.17 rows=1 width=14)\n                     Index Cond: (f1 = 101)\n               ->  Index Scan using child2_pkey on child2 parent_3  (cost=0.15..8.17 rows=1 width=14)\n                     Index Cond: (f1 = 101)\n               ->  Index Scan using child3_pkey on child3 parent_4  (cost=0.15..8.17 rows=1 width=14)\n                     Index Cond: (f1 = 101)", "source": {"url": "/docs/14/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 14.24 \u00b7 using-explain", "sha256": "7f5ab59cb21a035ada45ea3426c5d1cca3f781273483677f73fdd76753555206"}, "paragraphs": ["\u793a\u4f8b\u6458\u81ea PostgreSQL 14.24 \u624b\u518c\uff1b\u672c\u767e\u79d1\u672a\u5b9e\u9645\u6267\u884c\u6b64\u793a\u4f8b\u3002", "UPDATE \u6216 DELETE \u547d\u4ee4\u5f71\u54cd\u7ee7\u627f\u5c42\u7ea7\u65f6\uff0c\u8f93\u51fa\u53ef\u80fd\u5982\u4e0b\uff1a"]}]}, {"title": "\u6267\u884c\u5668\u5b9e\u73b0\u8bf4\u660e", "paragraphs": ["nodeResult.c\uff1a\u652f\u6301\u9700\u8981\u7279\u6b8a\u4ee3\u7801\u7684\u5e38\u91cf\u8282\u70b9\u3002", "Result \u8282\u70b9\u7528\u4e8e\u4e0d\u626b\u63cf\u4efb\u4f55\u5173\u7cfb\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\uff08\u8bf7\u8bb0\u4f4f\uff0cINSERT \u6216 UPDATE \u9700\u8981\u4e00\u68f5\u751f\u6210\u65b0\u884c\u7684\u8ba1\u5212\u6811\u3002\uff09", "Result \u8282\u70b9\u4e5f\u7528\u4e8e\u4f18\u5316\u5e26\u6709\u5e38\u91cf\u6761\u4ef6\uff08\u5373\u4e0d\u4f9d\u8d56\u626b\u63cf\u6570\u636e\u7684\u6761\u4ef6\uff09\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\u8fd0\u884c\u65f6\uff0cResult \u8282\u70b9\u53ea\u8ba1\u7b97\u4e00\u6b21\u5e38\u91cf\u6761\u4ef6\uff0cEXPLAIN \u5c06\u5176\u663e\u793a\u4e3a One-Time Filter\u3002\u5982\u679c\u6761\u4ef6\u4e3a\u5047\uff0c\u65e0\u9700\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u4fbf\u53ef\u8fd4\u56de\u7a7a\u7ed3\u679c\u96c6\uff1b\u5982\u679c\u4e3a\u771f\uff0c\u5219\u6b63\u5e38\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u5e76\u4f20\u56de\u7ed3\u679c\u3002"]}, {"code": "case T_Result:\n\t\t\tpname = sname = \"Result\";\n\t\t\tbreak;", "title": "\u6838\u5fc3\u6e90\u7801\u4e2d\u7684 EXPLAIN \u6807\u8bc6"}], "strategies": [], "description": ["\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002"], "localization": {"status": "complete", "sources": [{"url": "/docs/14/parallel-plans.html", "method": "same-major semantic node", "sha256": "27ba0fab61ef7b5aa518b18597a7cd30f9560e5cf2b383016d31e59518892f88", "language": "zh", "matched_nodes": ["#PARALLEL-PLANS/p[2]"]}], "language": "zh", "original_text": {"/versions/14/description/0": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/versions/14/facts/0/label": "Core node tag", "/versions/14/facts/1/label": "Structured EXPLAIN Node Type", "/versions/14/facts/2/label": "Inputs", "/versions/14/facts/2/value": "Optional child plan", "/versions/14/facts/3/label": "Output", "/versions/14/facts/3/value": "Projected tuples", "/versions/14/facts/4/label": "Executor initializer", "/versions/14/facts/5/label": "Memory mechanism", "/versions/14/tables/0/title": "EXPLAIN labels in this source build", "/versions/14/related/1/label": "Using EXPLAIN", "/versions/14/related/2/label": "Parallel plans", "/versions/14/sections/0/title": "EXPLAIN names and attributes", "/versions/14/sections/1/title": "Memory and temporary storage", "/versions/14/sections/2/title": "Parallel execution and instrumentation", "/versions/14/sections/3/title": "Same-version manual discussion", "/versions/14/sections/4/title": "Examples from this manual build", "/versions/14/sections/5/title": "Executor implementation notes", "/versions/14/sections/6/title": "EXPLAIN identity in core source", "/versions/14/memory/description": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/14/sections/0/paragraphs/0": "Structured formats use the Node Type above. Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.", "/versions/14/sections/0/paragraphs/1": "Text names recorded by this source: Result.", "/versions/14/sections/0/paragraphs/2": "Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node.", "/versions/14/sections/1/paragraphs/0": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/14/sections/2/paragraphs/0": "The source callbacks below can coordinate execution or collect worker instrumentation. Their presence is not a blanket claim that this node supports a shared parallel scan or shared state.", "/versions/14/sections/2/paragraphs/1": "Callbacks in this build: none extracted from this node implementation.", "/versions/14/sections/3/paragraphs/0": "It's important to understand that the cost of an upper-level node includes the cost of all its child nodes. It's also important to realize that the cost only reflects things that the planner cares about. In particular, the cost does not consider the time spent transmitting result rows to the client, which could be an important factor in the real elapsed time; but the planner ignores it because it cannot change it by altering the plan. (Every correct plan will output the same row set, we trust.)", "/versions/14/sections/3/paragraphs/1": "The rows value is a little tricky because it is not the number of rows processed or scanned by the plan node, but rather the number emitted by the node. This is often less than the number scanned, as a result of filtering by any WHERE -clause conditions that are being applied at the node. Ideally the top-level rows estimate will approximate the number of rows actually returned, updated, or deleted by the query.", "/versions/14/sections/3/paragraphs/2": "Compared to regular sorts, sorting incrementally allows returning tuples before the entire result set has been sorted, which particularly enables optimizations with LIMIT queries. It may also reduce memory usage and the likelihood of spilling sorts to disk, but it comes at the cost of the increased overhead of splitting the result set into multiple sorting batches.", "/versions/14/sections/3/paragraphs/3": "In this plan, we have a nested-loop join node with two table scans as inputs, or children. The indentation of the node summary lines reflects the plan tree structure. The join's first, or \u201c outer \u201d , child is a bitmap scan similar to those we saw before. Its cost and row count are the same as we'd get from SELECT ... WHERE unique1 < 10 because we are applying the WHERE clause unique1 < 10 at that node. The t1.unique2 = t2.unique2 clause is not relevant yet, so it doesn't affect the row count of the outer scan. The nested-loop join node will run its second, or \u201c inner \u201d child once for each row obtained from the outer child. Column values from the current outer row can be plugged into the inner scan; here, the t1.unique2 value from the outer row is available, so we get a plan and costs similar to what we saw above for a simple SELECT ... WHERE t2.unique2 = constant case. (The estimated cost is actually a bit lower than what was seen above, as a result of caching that's expected to occur during the repeated index scans on t2 .) The costs of the loop node are then set on the basis of the cost of the outer scan, plus one repetition of the inner scan for each outer row (10 * 7.91, here), plus a little CPU time for join processing.", "/versions/14/sections/3/paragraphs/4": "It is possible to check the accuracy of the planner's estimates by using EXPLAIN 's ANALYZE option. With this option, EXPLAIN actually executes the query, and then displays the true row counts and true run time accumulated within each plan node, along with the same estimates that a plain EXPLAIN shows. For example, we might get a result like this:", "/versions/14/sections/3/paragraphs/5": "Because each worker executes the parallel portion of the plan to completion, it is not possible to simply take an ordinary query plan and run it using multiple workers. Each worker would produce a full copy of the output result set, so the query would not run any faster than normal but would produce incorrect results. Instead, the parallel portion of the plan must be what is known internally to the query optimizer as a partial plan ; that is, it must be constructed so that each process that executes the plan will generate only a subset of the output rows in such a way that each required output row is guaranteed to be generated by exactly one of the cooperating processes. Generally, this means that the scan on the driving table of the query must be a parallel-aware scan.", "/versions/14/sections/5/paragraphs/0": "nodeResult.c support for constant nodes needing special code.", "/versions/14/sections/5/paragraphs/1": "Result nodes are used in queries where no relations are scanned. Examples of such queries are:", "/versions/14/sections/5/paragraphs/2": "(Remember that in an INSERT or UPDATE, we need a plan tree that generates the new rows.)", "/versions/14/sections/5/paragraphs/3": "Result nodes are also used to optimise queries with constant qualifications (ie, quals that do not depend on the scanned data), such as:", "/versions/14/sections/5/paragraphs/4": "At runtime, the Result node evaluates the constant qual once, which is shown by EXPLAIN as a One-Time Filter. If it's false, we can return an empty result set without running the controlled plan at all. If it's true, we run the controlled plan normally and pass back the results.", "/versions/14/tables/0/columns/0/label": "Text-format label", "/versions/14/tables/0/columns/1/label": "Structured node identity", "/versions/14/sections/4/blocks/0/paragraphs/0": "Example copied from the PostgreSQL 14.24 manual; it was not executed for this collection.", "/versions/14/sections/4/blocks/0/paragraphs/1": "When an UPDATE or DELETE command affects an inheritance hierarchy, the output might look like this:"}, "fallback_fields": [], "source_language": "en", "original_snapshot_sha256": "5083d510b8a0b15a39aa73a0548574a4819b6f6a150d9d36ead50d11fd1db16e"}, "evidence_kind": "source and documentation", "explain_names": ["Result"], "partial_modes": [], "comparison_data": {"node_tag": "T_Result", "strategies": [], "text_names": ["Result"], "initializer": "ExecInitResult", "partial_modes": [], "memory_mechanism": "unclassified", "parallel_callbacks": []}, "comparison_hash": "7d9e21f5e91321228505ba502e7faa5b9ebdda5ba4d71b8a9b97571a1f87b5f5", "explain_prefixes": ["Parallel", "Async"], "runtime_verified": false, "source_inventory": {"explain": "src/backend/commands/explain.c", "executor": "src/backend/executor/execProcnode.c", "implementation": "src/backend/executor/nodeResult.c"}, "parallel_callbacks": []}, "15": {"facts": [{"label": "\u6838\u5fc3\u8282\u70b9\u6807\u7b7e", "value": "T_Result"}, {"label": "\u7ed3\u6784\u5316 EXPLAIN \u8282\u70b9\u7c7b\u578b", "value": "Result"}, {"label": "\u8f93\u5165", "value": "\u53ef\u9009\u7684\u5b50\u8ba1\u5212"}, {"label": "\u8f93\u51fa", "value": "\u6295\u5f71\u540e\u7684\u5143\u7ec4"}, {"label": "\u6267\u884c\u5668\u521d\u59cb\u5316\u51fd\u6570", "value": "ExecInitResult"}, {"label": "\u5185\u5b58\u673a\u5236", "value": "unclassified"}], "memory": {"evidence": [{"url": "https://ftp.postgresql.org/pub/source/v15.19/postgresql-15.19.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "f3928410da9356b863680d717219c4c6be1289177ce42911e10c40e7d1c65ca9", "archive_sha256": "e1a64a87a46b825b88c082e4518161a47aab53c45694964f8ba1df28f7859f89"}], "mechanism": "unclassified", "description": "\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002", "source_notes": []}, "tables": [{"key": "explain-labels", "rows": [{"label": "Result", "identity": "Result"}], "title": "\u672c\u6784\u5efa\u4e2d\u7684 EXPLAIN \u6807\u7b7e", "columns": [{"key": "label", "label": "\u6587\u672c\u683c\u5f0f\u6807\u7b7e"}, {"key": "identity", "label": "\u7ed3\u6784\u5316\u8282\u70b9\u6807\u8bc6"}]}], "related": [{"url": "/wiki/sql/explain/?v=15", "label": "EXPLAIN"}, {"url": "/docs/15/using-explain.html", "label": "\u4f7f\u7528 EXPLAIN"}, {"url": "/docs/15/parallel-plans.html", "label": "\u5e76\u884c\u8ba1\u5212"}], "release": {"ref": "PostgreSQL 15.19 source archive", "label": "15.19", "major": "15", "channel": "stable", "revision": "e1a64a87a46b825b88c082e4518161a47aab53c45694964f8ba1df28f7859f89", "source_url": "https://ftp.postgresql.org/pub/source/v15.19/postgresql-15.19.tar.bz2", "source_snapshot_utc": ""}, "sources": [{"url": "https://ftp.postgresql.org/pub/source/v15.19/postgresql-15.19.tar.bz2", "line": 1172, "path": "src/backend/commands/explain.c", "label": "src/backend/commands/explain.c:1172", "sha256": "bb3b442d0f1b098aa8707335250102f027a596cd94117308bd16d1d36b258f5c", "archive_sha256": "e1a64a87a46b825b88c082e4518161a47aab53c45694964f8ba1df28f7859f89"}, {"url": "https://ftp.postgresql.org/pub/source/v15.19/postgresql-15.19.tar.bz2", "line": 166, "path": "src/backend/executor/execProcnode.c", "label": "src/backend/executor/execProcnode.c:166", "sha256": "19836c50a272741a4eac653541e655437c2e00710a541e5348d6a277d0669d7c", "archive_sha256": "e1a64a87a46b825b88c082e4518161a47aab53c45694964f8ba1df28f7859f89"}, {"url": "https://ftp.postgresql.org/pub/source/v15.19/postgresql-15.19.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "f3928410da9356b863680d717219c4c6be1289177ce42911e10c40e7d1c65ca9", "archive_sha256": "e1a64a87a46b825b88c082e4518161a47aab53c45694964f8ba1df28f7859f89"}, {"url": "https://ftp.postgresql.org/pub/source/v15.19/postgresql-15.19.tar.bz2", "path": "src/include/nodes/plannodes.h", "label": "src/include/nodes/plannodes.h", "sha256": "fb4a4c8165495299131173680bc02a950d88e1ff610231fd97997bc0c9afc1d7", "archive_sha256": "e1a64a87a46b825b88c082e4518161a47aab53c45694964f8ba1df28f7859f89"}, {"url": "https://pg.center/docs/15/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 15.19 \u00b7 using-explain", "sha256": "d1f509457c647da453d2575c772d91022a0f115dd84f9a3b20f5ff25a243648f", "language": "en", "original_url": "/docs/15/using-explain.html#USING-EXPLAIN-BASICS"}, {"url": "https://pg.center/docs/15/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 15.19 \u00b7 using-explain", "sha256": "d1f509457c647da453d2575c772d91022a0f115dd84f9a3b20f5ff25a243648f", "language": "en", "original_url": "/docs/15/using-explain.html#USING-EXPLAIN-ANALYZE"}, {"url": "https://pg.center/docs/15/parallel-plans.html#PARALLEL-PLANS", "path": "parallel-plans.html", "label": "PostgreSQL 15.19 \u00b7 parallel-plans", "sha256": "ec9345488a15cdc05d3e0b0849763e2bf0b864ad17de786c5f023db5dab1ea96", "language": "en", "original_url": "/docs/15/parallel-plans.html#PARALLEL-PLANS"}], "node_tag": "T_Result", "sections": [{"title": "EXPLAIN \u540d\u79f0\u4e0e\u5c5e\u6027", "paragraphs": ["\u7ed3\u6784\u5316\u683c\u5f0f\u4f7f\u7528\u4e0a\u8ff0 Node Type\u3002\u6587\u672c\u683c\u5f0f\u540d\u79f0\u8fd8\u53ef\u80fd\u5305\u542b\u64cd\u4f5c\u3001\u7b56\u7565\u3001\u8fde\u63a5\u7c7b\u578b\u3001\u626b\u63cf\u65b9\u5411\u6216\u805a\u5408\u9636\u6bb5\u5c5e\u6027\u3002", "\u6b64\u6e90\u7801\u8bb0\u5f55\u7684\u6587\u672c\u540d\u79f0\uff1aResult.", "\u5e76\u884c\u611f\u77e5\u4e0e\u5e76\u884c\u5b89\u5168\u662f\u4e0d\u540c\u7684\u8ba1\u5212\u5c5e\u6027\u3002\u5728\u5e76\u884c\u5de5\u4f5c\u8fdb\u7a0b\u5185\u8fd0\u884c\u7684\u8282\u70b9\u4e0d\u4e00\u5b9a\u662f\u5e76\u884c\u611f\u77e5\u8282\u70b9\u3002"]}, {"title": "\u5185\u5b58\u4e0e\u4e34\u65f6\u5b58\u50a8", "paragraphs": ["\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002"]}, {"title": "\u5e76\u884c\u6267\u884c\u4e0e\u8fd0\u884c\u4fe1\u606f\u91c7\u96c6", "paragraphs": ["\u4ee5\u4e0b\u6e90\u7801\u56de\u8c03\u53ef\u4ee5\u534f\u8c03\u6267\u884c\u6216\u6536\u96c6\u5de5\u4f5c\u8fdb\u7a0b\u7684\u6d4b\u91cf\u6570\u636e\u3002\u56de\u8c03\u5b58\u5728\u4e0d\u4ee3\u8868\u8be5\u8282\u70b9\u666e\u904d\u652f\u6301\u5171\u4eab\u5e76\u884c\u626b\u63cf\u6216\u5171\u4eab\u72b6\u6001\u3002", "\u6b64\u6784\u5efa\u7684\u56de\u8c03\uff1anone extracted from this node implementation."]}, {"title": "\u540c\u7248\u672c\u624b\u518c\u8bf4\u660e", "paragraphs": ["\u9700\u8981\u7406\u89e3\uff0c\u4e0a\u5c42\u8282\u70b9\u7684\u4ee3\u4ef7\u5305\u542b\u5176\u5168\u90e8\u5b50\u8282\u70b9\u7684\u4ee3\u4ef7\u3002\u540c\u65f6\uff0c\u4ee3\u4ef7\u4ec5\u53cd\u6620\u89c4\u5212\u5668\u5173\u6ce8\u7684\u56e0\u7d20\u3002\u5c24\u5176\u662f\uff0c\u4ee3\u4ef7\u4e0d\u5305\u542b\u5411\u5ba2\u6237\u7aef\u4f20\u8f93\u7ed3\u679c\u884c\u6240\u82b1\u8d39\u7684\u65f6\u95f4\uff0c\u5c3d\u7ba1\u5b83\u53ef\u80fd\u663e\u8457\u5f71\u54cd\u5b9e\u9645\u8017\u65f6\uff1b\u89c4\u5212\u5668\u5ffd\u7565\u5b83\uff0c\u662f\u56e0\u4e3a\u6539\u53d8\u8ba1\u5212\u65e0\u6cd5\u6539\u53d8\u8fd9\u90e8\u5206\u65f6\u95f4\u3002\uff08\u6211\u4eec\u76f8\u4fe1\u6bcf\u4e2a\u6b63\u786e\u8ba1\u5212\u90fd\u4f1a\u8f93\u51fa\u540c\u6837\u7684\u884c\u96c6\u3002\uff09", "rows \u5bb9\u6613\u4ee4\u4eba\u8bef\u89e3\uff1a\u5b83\u8868\u793a\u8282\u70b9\u8f93\u51fa\u7684\u884c\u6570\uff0c\u800c\u4e0d\u662f\u5904\u7406\u6216\u626b\u63cf\u7684\u884c\u6570\u3002\u8282\u70b9\u5e94\u7528 WHERE \u6761\u4ef6\u7b5b\u9009\u540e\uff0c\u8f93\u51fa\u884c\u6570\u901a\u5e38\u5c0f\u4e8e\u626b\u63cf\u884c\u6570\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u9876\u5c42 rows \u4f30\u8ba1\u5e94\u63a5\u8fd1\u67e5\u8be2\u5b9e\u9645\u8fd4\u56de\u3001\u66f4\u65b0\u6216\u5220\u9664\u7684\u884c\u6570\u3002", "\u4e0e\u666e\u901a\u6392\u5e8f\u76f8\u6bd4\uff0c\u589e\u91cf\u6392\u5e8f\u53ef\u5728\u6574\u4e2a\u7ed3\u679c\u96c6\u5c1a\u672a\u6392\u5b8c\u65f6\u5c31\u8fd4\u56de\u5143\u7ec4\uff0c\u5c24\u5176\u6709\u5229\u4e8e\u4f18\u5316\u5e26 LIMIT \u7684\u67e5\u8be2\u3002\u5b83\u8fd8\u53ef\u80fd\u51cf\u5c11\u5185\u5b58\u7528\u91cf\u548c\u6392\u5e8f\u6ea2\u5199\u78c1\u76d8\u7684\u6982\u7387\uff0c\u4f46\u4ee3\u4ef7\u662f\u5c06\u7ed3\u679c\u96c6\u62c6\u6210\u591a\u4e2a\u6392\u5e8f\u6279\u6b21\u6240\u5e26\u6765\u7684\u989d\u5916\u5f00\u9500\u3002", "\u6b64\u8ba1\u5212\u5305\u542b\u4e00\u4e2a\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\uff0c\u4ee5\u4e24\u4e2a\u8868\u626b\u63cf\u4f5c\u4e3a\u8f93\u5165\uff0c\u5373\u5b50\u8282\u70b9\u3002\u8282\u70b9\u6458\u8981\u884c\u7684\u7f29\u8fdb\u53cd\u6620\u8ba1\u5212\u6811\u7ed3\u6784\u3002\u8fde\u63a5\u7684\u7b2c\u4e00\u4e2a\u5b50\u8282\u70b9\uff08\u5916\u4fa7\u5b50\u8282\u70b9\uff09\u662f\u524d\u9762\u89c1\u8fc7\u7684\u4f4d\u56fe\u626b\u63cf\u3002\u5b83\u7684\u4ee3\u4ef7\u548c\u884c\u6570\u4e0e SELECT ... WHERE unique1 < 10 \u76f8\u540c\uff0c\u56e0\u4e3a\u8be5\u8282\u70b9\u5e94\u7528\u4e86 WHERE \u6761\u4ef6 unique1 < 10\u3002t1.unique2 = t2.unique2 \u6761\u4ef6\u6b64\u65f6\u5c1a\u4e0d\u76f8\u5173\uff0c\u56e0\u6b64\u4e0d\u4f1a\u5f71\u54cd\u5916\u4fa7\u626b\u63cf\u7684\u884c\u6570\u3002\u5bf9\u4e8e\u4ece\u5916\u4fa7\u5b50\u8282\u70b9\u83b7\u53d6\u7684\u6bcf\u4e00\u884c\uff0c\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\u90fd\u4f1a\u6267\u884c\u4e00\u6b21\u7b2c\u4e8c\u4e2a\u5b50\u8282\u70b9\uff08\u5185\u4fa7\u5b50\u8282\u70b9\uff09\u3002\u5f53\u524d\u5916\u4fa7\u884c\u7684\u5217\u503c\u53ef\u4ee5\u4ee3\u5165\u5185\u4fa7\u626b\u63cf\uff1b\u8fd9\u91cc\u53ef\u4f7f\u7528\u5916\u4fa7\u884c\u7684 t1.unique2 \u503c\uff0c\u56e0\u6b64\u5f97\u5230\u7684\u8ba1\u5212\u548c\u4ee3\u4ef7\u4e0e\u4e0a\u6587\u7b80\u5355\u7684 SELECT ... WHERE t2.unique2 = constant \u60c5\u51b5\u7c7b\u4f3c\u3002\uff08\u4f30\u8ba1\u4ee3\u4ef7\u5b9e\u9645\u7565\u4f4e\u4e8e\u4e0a\u4f8b\uff0c\u8fd9\u662f\u56e0\u4e3a\u9884\u8ba1\u53cd\u590d\u626b\u63cf t2 \u7d22\u5f15\u65f6\u4f1a\u4ea7\u751f\u7f13\u5b58\u6536\u76ca\u3002\uff09\u5faa\u73af\u8282\u70b9\u7684\u4ee3\u4ef7\u7531\u5916\u4fa7\u626b\u63cf\u4ee3\u4ef7\u3001\u6bcf\u4e2a\u5916\u4fa7\u884c\u6267\u884c\u4e00\u6b21\u5185\u4fa7\u626b\u63cf\u7684\u4ee3\u4ef7\uff08\u672c\u4f8b\u4e3a 10 * 7.91\uff09\uff0c\u4ee5\u53ca\u5c11\u91cf\u8fde\u63a5\u5904\u7406\u6240\u9700\u7684 CPU \u65f6\u95f4\u7ec4\u6210\u3002", "\u53ef\u4f7f\u7528 EXPLAIN \u7684 ANALYZE \u9009\u9879\u68c0\u67e5\u89c4\u5212\u5668\u4f30\u7b97\u662f\u5426\u51c6\u786e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\uff0cEXPLAIN \u4f1a\u5b9e\u9645\u6267\u884c\u67e5\u8be2\uff0c\u7136\u540e\u663e\u793a\u6bcf\u4e2a\u8ba1\u5212\u8282\u70b9\u7d2f\u8ba1\u7684\u771f\u5b9e\u884c\u6570\u548c\u771f\u5b9e\u8fd0\u884c\u65f6\u95f4\uff0c\u4ee5\u53ca\u666e\u901a EXPLAIN \u6240\u663e\u793a\u7684\u4f30\u7b97\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u80fd\u5f97\u5230\u5982\u4e0b\u7ed3\u679c\uff1a", "\u7531\u4e8e\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u5c06\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u6267\u884c\u5230\u5e95\uff0c\u56e0\u6b64\u4e0d\u80fd\u7b80\u5355\u5730\u62ff\u4e00\u4e2a\u666e\u901a\u67e5\u8be2\u8ba1\u5212\u5e76\u8ba9\u591a\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u540c\u65f6\u8fd0\u884c\u3002\u90a3\u6837\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u751f\u6210\u5b8c\u6574\u8f93\u51fa\u7ed3\u679c\u96c6\u7684\u4e00\u4efd\u526f\u672c\uff0c\u6240\u4ee5\u67e5\u8be2\u4e0d\u4ec5\u4e0d\u4f1a\u6bd4\u5e73\u5e38\u66f4\u5feb\uff0c\u53cd\u800c\u4f1a\u4ea7\u751f\u9519\u8bef\u7ed3\u679c\u3002\u76f8\u53cd\uff0c\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u5fc5\u987b\u662f\u67e5\u8be2\u4f18\u5316\u5668\u5185\u90e8\u6240\u8bf4\u7684 \u90e8\u5206\u8ba1\u5212 \uff1b\u4e5f\u5c31\u662f\u8bf4\uff0c\u5b83\u5fc5\u987b\u88ab\u6784\u9020\u4e3a\u4f7f\u6267\u884c\u8be5\u8ba1\u5212\u7684\u6bcf\u4e2a\u8fdb\u7a0b\u53ea\u751f\u6210\u8f93\u51fa\u884c\u7684\u4e00\u4e2a\u5b50\u96c6\uff0c\u5e76\u4e14\u4fdd\u8bc1\u6bcf\u4e00\u6761\u6240\u9700\u8f93\u51fa\u884c\u90fd\u6070\u597d\u7531\u67d0\u4e2a\u534f\u4f5c\u8fdb\u7a0b\u751f\u6210\u4e00\u6b21\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u8fd9\u610f\u5473\u7740\u67e5\u8be2\u9a71\u52a8\u8868\u4e0a\u7684\u626b\u63cf\u5fc5\u987b\u662f\u5e76\u884c\u611f\u77e5\u626b\u63cf\u3002"]}, {"title": "\u672c\u7248\u624b\u518c\u4e2d\u7684\u793a\u4f8b", "blocks": [{"code": "EXPLAIN UPDATE parent SET f2 = f2 + 1 WHERE f1 = 101;\n                                              QUERY PLAN\n------------------------------------------------------------------------------------------------------\n Update on parent  (cost=0.00..24.59 rows=0 width=0)\n   Update on parent parent_1\n   Update on child1 parent_2\n   Update on child2 parent_3\n   Update on child3 parent_4\n   ->  Result  (cost=0.00..24.59 rows=4 width=14)\n         ->  Append  (cost=0.00..24.54 rows=4 width=14)\n               ->  Seq Scan on parent parent_1  (cost=0.00..0.00 rows=1 width=14)\n                     Filter: (f1 = 101)\n               ->  Index Scan using child1_pkey on child1 parent_2  (cost=0.15..8.17 rows=1 width=14)\n                     Index Cond: (f1 = 101)\n               ->  Index Scan using child2_pkey on child2 parent_3  (cost=0.15..8.17 rows=1 width=14)\n                     Index Cond: (f1 = 101)\n               ->  Index Scan using child3_pkey on child3 parent_4  (cost=0.15..8.17 rows=1 width=14)\n                     Index Cond: (f1 = 101)", "source": {"url": "/docs/15/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 15.19 \u00b7 using-explain", "sha256": "d1f509457c647da453d2575c772d91022a0f115dd84f9a3b20f5ff25a243648f"}, "paragraphs": ["\u793a\u4f8b\u6458\u81ea PostgreSQL 15.19 \u624b\u518c\uff1b\u672c\u767e\u79d1\u672a\u5b9e\u9645\u6267\u884c\u6b64\u793a\u4f8b\u3002", "UPDATE\u3001DELETE \u6216 MERGE \u4f5c\u7528\u4e8e\u7ee7\u627f\u5c42\u7ea7\u65f6\uff0c\u8f93\u51fa\u53ef\u80fd\u5982\u4e0b\uff1a"]}]}, {"title": "\u6267\u884c\u5668\u5b9e\u73b0\u8bf4\u660e", "paragraphs": ["nodeResult.c\uff1a\u652f\u6301\u9700\u8981\u7279\u6b8a\u4ee3\u7801\u7684\u5e38\u91cf\u8282\u70b9\u3002", "Result \u8282\u70b9\u7528\u4e8e\u4e0d\u626b\u63cf\u4efb\u4f55\u5173\u7cfb\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\uff08\u8bf7\u8bb0\u4f4f\uff0cINSERT \u6216 UPDATE \u9700\u8981\u4e00\u68f5\u751f\u6210\u65b0\u884c\u7684\u8ba1\u5212\u6811\u3002\uff09", "Result \u8282\u70b9\u4e5f\u7528\u4e8e\u4f18\u5316\u5e26\u6709\u5e38\u91cf\u6761\u4ef6\uff08\u5373\u4e0d\u4f9d\u8d56\u626b\u63cf\u6570\u636e\u7684\u6761\u4ef6\uff09\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\u8fd0\u884c\u65f6\uff0cResult \u8282\u70b9\u53ea\u8ba1\u7b97\u4e00\u6b21\u5e38\u91cf\u6761\u4ef6\uff0cEXPLAIN \u5c06\u5176\u663e\u793a\u4e3a One-Time Filter\u3002\u5982\u679c\u6761\u4ef6\u4e3a\u5047\uff0c\u65e0\u9700\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u4fbf\u53ef\u8fd4\u56de\u7a7a\u7ed3\u679c\u96c6\uff1b\u5982\u679c\u4e3a\u771f\uff0c\u5219\u6b63\u5e38\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u5e76\u4f20\u56de\u7ed3\u679c\u3002"]}, {"code": "case T_Result:\n\t\t\tpname = sname = \"Result\";\n\t\t\tbreak;", "title": "\u6838\u5fc3\u6e90\u7801\u4e2d\u7684 EXPLAIN \u6807\u8bc6"}], "strategies": [], "description": ["\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002"], "localization": {"status": "complete", "sources": [{"url": "/docs/15/parallel-plans.html", "method": "same-major semantic node", "sha256": "f854eb236b7b7015acb3d4356b2199700ef6396672fbb271f4325b656c16e6c3", "language": "zh", "matched_nodes": ["#PARALLEL-PLANS/p[2]"]}], "language": "zh", "original_text": {"/versions/15/description/0": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/versions/15/facts/0/label": "Core node tag", "/versions/15/facts/1/label": "Structured EXPLAIN Node Type", "/versions/15/facts/2/label": "Inputs", "/versions/15/facts/2/value": "Optional child plan", "/versions/15/facts/3/label": "Output", "/versions/15/facts/3/value": "Projected tuples", "/versions/15/facts/4/label": "Executor initializer", "/versions/15/facts/5/label": "Memory mechanism", "/versions/15/tables/0/title": "EXPLAIN labels in this source build", "/versions/15/related/1/label": "Using EXPLAIN", "/versions/15/related/2/label": "Parallel plans", "/versions/15/sections/0/title": "EXPLAIN names and attributes", "/versions/15/sections/1/title": "Memory and temporary storage", "/versions/15/sections/2/title": "Parallel execution and instrumentation", "/versions/15/sections/3/title": "Same-version manual discussion", "/versions/15/sections/4/title": "Examples from this manual build", "/versions/15/sections/5/title": "Executor implementation notes", "/versions/15/sections/6/title": "EXPLAIN identity in core source", "/versions/15/memory/description": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/15/sections/0/paragraphs/0": "Structured formats use the Node Type above. Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.", "/versions/15/sections/0/paragraphs/1": "Text names recorded by this source: Result.", "/versions/15/sections/0/paragraphs/2": "Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node.", "/versions/15/sections/1/paragraphs/0": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/15/sections/2/paragraphs/0": "The source callbacks below can coordinate execution or collect worker instrumentation. Their presence is not a blanket claim that this node supports a shared parallel scan or shared state.", "/versions/15/sections/2/paragraphs/1": "Callbacks in this build: none extracted from this node implementation.", "/versions/15/sections/3/paragraphs/0": "It's important to understand that the cost of an upper-level node includes the cost of all its child nodes. It's also important to realize that the cost only reflects things that the planner cares about. In particular, the cost does not consider the time spent transmitting result rows to the client, which could be an important factor in the real elapsed time; but the planner ignores it because it cannot change it by altering the plan. (Every correct plan will output the same row set, we trust.)", "/versions/15/sections/3/paragraphs/1": "The rows value is a little tricky because it is not the number of rows processed or scanned by the plan node, but rather the number emitted by the node. This is often less than the number scanned, as a result of filtering by any WHERE -clause conditions that are being applied at the node. Ideally the top-level rows estimate will approximate the number of rows actually returned, updated, or deleted by the query.", "/versions/15/sections/3/paragraphs/2": "Compared to regular sorts, sorting incrementally allows returning tuples before the entire result set has been sorted, which particularly enables optimizations with LIMIT queries. It may also reduce memory usage and the likelihood of spilling sorts to disk, but it comes at the cost of the increased overhead of splitting the result set into multiple sorting batches.", "/versions/15/sections/3/paragraphs/3": "In this plan, we have a nested-loop join node with two table scans as inputs, or children. The indentation of the node summary lines reflects the plan tree structure. The join's first, or \u201c outer \u201d , child is a bitmap scan similar to those we saw before. Its cost and row count are the same as we'd get from SELECT ... WHERE unique1 < 10 because we are applying the WHERE clause unique1 < 10 at that node. The t1.unique2 = t2.unique2 clause is not relevant yet, so it doesn't affect the row count of the outer scan. The nested-loop join node will run its second, or \u201c inner \u201d child once for each row obtained from the outer child. Column values from the current outer row can be plugged into the inner scan; here, the t1.unique2 value from the outer row is available, so we get a plan and costs similar to what we saw above for a simple SELECT ... WHERE t2.unique2 = constant case. (The estimated cost is actually a bit lower than what was seen above, as a result of caching that's expected to occur during the repeated index scans on t2 .) The costs of the loop node are then set on the basis of the cost of the outer scan, plus one repetition of the inner scan for each outer row (10 * 7.91, here), plus a little CPU time for join processing.", "/versions/15/sections/3/paragraphs/4": "It is possible to check the accuracy of the planner's estimates by using EXPLAIN 's ANALYZE option. With this option, EXPLAIN actually executes the query, and then displays the true row counts and true run time accumulated within each plan node, along with the same estimates that a plain EXPLAIN shows. For example, we might get a result like this:", "/versions/15/sections/3/paragraphs/5": "Because each worker executes the parallel portion of the plan to completion, it is not possible to simply take an ordinary query plan and run it using multiple workers. Each worker would produce a full copy of the output result set, so the query would not run any faster than normal but would produce incorrect results. Instead, the parallel portion of the plan must be what is known internally to the query optimizer as a partial plan ; that is, it must be constructed so that each process that executes the plan will generate only a subset of the output rows in such a way that each required output row is guaranteed to be generated by exactly one of the cooperating processes. Generally, this means that the scan on the driving table of the query must be a parallel-aware scan.", "/versions/15/sections/5/paragraphs/0": "nodeResult.c support for constant nodes needing special code.", "/versions/15/sections/5/paragraphs/1": "Result nodes are used in queries where no relations are scanned. Examples of such queries are:", "/versions/15/sections/5/paragraphs/2": "(Remember that in an INSERT or UPDATE, we need a plan tree that generates the new rows.)", "/versions/15/sections/5/paragraphs/3": "Result nodes are also used to optimise queries with constant qualifications (ie, quals that do not depend on the scanned data), such as:", "/versions/15/sections/5/paragraphs/4": "At runtime, the Result node evaluates the constant qual once, which is shown by EXPLAIN as a One-Time Filter. If it's false, we can return an empty result set without running the controlled plan at all. If it's true, we run the controlled plan normally and pass back the results.", "/versions/15/tables/0/columns/0/label": "Text-format label", "/versions/15/tables/0/columns/1/label": "Structured node identity", "/versions/15/sections/4/blocks/0/paragraphs/0": "Example copied from the PostgreSQL 15.19 manual; it was not executed for this collection.", "/versions/15/sections/4/blocks/0/paragraphs/1": "When an UPDATE , DELETE , or MERGE command affects an inheritance hierarchy, the output might look like this:"}, "fallback_fields": [], "source_language": "en", "original_snapshot_sha256": "aecd5c0469e88937c42ef7e7e8993bdb2760e1b3be4be2a8cf450147c7c79d59"}, "evidence_kind": "source and documentation", "explain_names": ["Result"], "partial_modes": [], "comparison_data": {"node_tag": "T_Result", "strategies": [], "text_names": ["Result"], "initializer": "ExecInitResult", "partial_modes": [], "memory_mechanism": "unclassified", "parallel_callbacks": []}, "comparison_hash": "7d9e21f5e91321228505ba502e7faa5b9ebdda5ba4d71b8a9b97571a1f87b5f5", "explain_prefixes": ["Parallel", "Async"], "runtime_verified": false, "source_inventory": {"explain": "src/backend/commands/explain.c", "executor": "src/backend/executor/execProcnode.c", "implementation": "src/backend/executor/nodeResult.c"}, "parallel_callbacks": []}, "16": {"facts": [{"label": "\u6838\u5fc3\u8282\u70b9\u6807\u7b7e", "value": "T_Result"}, {"label": "\u7ed3\u6784\u5316 EXPLAIN \u8282\u70b9\u7c7b\u578b", "value": "Result"}, {"label": "\u8f93\u5165", "value": "\u53ef\u9009\u7684\u5b50\u8ba1\u5212"}, {"label": "\u8f93\u51fa", "value": "\u6295\u5f71\u540e\u7684\u5143\u7ec4"}, {"label": "\u6267\u884c\u5668\u521d\u59cb\u5316\u51fd\u6570", "value": "ExecInitResult"}, {"label": "\u5185\u5b58\u673a\u5236", "value": "unclassified"}], "memory": {"evidence": [{"url": "https://ftp.postgresql.org/pub/source/v16.15/postgresql-16.15.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "c864f63b35a5262bafbef20a431050f1c1655b892f56da1a1485df3a0ca81ddf", "archive_sha256": "c1575341fa7bd40f5274ea465b34390f4dc64cdd0770af327005caaeb9f6b7ed"}], "mechanism": "unclassified", "description": "\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002", "source_notes": []}, "tables": [{"key": "explain-labels", "rows": [{"label": "Result", "identity": "Result"}], "title": "\u672c\u6784\u5efa\u4e2d\u7684 EXPLAIN \u6807\u7b7e", "columns": [{"key": "label", "label": "\u6587\u672c\u683c\u5f0f\u6807\u7b7e"}, {"key": "identity", "label": "\u7ed3\u6784\u5316\u8282\u70b9\u6807\u8bc6"}]}], "related": [{"url": "/wiki/sql/explain/?v=16", "label": "EXPLAIN"}, {"url": "/docs/16/using-explain.html", "label": "\u4f7f\u7528 EXPLAIN"}, {"url": "/docs/16/parallel-plans.html", "label": "\u5e76\u884c\u8ba1\u5212"}], "release": {"ref": "PostgreSQL 16.15 source archive", "label": "16.15", "major": "16", "channel": "stable", "revision": "c1575341fa7bd40f5274ea465b34390f4dc64cdd0770af327005caaeb9f6b7ed", "source_url": "https://ftp.postgresql.org/pub/source/v16.15/postgresql-16.15.tar.bz2", "source_snapshot_utc": ""}, "sources": [{"url": "https://ftp.postgresql.org/pub/source/v16.15/postgresql-16.15.tar.bz2", "line": 1205, "path": "src/backend/commands/explain.c", "label": "src/backend/commands/explain.c:1205", "sha256": "8e017f0116dbea471339b40c37a667cc9f95039e7e0329c783e5e8ce194de7e1", "archive_sha256": "c1575341fa7bd40f5274ea465b34390f4dc64cdd0770af327005caaeb9f6b7ed"}, {"url": "https://ftp.postgresql.org/pub/source/v16.15/postgresql-16.15.tar.bz2", "line": 166, "path": "src/backend/executor/execProcnode.c", "label": "src/backend/executor/execProcnode.c:166", "sha256": "e48c08e555f8cb4e4bb43df516c4b8906ce9bc374b2a745d98a1fc8c22cc5099", "archive_sha256": "c1575341fa7bd40f5274ea465b34390f4dc64cdd0770af327005caaeb9f6b7ed"}, {"url": "https://ftp.postgresql.org/pub/source/v16.15/postgresql-16.15.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "c864f63b35a5262bafbef20a431050f1c1655b892f56da1a1485df3a0ca81ddf", "archive_sha256": "c1575341fa7bd40f5274ea465b34390f4dc64cdd0770af327005caaeb9f6b7ed"}, {"url": "https://ftp.postgresql.org/pub/source/v16.15/postgresql-16.15.tar.bz2", "path": "src/include/nodes/plannodes.h", "label": "src/include/nodes/plannodes.h", "sha256": "97db47353db76326b874589a5ad0a04501cc74cd72e237e7bd956e7472c41f1f", "archive_sha256": "c1575341fa7bd40f5274ea465b34390f4dc64cdd0770af327005caaeb9f6b7ed"}, {"url": "https://pg.center/docs/16/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 16.15 \u00b7 using-explain", "sha256": "bd8b86e5281cf0e52ad6e0e4bb8b6ff6510dac61982b44f0c1dd07d54012db3c", "language": "en", "original_url": "/docs/16/using-explain.html#USING-EXPLAIN-BASICS"}, {"url": "https://pg.center/docs/16/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 16.15 \u00b7 using-explain", "sha256": "bd8b86e5281cf0e52ad6e0e4bb8b6ff6510dac61982b44f0c1dd07d54012db3c", "language": "en", "original_url": "/docs/16/using-explain.html#USING-EXPLAIN-ANALYZE"}, {"url": "https://pg.center/docs/16/parallel-plans.html#PARALLEL-PLANS", "path": "parallel-plans.html", "label": "PostgreSQL 16.15 \u00b7 parallel-plans", "sha256": "53d83f63f97381fe1e4c0cfe5ceb81d30c1542b03e35a144684afd8fb3b9686c", "language": "en", "original_url": "/docs/16/parallel-plans.html#PARALLEL-PLANS"}], "node_tag": "T_Result", "sections": [{"title": "EXPLAIN \u540d\u79f0\u4e0e\u5c5e\u6027", "paragraphs": ["\u7ed3\u6784\u5316\u683c\u5f0f\u4f7f\u7528\u4e0a\u8ff0 Node Type\u3002\u6587\u672c\u683c\u5f0f\u540d\u79f0\u8fd8\u53ef\u80fd\u5305\u542b\u64cd\u4f5c\u3001\u7b56\u7565\u3001\u8fde\u63a5\u7c7b\u578b\u3001\u626b\u63cf\u65b9\u5411\u6216\u805a\u5408\u9636\u6bb5\u5c5e\u6027\u3002", "\u6b64\u6e90\u7801\u8bb0\u5f55\u7684\u6587\u672c\u540d\u79f0\uff1aResult.", "\u5e76\u884c\u611f\u77e5\u4e0e\u5e76\u884c\u5b89\u5168\u662f\u4e0d\u540c\u7684\u8ba1\u5212\u5c5e\u6027\u3002\u5728\u5e76\u884c\u5de5\u4f5c\u8fdb\u7a0b\u5185\u8fd0\u884c\u7684\u8282\u70b9\u4e0d\u4e00\u5b9a\u662f\u5e76\u884c\u611f\u77e5\u8282\u70b9\u3002"]}, {"title": "\u5185\u5b58\u4e0e\u4e34\u65f6\u5b58\u50a8", "paragraphs": ["\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002"]}, {"title": "\u5e76\u884c\u6267\u884c\u4e0e\u8fd0\u884c\u4fe1\u606f\u91c7\u96c6", "paragraphs": ["\u4ee5\u4e0b\u6e90\u7801\u56de\u8c03\u53ef\u4ee5\u534f\u8c03\u6267\u884c\u6216\u6536\u96c6\u5de5\u4f5c\u8fdb\u7a0b\u7684\u6d4b\u91cf\u6570\u636e\u3002\u56de\u8c03\u5b58\u5728\u4e0d\u4ee3\u8868\u8be5\u8282\u70b9\u666e\u904d\u652f\u6301\u5171\u4eab\u5e76\u884c\u626b\u63cf\u6216\u5171\u4eab\u72b6\u6001\u3002", "\u6b64\u6784\u5efa\u7684\u56de\u8c03\uff1anone extracted from this node implementation."]}, {"title": "\u540c\u7248\u672c\u624b\u518c\u8bf4\u660e", "paragraphs": ["\u9700\u8981\u7406\u89e3\uff0c\u4e0a\u5c42\u8282\u70b9\u7684\u4ee3\u4ef7\u5305\u542b\u5176\u5168\u90e8\u5b50\u8282\u70b9\u7684\u4ee3\u4ef7\u3002\u540c\u65f6\uff0c\u4ee3\u4ef7\u4ec5\u53cd\u6620\u89c4\u5212\u5668\u5173\u6ce8\u7684\u56e0\u7d20\u3002\u5c24\u5176\u662f\uff0c\u4ee3\u4ef7\u4e0d\u5305\u542b\u5411\u5ba2\u6237\u7aef\u4f20\u8f93\u7ed3\u679c\u884c\u6240\u82b1\u8d39\u7684\u65f6\u95f4\uff0c\u5c3d\u7ba1\u5b83\u53ef\u80fd\u663e\u8457\u5f71\u54cd\u5b9e\u9645\u8017\u65f6\uff1b\u89c4\u5212\u5668\u5ffd\u7565\u5b83\uff0c\u662f\u56e0\u4e3a\u6539\u53d8\u8ba1\u5212\u65e0\u6cd5\u6539\u53d8\u8fd9\u90e8\u5206\u65f6\u95f4\u3002\uff08\u6211\u4eec\u76f8\u4fe1\u6bcf\u4e2a\u6b63\u786e\u8ba1\u5212\u90fd\u4f1a\u8f93\u51fa\u540c\u6837\u7684\u884c\u96c6\u3002\uff09", "rows \u5bb9\u6613\u4ee4\u4eba\u8bef\u89e3\uff1a\u5b83\u8868\u793a\u8282\u70b9\u8f93\u51fa\u7684\u884c\u6570\uff0c\u800c\u4e0d\u662f\u5904\u7406\u6216\u626b\u63cf\u7684\u884c\u6570\u3002\u8282\u70b9\u5e94\u7528 WHERE \u6761\u4ef6\u7b5b\u9009\u540e\uff0c\u8f93\u51fa\u884c\u6570\u901a\u5e38\u5c0f\u4e8e\u626b\u63cf\u884c\u6570\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u9876\u5c42 rows \u4f30\u8ba1\u5e94\u63a5\u8fd1\u67e5\u8be2\u5b9e\u9645\u8fd4\u56de\u3001\u66f4\u65b0\u6216\u5220\u9664\u7684\u884c\u6570\u3002", "\u4e0e\u666e\u901a\u6392\u5e8f\u76f8\u6bd4\uff0c\u589e\u91cf\u6392\u5e8f\u53ef\u5728\u6574\u4e2a\u7ed3\u679c\u96c6\u5c1a\u672a\u6392\u5b8c\u65f6\u5c31\u8fd4\u56de\u5143\u7ec4\uff0c\u5c24\u5176\u6709\u5229\u4e8e\u4f18\u5316\u5e26 LIMIT \u7684\u67e5\u8be2\u3002\u5b83\u8fd8\u53ef\u80fd\u51cf\u5c11\u5185\u5b58\u7528\u91cf\u548c\u6392\u5e8f\u6ea2\u5199\u78c1\u76d8\u7684\u6982\u7387\uff0c\u4f46\u4ee3\u4ef7\u662f\u5c06\u7ed3\u679c\u96c6\u62c6\u6210\u591a\u4e2a\u6392\u5e8f\u6279\u6b21\u6240\u5e26\u6765\u7684\u989d\u5916\u5f00\u9500\u3002", "\u6b64\u8ba1\u5212\u5305\u542b\u4e00\u4e2a\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\uff0c\u4ee5\u4e24\u4e2a\u8868\u626b\u63cf\u4f5c\u4e3a\u8f93\u5165\uff0c\u5373\u5b50\u8282\u70b9\u3002\u8282\u70b9\u6458\u8981\u884c\u7684\u7f29\u8fdb\u53cd\u6620\u8ba1\u5212\u6811\u7ed3\u6784\u3002\u8fde\u63a5\u7684\u7b2c\u4e00\u4e2a\u5b50\u8282\u70b9\uff08\u5916\u4fa7\u5b50\u8282\u70b9\uff09\u662f\u524d\u9762\u89c1\u8fc7\u7684\u4f4d\u56fe\u626b\u63cf\u3002\u5b83\u7684\u4ee3\u4ef7\u548c\u884c\u6570\u4e0e SELECT ... WHERE unique1 < 10 \u76f8\u540c\uff0c\u56e0\u4e3a\u8be5\u8282\u70b9\u5e94\u7528\u4e86 WHERE \u6761\u4ef6 unique1 < 10\u3002t1.unique2 = t2.unique2 \u6761\u4ef6\u6b64\u65f6\u5c1a\u4e0d\u76f8\u5173\uff0c\u56e0\u6b64\u4e0d\u4f1a\u5f71\u54cd\u5916\u4fa7\u626b\u63cf\u7684\u884c\u6570\u3002\u5bf9\u4e8e\u4ece\u5916\u4fa7\u5b50\u8282\u70b9\u83b7\u53d6\u7684\u6bcf\u4e00\u884c\uff0c\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\u90fd\u4f1a\u6267\u884c\u4e00\u6b21\u7b2c\u4e8c\u4e2a\u5b50\u8282\u70b9\uff08\u5185\u4fa7\u5b50\u8282\u70b9\uff09\u3002\u5f53\u524d\u5916\u4fa7\u884c\u7684\u5217\u503c\u53ef\u4ee5\u4ee3\u5165\u5185\u4fa7\u626b\u63cf\uff1b\u8fd9\u91cc\u53ef\u4f7f\u7528\u5916\u4fa7\u884c\u7684 t1.unique2 \u503c\uff0c\u56e0\u6b64\u5f97\u5230\u7684\u8ba1\u5212\u548c\u4ee3\u4ef7\u4e0e\u4e0a\u6587\u7b80\u5355\u7684 SELECT ... WHERE t2.unique2 = constant \u60c5\u51b5\u7c7b\u4f3c\u3002\uff08\u4f30\u8ba1\u4ee3\u4ef7\u5b9e\u9645\u7565\u4f4e\u4e8e\u4e0a\u4f8b\uff0c\u8fd9\u662f\u56e0\u4e3a\u9884\u8ba1\u53cd\u590d\u626b\u63cf t2 \u7d22\u5f15\u65f6\u4f1a\u4ea7\u751f\u7f13\u5b58\u6536\u76ca\u3002\uff09\u5faa\u73af\u8282\u70b9\u7684\u4ee3\u4ef7\u7531\u5916\u4fa7\u626b\u63cf\u4ee3\u4ef7\u3001\u6bcf\u4e2a\u5916\u4fa7\u884c\u6267\u884c\u4e00\u6b21\u5185\u4fa7\u626b\u63cf\u7684\u4ee3\u4ef7\uff08\u672c\u4f8b\u4e3a 10 * 7.91\uff09\uff0c\u4ee5\u53ca\u5c11\u91cf\u8fde\u63a5\u5904\u7406\u6240\u9700\u7684 CPU \u65f6\u95f4\u7ec4\u6210\u3002", "\u53ef\u4f7f\u7528 EXPLAIN \u7684 ANALYZE \u9009\u9879\u68c0\u67e5\u89c4\u5212\u5668\u4f30\u7b97\u662f\u5426\u51c6\u786e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\uff0cEXPLAIN \u4f1a\u5b9e\u9645\u6267\u884c\u67e5\u8be2\uff0c\u7136\u540e\u663e\u793a\u6bcf\u4e2a\u8ba1\u5212\u8282\u70b9\u7d2f\u8ba1\u7684\u771f\u5b9e\u884c\u6570\u548c\u771f\u5b9e\u8fd0\u884c\u65f6\u95f4\uff0c\u4ee5\u53ca\u666e\u901a EXPLAIN \u6240\u663e\u793a\u7684\u4f30\u7b97\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u80fd\u5f97\u5230\u5982\u4e0b\u7ed3\u679c\uff1a", "\u7531\u4e8e\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u5c06\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u6267\u884c\u5230\u5e95\uff0c\u56e0\u6b64\u4e0d\u80fd\u7b80\u5355\u5730\u62ff\u4e00\u4e2a\u666e\u901a\u67e5\u8be2\u8ba1\u5212\u5e76\u8ba9\u591a\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u540c\u65f6\u8fd0\u884c\u3002\u90a3\u6837\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u751f\u6210\u5b8c\u6574\u8f93\u51fa\u7ed3\u679c\u96c6\u7684\u4e00\u4efd\u526f\u672c\uff0c\u6240\u4ee5\u67e5\u8be2\u4e0d\u4ec5\u4e0d\u4f1a\u6bd4\u5e73\u5e38\u66f4\u5feb\uff0c\u53cd\u800c\u4f1a\u4ea7\u751f\u9519\u8bef\u7ed3\u679c\u3002\u76f8\u53cd\uff0c\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u5fc5\u987b\u662f\u67e5\u8be2\u4f18\u5316\u5668\u5185\u90e8\u6240\u8bf4\u7684 \u90e8\u5206\u8ba1\u5212 \uff1b\u4e5f\u5c31\u662f\u8bf4\uff0c\u5b83\u5fc5\u987b\u88ab\u6784\u9020\u4e3a\u4f7f\u6267\u884c\u8be5\u8ba1\u5212\u7684\u6bcf\u4e2a\u8fdb\u7a0b\u53ea\u751f\u6210\u8f93\u51fa\u884c\u7684\u4e00\u4e2a\u5b50\u96c6\uff0c\u5e76\u4e14\u4fdd\u8bc1\u6bcf\u4e00\u6761\u6240\u9700\u8f93\u51fa\u884c\u90fd\u6070\u597d\u7531\u67d0\u4e2a\u534f\u4f5c\u8fdb\u7a0b\u751f\u6210\u4e00\u6b21\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u8fd9\u610f\u5473\u7740\u67e5\u8be2\u9a71\u52a8\u8868\u4e0a\u7684\u626b\u63cf\u5fc5\u987b\u662f\u5e76\u884c\u611f\u77e5\u626b\u63cf\u3002"]}, {"title": "\u672c\u7248\u624b\u518c\u4e2d\u7684\u793a\u4f8b", "blocks": [{"code": "EXPLAIN UPDATE parent SET f2 = f2 + 1 WHERE f1 = 101;\n                                              QUERY PLAN\n------------------------------------------------------------------------------------------------------\n Update on parent  (cost=0.00..24.59 rows=0 width=0)\n   Update on parent parent_1\n   Update on child1 parent_2\n   Update on child2 parent_3\n   Update on child3 parent_4\n   ->  Result  (cost=0.00..24.59 rows=4 width=14)\n         ->  Append  (cost=0.00..24.54 rows=4 width=14)\n               ->  Seq Scan on parent parent_1  (cost=0.00..0.00 rows=1 width=14)\n                     Filter: (f1 = 101)\n               ->  Index Scan using child1_pkey on child1 parent_2  (cost=0.15..8.17 rows=1 width=14)\n                     Index Cond: (f1 = 101)\n               ->  Index Scan using child2_pkey on child2 parent_3  (cost=0.15..8.17 rows=1 width=14)\n                     Index Cond: (f1 = 101)\n               ->  Index Scan using child3_pkey on child3 parent_4  (cost=0.15..8.17 rows=1 width=14)\n                     Index Cond: (f1 = 101)", "source": {"url": "/docs/16/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 16.15 \u00b7 using-explain", "sha256": "bd8b86e5281cf0e52ad6e0e4bb8b6ff6510dac61982b44f0c1dd07d54012db3c"}, "paragraphs": ["\u793a\u4f8b\u6458\u81ea PostgreSQL 16.15 \u624b\u518c\uff1b\u672c\u767e\u79d1\u672a\u5b9e\u9645\u6267\u884c\u6b64\u793a\u4f8b\u3002", "UPDATE\u3001DELETE \u6216 MERGE \u4f5c\u7528\u4e8e\u7ee7\u627f\u5c42\u7ea7\u65f6\uff0c\u8f93\u51fa\u53ef\u80fd\u5982\u4e0b\uff1a"]}]}, {"title": "\u6267\u884c\u5668\u5b9e\u73b0\u8bf4\u660e", "paragraphs": ["nodeResult.c\uff1a\u652f\u6301\u9700\u8981\u7279\u6b8a\u4ee3\u7801\u7684\u5e38\u91cf\u8282\u70b9\u3002", "Result \u8282\u70b9\u7528\u4e8e\u4e0d\u626b\u63cf\u4efb\u4f55\u5173\u7cfb\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\uff08\u8bf7\u8bb0\u4f4f\uff0cINSERT \u6216 UPDATE \u9700\u8981\u4e00\u68f5\u751f\u6210\u65b0\u884c\u7684\u8ba1\u5212\u6811\u3002\uff09", "Result \u8282\u70b9\u4e5f\u7528\u4e8e\u4f18\u5316\u5e26\u6709\u5e38\u91cf\u6761\u4ef6\uff08\u5373\u4e0d\u4f9d\u8d56\u626b\u63cf\u6570\u636e\u7684\u6761\u4ef6\uff09\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\u8fd0\u884c\u65f6\uff0cResult \u8282\u70b9\u53ea\u8ba1\u7b97\u4e00\u6b21\u5e38\u91cf\u6761\u4ef6\uff0cEXPLAIN \u5c06\u5176\u663e\u793a\u4e3a One-Time Filter\u3002\u5982\u679c\u6761\u4ef6\u4e3a\u5047\uff0c\u65e0\u9700\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u4fbf\u53ef\u8fd4\u56de\u7a7a\u7ed3\u679c\u96c6\uff1b\u5982\u679c\u4e3a\u771f\uff0c\u5219\u6b63\u5e38\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u5e76\u4f20\u56de\u7ed3\u679c\u3002"]}, {"code": "case T_Result:\n\t\t\tpname = sname = \"Result\";\n\t\t\tbreak;", "title": "\u6838\u5fc3\u6e90\u7801\u4e2d\u7684 EXPLAIN \u6807\u8bc6"}], "strategies": [], "description": ["\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002"], "localization": {"status": "complete", "sources": [{"url": "/docs/16/parallel-plans.html", "method": "same-major semantic node", "sha256": "ebdab5889ade652e62c92fd2e4361d8aa32ae8132faccfdcafab869292fc4392", "language": "zh", "matched_nodes": ["#PARALLEL-PLANS/p[2]"]}], "language": "zh", "original_text": {"/versions/16/description/0": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/versions/16/facts/0/label": "Core node tag", "/versions/16/facts/1/label": "Structured EXPLAIN Node Type", "/versions/16/facts/2/label": "Inputs", "/versions/16/facts/2/value": "Optional child plan", "/versions/16/facts/3/label": "Output", "/versions/16/facts/3/value": "Projected tuples", "/versions/16/facts/4/label": "Executor initializer", "/versions/16/facts/5/label": "Memory mechanism", "/versions/16/tables/0/title": "EXPLAIN labels in this source build", "/versions/16/related/1/label": "Using EXPLAIN", "/versions/16/related/2/label": "Parallel plans", "/versions/16/sections/0/title": "EXPLAIN names and attributes", "/versions/16/sections/1/title": "Memory and temporary storage", "/versions/16/sections/2/title": "Parallel execution and instrumentation", "/versions/16/sections/3/title": "Same-version manual discussion", "/versions/16/sections/4/title": "Examples from this manual build", "/versions/16/sections/5/title": "Executor implementation notes", "/versions/16/sections/6/title": "EXPLAIN identity in core source", "/versions/16/memory/description": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/16/sections/0/paragraphs/0": "Structured formats use the Node Type above. Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.", "/versions/16/sections/0/paragraphs/1": "Text names recorded by this source: Result.", "/versions/16/sections/0/paragraphs/2": "Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node.", "/versions/16/sections/1/paragraphs/0": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/16/sections/2/paragraphs/0": "The source callbacks below can coordinate execution or collect worker instrumentation. Their presence is not a blanket claim that this node supports a shared parallel scan or shared state.", "/versions/16/sections/2/paragraphs/1": "Callbacks in this build: none extracted from this node implementation.", "/versions/16/sections/3/paragraphs/0": "It's important to understand that the cost of an upper-level node includes the cost of all its child nodes. It's also important to realize that the cost only reflects things that the planner cares about. In particular, the cost does not consider the time spent transmitting result rows to the client, which could be an important factor in the real elapsed time; but the planner ignores it because it cannot change it by altering the plan. (Every correct plan will output the same row set, we trust.)", "/versions/16/sections/3/paragraphs/1": "The rows value is a little tricky because it is not the number of rows processed or scanned by the plan node, but rather the number emitted by the node. This is often less than the number scanned, as a result of filtering by any WHERE -clause conditions that are being applied at the node. Ideally the top-level rows estimate will approximate the number of rows actually returned, updated, or deleted by the query.", "/versions/16/sections/3/paragraphs/2": "Compared to regular sorts, sorting incrementally allows returning tuples before the entire result set has been sorted, which particularly enables optimizations with LIMIT queries. It may also reduce memory usage and the likelihood of spilling sorts to disk, but it comes at the cost of the increased overhead of splitting the result set into multiple sorting batches.", "/versions/16/sections/3/paragraphs/3": "In this plan, we have a nested-loop join node with two table scans as inputs, or children. The indentation of the node summary lines reflects the plan tree structure. The join's first, or \u201c outer \u201d , child is a bitmap scan similar to those we saw before. Its cost and row count are the same as we'd get from SELECT ... WHERE unique1 < 10 because we are applying the WHERE clause unique1 < 10 at that node. The t1.unique2 = t2.unique2 clause is not relevant yet, so it doesn't affect the row count of the outer scan. The nested-loop join node will run its second, or \u201c inner \u201d child once for each row obtained from the outer child. Column values from the current outer row can be plugged into the inner scan; here, the t1.unique2 value from the outer row is available, so we get a plan and costs similar to what we saw above for a simple SELECT ... WHERE t2.unique2 = constant case. (The estimated cost is actually a bit lower than what was seen above, as a result of caching that's expected to occur during the repeated index scans on t2 .) The costs of the loop node are then set on the basis of the cost of the outer scan, plus one repetition of the inner scan for each outer row (10 * 7.91, here), plus a little CPU time for join processing.", "/versions/16/sections/3/paragraphs/4": "It is possible to check the accuracy of the planner's estimates by using EXPLAIN 's ANALYZE option. With this option, EXPLAIN actually executes the query, and then displays the true row counts and true run time accumulated within each plan node, along with the same estimates that a plain EXPLAIN shows. For example, we might get a result like this:", "/versions/16/sections/3/paragraphs/5": "Because each worker executes the parallel portion of the plan to completion, it is not possible to simply take an ordinary query plan and run it using multiple workers. Each worker would produce a full copy of the output result set, so the query would not run any faster than normal but would produce incorrect results. Instead, the parallel portion of the plan must be what is known internally to the query optimizer as a partial plan ; that is, it must be constructed so that each process that executes the plan will generate only a subset of the output rows in such a way that each required output row is guaranteed to be generated by exactly one of the cooperating processes. Generally, this means that the scan on the driving table of the query must be a parallel-aware scan.", "/versions/16/sections/5/paragraphs/0": "nodeResult.c support for constant nodes needing special code.", "/versions/16/sections/5/paragraphs/1": "Result nodes are used in queries where no relations are scanned. Examples of such queries are:", "/versions/16/sections/5/paragraphs/2": "(Remember that in an INSERT or UPDATE, we need a plan tree that generates the new rows.)", "/versions/16/sections/5/paragraphs/3": "Result nodes are also used to optimise queries with constant qualifications (ie, quals that do not depend on the scanned data), such as:", "/versions/16/sections/5/paragraphs/4": "At runtime, the Result node evaluates the constant qual once, which is shown by EXPLAIN as a One-Time Filter. If it's false, we can return an empty result set without running the controlled plan at all. If it's true, we run the controlled plan normally and pass back the results.", "/versions/16/tables/0/columns/0/label": "Text-format label", "/versions/16/tables/0/columns/1/label": "Structured node identity", "/versions/16/sections/4/blocks/0/paragraphs/0": "Example copied from the PostgreSQL 16.15 manual; it was not executed for this collection.", "/versions/16/sections/4/blocks/0/paragraphs/1": "When an UPDATE , DELETE , or MERGE command affects an inheritance hierarchy, the output might look like this:"}, "fallback_fields": [], "source_language": "en", "original_snapshot_sha256": "8b2cc3134cbe8ce9c87e101103989681c393787bdd350e50447a516bbe2e1a6a"}, "evidence_kind": "source and documentation", "explain_names": ["Result"], "partial_modes": [], "comparison_data": {"node_tag": "T_Result", "strategies": [], "text_names": ["Result"], "initializer": "ExecInitResult", "partial_modes": [], "memory_mechanism": "unclassified", "parallel_callbacks": []}, "comparison_hash": "7d9e21f5e91321228505ba502e7faa5b9ebdda5ba4d71b8a9b97571a1f87b5f5", "explain_prefixes": ["Parallel", "Async"], "runtime_verified": false, "source_inventory": {"explain": "src/backend/commands/explain.c", "executor": "src/backend/executor/execProcnode.c", "implementation": "src/backend/executor/nodeResult.c"}, "parallel_callbacks": []}, "17": {"facts": [{"label": "\u6838\u5fc3\u8282\u70b9\u6807\u7b7e", "value": "T_Result"}, {"label": "\u7ed3\u6784\u5316 EXPLAIN \u8282\u70b9\u7c7b\u578b", "value": "Result"}, {"label": "\u8f93\u5165", "value": "\u53ef\u9009\u7684\u5b50\u8ba1\u5212"}, {"label": "\u8f93\u51fa", "value": "\u6295\u5f71\u540e\u7684\u5143\u7ec4"}, {"label": "\u6267\u884c\u5668\u521d\u59cb\u5316\u51fd\u6570", "value": "ExecInitResult"}, {"label": "\u5185\u5b58\u673a\u5236", "value": "unclassified"}], "memory": {"evidence": [{"url": "https://ftp.postgresql.org/pub/source/v17.11/postgresql-17.11.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "54d71ca039452ab93b9ff3edc63e345701fe6e0782b8d8afe4c9246aeda6f7f5", "archive_sha256": "dd27f2b3c59e73ed14aa3324901242bf69a032a6347805f274e6260322d42979"}], "mechanism": "unclassified", "description": "\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002", "source_notes": []}, "tables": [{"key": "explain-labels", "rows": [{"label": "Result", "identity": "Result"}], "title": "\u672c\u6784\u5efa\u4e2d\u7684 EXPLAIN \u6807\u7b7e", "columns": [{"key": "label", "label": "\u6587\u672c\u683c\u5f0f\u6807\u7b7e"}, {"key": "identity", "label": "\u7ed3\u6784\u5316\u8282\u70b9\u6807\u8bc6"}]}], "related": [{"url": "/wiki/sql/explain/?v=17", "label": "EXPLAIN"}, {"url": "/docs/17/using-explain.html", "label": "\u4f7f\u7528 EXPLAIN"}, {"url": "/docs/17/parallel-plans.html", "label": "\u5e76\u884c\u8ba1\u5212"}], "release": {"ref": "PostgreSQL 17.11 source archive", "label": "17.11", "major": "17", "channel": "stable", "revision": "dd27f2b3c59e73ed14aa3324901242bf69a032a6347805f274e6260322d42979", "source_url": "https://ftp.postgresql.org/pub/source/v17.11/postgresql-17.11.tar.bz2", "source_snapshot_utc": ""}, "sources": [{"url": "https://ftp.postgresql.org/pub/source/v17.11/postgresql-17.11.tar.bz2", "line": 1394, "path": "src/backend/commands/explain.c", "label": "src/backend/commands/explain.c:1394", "sha256": "741251b1a3b6d269a52a673d42eb63b02e13a5872db7b359b137086ab21b63c8", "archive_sha256": "dd27f2b3c59e73ed14aa3324901242bf69a032a6347805f274e6260322d42979"}, {"url": "https://ftp.postgresql.org/pub/source/v17.11/postgresql-17.11.tar.bz2", "line": 166, "path": "src/backend/executor/execProcnode.c", "label": "src/backend/executor/execProcnode.c:166", "sha256": "a77576e158b94cb01fa8c5174ba133004eabdd727660323f8afc66c8d2e757b8", "archive_sha256": "dd27f2b3c59e73ed14aa3324901242bf69a032a6347805f274e6260322d42979"}, {"url": "https://ftp.postgresql.org/pub/source/v17.11/postgresql-17.11.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "54d71ca039452ab93b9ff3edc63e345701fe6e0782b8d8afe4c9246aeda6f7f5", "archive_sha256": "dd27f2b3c59e73ed14aa3324901242bf69a032a6347805f274e6260322d42979"}, {"url": "https://ftp.postgresql.org/pub/source/v17.11/postgresql-17.11.tar.bz2", "path": "src/include/nodes/plannodes.h", "label": "src/include/nodes/plannodes.h", "sha256": "d390dd69e2d3f5085beb42b33e46ff0676a2959b916a12b82118a7e545f8e562", "archive_sha256": "dd27f2b3c59e73ed14aa3324901242bf69a032a6347805f274e6260322d42979"}, {"url": "https://pg.center/docs/17/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 17.11 \u00b7 using-explain", "sha256": "8e3422c77496cc53bfc225ccadda3e82eb23c8c362b8eb95e7fb02cdb315ea78", "language": "en", "original_url": "/docs/17/using-explain.html#USING-EXPLAIN-BASICS"}, {"url": "https://pg.center/docs/17/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 17.11 \u00b7 using-explain", "sha256": "8e3422c77496cc53bfc225ccadda3e82eb23c8c362b8eb95e7fb02cdb315ea78", "language": "en", "original_url": "/docs/17/using-explain.html#USING-EXPLAIN-ANALYZE"}, {"url": "https://pg.center/docs/17/parallel-plans.html#PARALLEL-PLANS", "path": "parallel-plans.html", "label": "PostgreSQL 17.11 \u00b7 parallel-plans", "sha256": "784fe3d3b7ae7d1a34e466aa551bde484a40a3b60dc5d2ada6e1675f40713bbc", "language": "en", "original_url": "/docs/17/parallel-plans.html#PARALLEL-PLANS"}], "node_tag": "T_Result", "sections": [{"title": "EXPLAIN \u540d\u79f0\u4e0e\u5c5e\u6027", "paragraphs": ["\u7ed3\u6784\u5316\u683c\u5f0f\u4f7f\u7528\u4e0a\u8ff0 Node Type\u3002\u6587\u672c\u683c\u5f0f\u540d\u79f0\u8fd8\u53ef\u80fd\u5305\u542b\u64cd\u4f5c\u3001\u7b56\u7565\u3001\u8fde\u63a5\u7c7b\u578b\u3001\u626b\u63cf\u65b9\u5411\u6216\u805a\u5408\u9636\u6bb5\u5c5e\u6027\u3002", "\u6b64\u6e90\u7801\u8bb0\u5f55\u7684\u6587\u672c\u540d\u79f0\uff1aResult.", "\u5e76\u884c\u611f\u77e5\u4e0e\u5e76\u884c\u5b89\u5168\u662f\u4e0d\u540c\u7684\u8ba1\u5212\u5c5e\u6027\u3002\u5728\u5e76\u884c\u5de5\u4f5c\u8fdb\u7a0b\u5185\u8fd0\u884c\u7684\u8282\u70b9\u4e0d\u4e00\u5b9a\u662f\u5e76\u884c\u611f\u77e5\u8282\u70b9\u3002"]}, {"title": "\u5185\u5b58\u4e0e\u4e34\u65f6\u5b58\u50a8", "paragraphs": ["\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002"]}, {"title": "\u5e76\u884c\u6267\u884c\u4e0e\u8fd0\u884c\u4fe1\u606f\u91c7\u96c6", "paragraphs": ["\u4ee5\u4e0b\u6e90\u7801\u56de\u8c03\u53ef\u4ee5\u534f\u8c03\u6267\u884c\u6216\u6536\u96c6\u5de5\u4f5c\u8fdb\u7a0b\u7684\u6d4b\u91cf\u6570\u636e\u3002\u56de\u8c03\u5b58\u5728\u4e0d\u4ee3\u8868\u8be5\u8282\u70b9\u666e\u904d\u652f\u6301\u5171\u4eab\u5e76\u884c\u626b\u63cf\u6216\u5171\u4eab\u72b6\u6001\u3002", "\u6b64\u6784\u5efa\u7684\u56de\u8c03\uff1anone extracted from this node implementation."]}, {"title": "\u540c\u7248\u672c\u624b\u518c\u8bf4\u660e", "paragraphs": ["rows \u5bb9\u6613\u4ee4\u4eba\u8bef\u89e3\uff1a\u5b83\u8868\u793a\u8282\u70b9\u8f93\u51fa\u7684\u884c\u6570\uff0c\u800c\u4e0d\u662f\u5904\u7406\u6216\u626b\u63cf\u7684\u884c\u6570\u3002\u8282\u70b9\u5e94\u7528 WHERE \u6761\u4ef6\u7b5b\u9009\u540e\uff0c\u8f93\u51fa\u884c\u6570\u901a\u5e38\u5c0f\u4e8e\u626b\u63cf\u884c\u6570\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u9876\u5c42 rows \u4f30\u8ba1\u5e94\u63a5\u8fd1\u67e5\u8be2\u5b9e\u9645\u8fd4\u56de\u3001\u66f4\u65b0\u6216\u5220\u9664\u7684\u884c\u6570\u3002", "\u4e0e\u666e\u901a\u6392\u5e8f\u76f8\u6bd4\uff0c\u589e\u91cf\u6392\u5e8f\u53ef\u5728\u6574\u4e2a\u7ed3\u679c\u96c6\u5c1a\u672a\u6392\u5b8c\u65f6\u5c31\u8fd4\u56de\u5143\u7ec4\uff0c\u5c24\u5176\u6709\u5229\u4e8e\u4f18\u5316\u5e26 LIMIT \u7684\u67e5\u8be2\u3002\u5b83\u8fd8\u53ef\u80fd\u51cf\u5c11\u5185\u5b58\u7528\u91cf\u548c\u6392\u5e8f\u6ea2\u5199\u78c1\u76d8\u7684\u6982\u7387\uff0c\u4f46\u4ee3\u4ef7\u662f\u5c06\u7ed3\u679c\u96c6\u62c6\u6210\u591a\u4e2a\u6392\u5e8f\u6279\u6b21\u6240\u5e26\u6765\u7684\u989d\u5916\u5f00\u9500\u3002", "\u5728\u8fd9\u4e2a\u8ba1\u5212\u4e2d\uff0c\u6709\u4e00\u4e2a\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\uff0c\u5b83\u7684\u4e24\u4e2a\u8f93\u5165\uff0c\u4e5f\u5c31\u662f\u4e24\u4e2a\u5b50\u8282\u70b9\uff0c\u90fd\u662f\u8868\u626b\u63cf\u3002\u8282\u70b9\u6458\u8981\u884c\u7684\u7f29\u8fdb\u53cd\u6620\u4e86\u8ba1\u5212\u6811\u7ed3\u6784\u3002\u8fde\u63a5\u7684\u7b2c\u4e00\u4e2a\u5b50\u8282\u70b9\uff0c\u4e5f\u5c31\u662f \u201c \u5916\u4fa7 \u201d \u5b50\u8282\u70b9\uff0c\u662f\u4e00\u4e2a\u4e0e\u524d\u9762\u89c1\u8fc7\u7684\u4f4d\u56fe\u626b\u63cf\u7c7b\u4f3c\u7684\u8282\u70b9\u3002\u5b83\u7684\u4ee3\u4ef7\u548c\u884c\u8ba1\u6570\u4e0e SELECT ... WHERE unique1 < 10 \u5f97\u5230\u7684\u7ed3\u679c\u76f8\u540c\uff0c\u56e0\u4e3a WHERE \u5b50\u53e5 unique1 < 10 \u6b63\u662f\u5728\u8be5\u8282\u70b9\u4e0a\u5e94\u7528\u7684\u3002 t1.unique2 = t2.unique2 \u5b50\u53e5\u6b64\u65f6\u8fd8\u65e0\u5173\uff0c\u56e0\u6b64\u4e0d\u4f1a\u5f71\u54cd\u5916\u4fa7\u626b\u63cf\u7684\u884c\u8ba1\u6570\u3002\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\u4f1a\u5bf9\u4ece\u5916\u4fa7\u5b50\u8282\u70b9\u5f97\u5230\u7684\u6bcf\u4e00\u884c\u6267\u884c\u4e00\u6b21\u7b2c\u4e8c\u4e2a\uff0c\u4e5f\u5c31\u662f \u201c \u5185\u4fa7 \u201d \u5b50\u8282\u70b9\u3002\u5f53\u524d\u5916\u4fa7\u884c\u4e2d\u7684\u5217\u503c\u53ef\u4ee5\u4ee3\u5165\u5185\u4fa7\u626b\u63cf\uff1b\u8fd9\u91cc\u5916\u4fa7\u884c\u7684 t1.unique2 \u503c\u53ef\u7528\uff0c\u56e0\u6b64\u5f97\u5230\u7684\u8ba1\u5212\u548c\u4ee3\u4ef7\u4e0e\u524d\u9762\u770b\u5230\u7684\u7b80\u5355 SELECT ... WHERE t2.unique2 = constant \u60c5\u5f62\u7c7b\u4f3c\u3002\uff08\u7531\u4e8e\u9884\u671f\u5728\u5bf9 t2 \u53cd\u590d\u6267\u884c\u7d22\u5f15\u626b\u63cf\u671f\u95f4\u4f1a\u53d1\u751f\u7f13\u5b58\u547d\u4e2d\uff0c\u4f30\u8ba1\u4ee3\u4ef7\u5b9e\u9645\u4e0a\u6bd4\u524d\u9762\u770b\u5230\u7684\u7565\u4f4e\u4e00\u4e9b\u3002\uff09\u968f\u540e\uff0c\u5faa\u73af\u8282\u70b9\u7684\u4ee3\u4ef7\u5efa\u7acb\u5728\u5916\u4fa7\u626b\u63cf\u4ee3\u4ef7\u4e4b\u4e0a\uff0c\u518d\u52a0\u4e0a\u6bcf\u4e2a\u5916\u4fa7\u884c\u90fd\u8981\u6267\u884c\u4e00\u6b21\u5185\u4fa7\u626b\u63cf\u7684\u4ee3\u4ef7\uff08\u8fd9\u91cc\u662f 10 * 7.90\uff09\uff0c\u4ee5\u53ca\u5c11\u91cf\u8fde\u63a5\u5904\u7406\u7684 CPU \u65f6\u95f4\u3002", "\u8fd9\u4e2a\u523b\u610f\u6784\u9020\u7684\u793a\u4f8b\u8bf4\u660e\u4e86\u4e24\u70b9\uff1a\u5916\u5c42\u8ba1\u5212\u7684\u503c\u53ef\u4f20\u5165\u5b50\u8ba1\u5212\uff08\u8fd9\u91cc\u4f20\u5165 t.four\uff09\uff0c\u5b50\u67e5\u8be2\u7ed3\u679c\u4e5f\u53ef\u4f9b\u5916\u5c42\u8ba1\u5212\u4f7f\u7528\u3002EXPLAIN \u7528 (subplan_name).col N \u4e00\u7c7b\u8bb0\u53f7\u663e\u793a\u8fd9\u4e9b\u7ed3\u679c\u503c\uff0c\u8868\u793a\u5b50 SELECT \u7684\u7b2c N \u4e2a\u8f93\u51fa\u5217\u3002", "\u53ef\u4f7f\u7528 EXPLAIN \u7684 ANALYZE \u9009\u9879\u68c0\u67e5\u89c4\u5212\u5668\u4f30\u7b97\u662f\u5426\u51c6\u786e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\uff0cEXPLAIN \u4f1a\u5b9e\u9645\u6267\u884c\u67e5\u8be2\uff0c\u7136\u540e\u663e\u793a\u6bcf\u4e2a\u8ba1\u5212\u8282\u70b9\u7d2f\u8ba1\u7684\u771f\u5b9e\u884c\u6570\u548c\u771f\u5b9e\u8fd0\u884c\u65f6\u95f4\uff0c\u4ee5\u53ca\u666e\u901a EXPLAIN \u6240\u663e\u793a\u7684\u4f30\u7b97\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u80fd\u5f97\u5230\u5982\u4e0b\u7ed3\u679c\uff1a", "\u7531\u4e8e\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u5c06\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u6267\u884c\u5230\u5e95\uff0c\u56e0\u6b64\u4e0d\u80fd\u7b80\u5355\u5730\u62ff\u4e00\u4e2a\u666e\u901a\u67e5\u8be2\u8ba1\u5212\u5e76\u8ba9\u591a\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u540c\u65f6\u8fd0\u884c\u3002\u90a3\u6837\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u751f\u6210\u5b8c\u6574\u8f93\u51fa\u7ed3\u679c\u96c6\u7684\u4e00\u4efd\u526f\u672c\uff0c\u6240\u4ee5\u67e5\u8be2\u4e0d\u4ec5\u4e0d\u4f1a\u6bd4\u5e73\u5e38\u66f4\u5feb\uff0c\u53cd\u800c\u4f1a\u4ea7\u751f\u9519\u8bef\u7ed3\u679c\u3002\u76f8\u53cd\uff0c\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u5fc5\u987b\u662f\u67e5\u8be2\u4f18\u5316\u5668\u5185\u90e8\u6240\u8bf4\u7684 \u90e8\u5206\u8ba1\u5212 \uff1b\u4e5f\u5c31\u662f\u8bf4\uff0c\u5b83\u5fc5\u987b\u88ab\u6784\u9020\u4e3a\u4f7f\u6267\u884c\u8be5\u8ba1\u5212\u7684\u6bcf\u4e2a\u8fdb\u7a0b\u53ea\u751f\u6210\u8f93\u51fa\u884c\u7684\u4e00\u4e2a\u5b50\u96c6\uff0c\u5e76\u4e14\u4fdd\u8bc1\u6bcf\u4e00\u6761\u6240\u9700\u8f93\u51fa\u884c\u90fd\u6070\u597d\u7531\u67d0\u4e2a\u534f\u4f5c\u8fdb\u7a0b\u751f\u6210\u4e00\u6b21\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u8fd9\u610f\u5473\u7740\u67e5\u8be2\u9a71\u52a8\u8868\u4e0a\u7684\u626b\u63cf\u5fc5\u987b\u662f\u5e76\u884c\u611f\u77e5\u626b\u63cf\u3002"]}, {"title": "\u672c\u7248\u624b\u518c\u4e2d\u7684\u793a\u4f8b", "blocks": [{"code": "EXPLAIN VERBOSE SELECT unique1\nFROM tenk1 t1 WHERE t1.ten = (SELECT (random() * 10)::integer);\n\n                             QUERY PLAN\n--------------------------------------------------------------------\n Seq Scan on public.tenk1 t1  (cost=0.02..470.02 rows=1000 width=4)\n   Output: t1.unique1\n   Filter: (t1.ten = (InitPlan 1).col1)\n   InitPlan 1\n     ->  Result  (cost=0.00..0.02 rows=1 width=4)\n           Output: ((random() * '10'::double precision))::integer", "source": {"url": "/docs/17/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 17.11 \u00b7 using-explain", "sha256": "8e3422c77496cc53bfc225ccadda3e82eb23c8c362b8eb95e7fb02cdb315ea78"}, "paragraphs": ["\u793a\u4f8b\u6458\u81ea PostgreSQL 17.11 \u624b\u518c\uff1b\u672c\u767e\u79d1\u672a\u5b9e\u9645\u6267\u884c\u6b64\u793a\u4f8b\u3002", "\u5982\u679c\u5b50 SELECT \u4e0d\u4ec5\u4e0d\u5f15\u7528\u5916\u5c42\u67e5\u8be2\u7684\u4efb\u4f55\u53d8\u91cf\uff0c\u800c\u4e14\u6700\u591a\u53ea\u4f1a\u8fd4\u56de\u4e00\u884c\uff0c\u90a3\u4e48\u5b83\u8fd8\u53ef\u80fd\u88ab\u5b9e\u73b0\u6210\u4e00\u4e2a \u521d\u59cb\u8ba1\u5212 \uff1a"]}]}, {"title": "\u6267\u884c\u5668\u5b9e\u73b0\u8bf4\u660e", "paragraphs": ["nodeResult.c\uff1a\u652f\u6301\u9700\u8981\u7279\u6b8a\u4ee3\u7801\u7684\u5e38\u91cf\u8282\u70b9\u3002", "Result \u8282\u70b9\u7528\u4e8e\u4e0d\u626b\u63cf\u4efb\u4f55\u5173\u7cfb\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\uff08\u8bf7\u8bb0\u4f4f\uff0cINSERT \u6216 UPDATE \u9700\u8981\u4e00\u68f5\u751f\u6210\u65b0\u884c\u7684\u8ba1\u5212\u6811\u3002\uff09", "Result \u8282\u70b9\u4e5f\u7528\u4e8e\u4f18\u5316\u5e26\u6709\u5e38\u91cf\u6761\u4ef6\uff08\u5373\u4e0d\u4f9d\u8d56\u626b\u63cf\u6570\u636e\u7684\u6761\u4ef6\uff09\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\u8fd0\u884c\u65f6\uff0cResult \u8282\u70b9\u53ea\u8ba1\u7b97\u4e00\u6b21\u5e38\u91cf\u6761\u4ef6\uff0cEXPLAIN \u5c06\u5176\u663e\u793a\u4e3a One-Time Filter\u3002\u5982\u679c\u6761\u4ef6\u4e3a\u5047\uff0c\u65e0\u9700\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u4fbf\u53ef\u8fd4\u56de\u7a7a\u7ed3\u679c\u96c6\uff1b\u5982\u679c\u4e3a\u771f\uff0c\u5219\u6b63\u5e38\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u5e76\u4f20\u56de\u7ed3\u679c\u3002"]}, {"code": "case T_Result:\n\t\t\tpname = sname = \"Result\";\n\t\t\tbreak;", "title": "\u6838\u5fc3\u6e90\u7801\u4e2d\u7684 EXPLAIN \u6807\u8bc6"}], "strategies": [], "description": ["\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002"], "localization": {"status": "complete", "sources": [{"url": "/docs/17/parallel-plans.html", "method": "same-major semantic node", "sha256": "bc44e48acadcea02ac72779d59456e07d8600160357ceacdc258da2cbc891e23", "language": "zh", "matched_nodes": ["#PARALLEL-PLANS/p[2]"]}, {"url": "/docs/17/using-explain.html", "method": "same-major semantic node", "sha256": "610ae355c419b53a5e213a8c8e2eacbf34e4fa0ac8f6d27365071bc6d3c90278", "language": "zh", "matched_nodes": ["#USING-EXPLAIN/div[7]/p[40]", "#USING-EXPLAIN/div[7]/p[61]"]}], "language": "zh", "original_text": {"/versions/17/description/0": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/versions/17/facts/0/label": "Core node tag", "/versions/17/facts/1/label": "Structured EXPLAIN Node Type", "/versions/17/facts/2/label": "Inputs", "/versions/17/facts/2/value": "Optional child plan", "/versions/17/facts/3/label": "Output", "/versions/17/facts/3/value": "Projected tuples", "/versions/17/facts/4/label": "Executor initializer", "/versions/17/facts/5/label": "Memory mechanism", "/versions/17/tables/0/title": "EXPLAIN labels in this source build", "/versions/17/related/1/label": "Using EXPLAIN", "/versions/17/related/2/label": "Parallel plans", "/versions/17/sections/0/title": "EXPLAIN names and attributes", "/versions/17/sections/1/title": "Memory and temporary storage", "/versions/17/sections/2/title": "Parallel execution and instrumentation", "/versions/17/sections/3/title": "Same-version manual discussion", "/versions/17/sections/4/title": "Examples from this manual build", "/versions/17/sections/5/title": "Executor implementation notes", "/versions/17/sections/6/title": "EXPLAIN identity in core source", "/versions/17/memory/description": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/17/sections/0/paragraphs/0": "Structured formats use the Node Type above. Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.", "/versions/17/sections/0/paragraphs/1": "Text names recorded by this source: Result.", "/versions/17/sections/0/paragraphs/2": "Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node.", "/versions/17/sections/1/paragraphs/0": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/17/sections/2/paragraphs/0": "The source callbacks below can coordinate execution or collect worker instrumentation. Their presence is not a blanket claim that this node supports a shared parallel scan or shared state.", "/versions/17/sections/2/paragraphs/1": "Callbacks in this build: none extracted from this node implementation.", "/versions/17/sections/3/paragraphs/0": "The rows value is a little tricky because it is not the number of rows processed or scanned by the plan node, but rather the number emitted by the node. This is often less than the number scanned, as a result of filtering by any WHERE -clause conditions that are being applied at the node. Ideally the top-level rows estimate will approximate the number of rows actually returned, updated, or deleted by the query.", "/versions/17/sections/3/paragraphs/1": "Compared to regular sorts, sorting incrementally allows returning tuples before the entire result set has been sorted, which particularly enables optimizations with LIMIT queries. It may also reduce memory usage and the likelihood of spilling sorts to disk, but it comes at the cost of the increased overhead of splitting the result set into multiple sorting batches.", "/versions/17/sections/3/paragraphs/2": "In this plan, we have a nested-loop join node with two table scans as inputs, or children. The indentation of the node summary lines reflects the plan tree structure. The join's first, or \u201c outer \u201d , child is a bitmap scan similar to those we saw before. Its cost and row count are the same as we'd get from SELECT ... WHERE unique1 < 10 because we are applying the WHERE clause unique1 < 10 at that node. The t1.unique2 = t2.unique2 clause is not relevant yet, so it doesn't affect the row count of the outer scan. The nested-loop join node will run its second, or \u201c inner \u201d child once for each row obtained from the outer child. Column values from the current outer row can be plugged into the inner scan; here, the t1.unique2 value from the outer row is available, so we get a plan and costs similar to what we saw above for a simple SELECT ... WHERE t2.unique2 = constant case. (The estimated cost is actually a bit lower than what was seen above, as a result of caching that's expected to occur during the repeated index scans on t2 .) The costs of the loop node are then set on the basis of the cost of the outer scan, plus one repetition of the inner scan for each outer row (10 * 7.90, here), plus a little CPU time for join processing.", "/versions/17/sections/3/paragraphs/3": "This rather artificial example serves to illustrate a couple of points: values from the outer plan level can be passed down into a subplan (here, t.four is passed down) and the results of the sub-select are available to the outer plan. Those result values are shown by EXPLAIN with notations like ( subplan_name ).col N , which refers to the N 'th output column of the sub- SELECT .", "/versions/17/sections/3/paragraphs/4": "It is possible to check the accuracy of the planner's estimates by using EXPLAIN 's ANALYZE option. With this option, EXPLAIN actually executes the query, and then displays the true row counts and true run time accumulated within each plan node, along with the same estimates that a plain EXPLAIN shows. For example, we might get a result like this:", "/versions/17/sections/3/paragraphs/5": "Because each worker executes the parallel portion of the plan to completion, it is not possible to simply take an ordinary query plan and run it using multiple workers. Each worker would produce a full copy of the output result set, so the query would not run any faster than normal but would produce incorrect results. Instead, the parallel portion of the plan must be what is known internally to the query optimizer as a partial plan ; that is, it must be constructed so that each process that executes the plan will generate only a subset of the output rows in such a way that each required output row is guaranteed to be generated by exactly one of the cooperating processes. Generally, this means that the scan on the driving table of the query must be a parallel-aware scan.", "/versions/17/sections/5/paragraphs/0": "nodeResult.c support for constant nodes needing special code.", "/versions/17/sections/5/paragraphs/1": "Result nodes are used in queries where no relations are scanned. Examples of such queries are:", "/versions/17/sections/5/paragraphs/2": "(Remember that in an INSERT or UPDATE, we need a plan tree that generates the new rows.)", "/versions/17/sections/5/paragraphs/3": "Result nodes are also used to optimise queries with constant qualifications (ie, quals that do not depend on the scanned data), such as:", "/versions/17/sections/5/paragraphs/4": "At runtime, the Result node evaluates the constant qual once, which is shown by EXPLAIN as a One-Time Filter. If it's false, we can return an empty result set without running the controlled plan at all. If it's true, we run the controlled plan normally and pass back the results.", "/versions/17/tables/0/columns/0/label": "Text-format label", "/versions/17/tables/0/columns/1/label": "Structured node identity", "/versions/17/sections/4/blocks/0/paragraphs/0": "Example copied from the PostgreSQL 17.11 manual; it was not executed for this collection.", "/versions/17/sections/4/blocks/0/paragraphs/1": "If, in addition to not referencing any variables of the outer query, the sub- SELECT cannot return more than one row, it may instead be implemented as an initplan :"}, "fallback_fields": [], "source_language": "en", "original_snapshot_sha256": "52ea849b4a62a6ae75a19de63652bd6dc4dffbbd4cf6d725f63d91e59bab77a0"}, "evidence_kind": "source and documentation", "explain_names": ["Result"], "partial_modes": [], "comparison_data": {"node_tag": "T_Result", "strategies": [], "text_names": ["Result"], "initializer": "ExecInitResult", "partial_modes": [], "memory_mechanism": "unclassified", "parallel_callbacks": []}, "comparison_hash": "7d9e21f5e91321228505ba502e7faa5b9ebdda5ba4d71b8a9b97571a1f87b5f5", "explain_prefixes": ["Parallel", "Async"], "runtime_verified": false, "source_inventory": {"explain": "src/backend/commands/explain.c", "executor": "src/backend/executor/execProcnode.c", "implementation": "src/backend/executor/nodeResult.c"}, "parallel_callbacks": []}, "18": {"facts": [{"label": "\u6838\u5fc3\u8282\u70b9\u6807\u7b7e", "value": "T_Result"}, {"label": "\u7ed3\u6784\u5316 EXPLAIN \u8282\u70b9\u7c7b\u578b", "value": "Result"}, {"label": "\u8f93\u5165", "value": "\u53ef\u9009\u7684\u5b50\u8ba1\u5212"}, {"label": "\u8f93\u51fa", "value": "\u6295\u5f71\u540e\u7684\u5143\u7ec4"}, {"label": "\u6267\u884c\u5668\u521d\u59cb\u5316\u51fd\u6570", "value": "ExecInitResult"}, {"label": "\u5185\u5b58\u673a\u5236", "value": "unclassified"}], "memory": {"evidence": [{"url": "https://ftp.postgresql.org/pub/source/v18.6/postgresql-18.6.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "32410ec3fc47eea05d944207a7abbf25625029ca8480f5eafee927f896578b9b", "archive_sha256": "555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f"}], "mechanism": "unclassified", "description": "\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002", "source_notes": []}, "tables": [{"key": "explain-labels", "rows": [{"label": "Result", "identity": "Result"}], "title": "\u672c\u6784\u5efa\u4e2d\u7684 EXPLAIN \u6807\u7b7e", "columns": [{"key": "label", "label": "\u6587\u672c\u683c\u5f0f\u6807\u7b7e"}, {"key": "identity", "label": "\u7ed3\u6784\u5316\u8282\u70b9\u6807\u8bc6"}]}], "related": [{"url": "/wiki/sql/explain/?v=18", "label": "EXPLAIN"}, {"url": "/docs/18/using-explain.html", "label": "\u4f7f\u7528 EXPLAIN"}, {"url": "/docs/18/parallel-plans.html", "label": "\u5e76\u884c\u8ba1\u5212"}], "release": {"ref": "PostgreSQL 18.6 source archive", "label": "18.6", "major": "18", "channel": "stable", "revision": "555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f", "source_url": "https://ftp.postgresql.org/pub/source/v18.6/postgresql-18.6.tar.bz2", "source_snapshot_utc": ""}, "sources": [{"url": "https://ftp.postgresql.org/pub/source/v18.6/postgresql-18.6.tar.bz2", "line": 1379, "path": "src/backend/commands/explain.c", "label": "src/backend/commands/explain.c:1379", "sha256": "34c86d6070224a0e981efef51f79101d6d505e5874f1684ace183034bab14bb4", "archive_sha256": "555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f"}, {"url": "https://ftp.postgresql.org/pub/source/v18.6/postgresql-18.6.tar.bz2", "line": 166, "path": "src/backend/executor/execProcnode.c", "label": "src/backend/executor/execProcnode.c:166", "sha256": "f8a06a3f539077249b20664b2812433db6d7bd12b2c0ca633525db43d06f112a", "archive_sha256": "555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f"}, {"url": "https://ftp.postgresql.org/pub/source/v18.6/postgresql-18.6.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "32410ec3fc47eea05d944207a7abbf25625029ca8480f5eafee927f896578b9b", "archive_sha256": "555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f"}, {"url": "https://ftp.postgresql.org/pub/source/v18.6/postgresql-18.6.tar.bz2", "path": "src/include/nodes/plannodes.h", "label": "src/include/nodes/plannodes.h", "sha256": "52422b327a8049fbbb20d8b96008a0fc0a6fafa60f7eff3c695d5b2e83830120", "archive_sha256": "555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f"}, {"url": "https://pg.center/docs/18/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 18.6 \u00b7 using-explain", "sha256": "60040c30180093418a0affe56dd27dff9df2504b705b38039589e458bf5c31ed", "language": "en", "original_url": "/docs/18/using-explain.html#USING-EXPLAIN-BASICS"}, {"url": "https://pg.center/docs/18/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 18.6 \u00b7 using-explain", "sha256": "60040c30180093418a0affe56dd27dff9df2504b705b38039589e458bf5c31ed", "language": "en", "original_url": "/docs/18/using-explain.html#USING-EXPLAIN-ANALYZE"}, {"url": "https://pg.center/docs/18/parallel-plans.html#PARALLEL-PLANS", "path": "parallel-plans.html", "label": "PostgreSQL 18.6 \u00b7 parallel-plans", "sha256": "62207d207bead82b01b59dc119c4f95856f08655cc11d4699a05a40867ed2070", "language": "en", "original_url": "/docs/18/parallel-plans.html#PARALLEL-PLANS"}], "node_tag": "T_Result", "sections": [{"title": "EXPLAIN \u540d\u79f0\u4e0e\u5c5e\u6027", "paragraphs": ["\u7ed3\u6784\u5316\u683c\u5f0f\u4f7f\u7528\u4e0a\u8ff0 Node Type\u3002\u6587\u672c\u683c\u5f0f\u540d\u79f0\u8fd8\u53ef\u80fd\u5305\u542b\u64cd\u4f5c\u3001\u7b56\u7565\u3001\u8fde\u63a5\u7c7b\u578b\u3001\u626b\u63cf\u65b9\u5411\u6216\u805a\u5408\u9636\u6bb5\u5c5e\u6027\u3002", "\u6b64\u6e90\u7801\u8bb0\u5f55\u7684\u6587\u672c\u540d\u79f0\uff1aResult.", "\u5e76\u884c\u611f\u77e5\u4e0e\u5e76\u884c\u5b89\u5168\u662f\u4e0d\u540c\u7684\u8ba1\u5212\u5c5e\u6027\u3002\u5728\u5e76\u884c\u5de5\u4f5c\u8fdb\u7a0b\u5185\u8fd0\u884c\u7684\u8282\u70b9\u4e0d\u4e00\u5b9a\u662f\u5e76\u884c\u611f\u77e5\u8282\u70b9\u3002"]}, {"title": "\u5185\u5b58\u4e0e\u4e34\u65f6\u5b58\u50a8", "paragraphs": ["\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002"]}, {"title": "\u5e76\u884c\u6267\u884c\u4e0e\u8fd0\u884c\u4fe1\u606f\u91c7\u96c6", "paragraphs": ["\u4ee5\u4e0b\u6e90\u7801\u56de\u8c03\u53ef\u4ee5\u534f\u8c03\u6267\u884c\u6216\u6536\u96c6\u5de5\u4f5c\u8fdb\u7a0b\u7684\u6d4b\u91cf\u6570\u636e\u3002\u56de\u8c03\u5b58\u5728\u4e0d\u4ee3\u8868\u8be5\u8282\u70b9\u666e\u904d\u652f\u6301\u5171\u4eab\u5e76\u884c\u626b\u63cf\u6216\u5171\u4eab\u72b6\u6001\u3002", "\u6b64\u6784\u5efa\u7684\u56de\u8c03\uff1anone extracted from this node implementation."]}, {"title": "\u540c\u7248\u672c\u624b\u518c\u8bf4\u660e", "paragraphs": ["rows \u5bb9\u6613\u4ee4\u4eba\u8bef\u89e3\uff1a\u5b83\u8868\u793a\u8282\u70b9\u8f93\u51fa\u7684\u884c\u6570\uff0c\u800c\u4e0d\u662f\u5904\u7406\u6216\u626b\u63cf\u7684\u884c\u6570\u3002\u8282\u70b9\u5e94\u7528 WHERE \u6761\u4ef6\u7b5b\u9009\u540e\uff0c\u8f93\u51fa\u884c\u6570\u901a\u5e38\u5c0f\u4e8e\u626b\u63cf\u884c\u6570\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u9876\u5c42 rows \u4f30\u8ba1\u5e94\u63a5\u8fd1\u67e5\u8be2\u5b9e\u9645\u8fd4\u56de\u3001\u66f4\u65b0\u6216\u5220\u9664\u7684\u884c\u6570\u3002", "\u4e0e\u666e\u901a\u6392\u5e8f\u76f8\u6bd4\uff0c\u589e\u91cf\u6392\u5e8f\u53ef\u5728\u6574\u4e2a\u7ed3\u679c\u96c6\u5c1a\u672a\u6392\u5b8c\u65f6\u5c31\u8fd4\u56de\u5143\u7ec4\uff0c\u5c24\u5176\u6709\u5229\u4e8e\u4f18\u5316\u5e26 LIMIT \u7684\u67e5\u8be2\u3002\u5b83\u8fd8\u53ef\u80fd\u51cf\u5c11\u5185\u5b58\u7528\u91cf\u548c\u6392\u5e8f\u6ea2\u5199\u78c1\u76d8\u7684\u6982\u7387\uff0c\u4f46\u4ee3\u4ef7\u662f\u5c06\u7ed3\u679c\u96c6\u62c6\u6210\u591a\u4e2a\u6392\u5e8f\u6279\u6b21\u6240\u5e26\u6765\u7684\u989d\u5916\u5f00\u9500\u3002", "\u5728\u8fd9\u4e2a\u8ba1\u5212\u4e2d\uff0c\u6709\u4e00\u4e2a\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\uff0c\u5b83\u7684\u4e24\u4e2a\u8f93\u5165\uff0c\u4e5f\u5c31\u662f\u4e24\u4e2a\u5b50\u8282\u70b9\uff0c\u90fd\u662f\u8868\u626b\u63cf\u3002\u8282\u70b9\u6458\u8981\u884c\u7684\u7f29\u8fdb\u53cd\u6620\u4e86\u8ba1\u5212\u6811\u7ed3\u6784\u3002\u8fde\u63a5\u7684\u7b2c\u4e00\u4e2a\u5b50\u8282\u70b9\uff0c\u4e5f\u5c31\u662f \u201c \u5916\u4fa7 \u201d \u5b50\u8282\u70b9\uff0c\u662f\u4e00\u4e2a\u4e0e\u524d\u9762\u89c1\u8fc7\u7684\u4f4d\u56fe\u626b\u63cf\u7c7b\u4f3c\u7684\u8282\u70b9\u3002\u5b83\u7684\u4ee3\u4ef7\u548c\u884c\u8ba1\u6570\u4e0e SELECT ... WHERE unique1 < 10 \u5f97\u5230\u7684\u7ed3\u679c\u76f8\u540c\uff0c\u56e0\u4e3a WHERE \u5b50\u53e5 unique1 < 10 \u6b63\u662f\u5728\u8be5\u8282\u70b9\u4e0a\u5e94\u7528\u7684\u3002 t1.unique2 = t2.unique2 \u5b50\u53e5\u6b64\u65f6\u8fd8\u65e0\u5173\uff0c\u56e0\u6b64\u4e0d\u4f1a\u5f71\u54cd\u5916\u4fa7\u626b\u63cf\u7684\u884c\u8ba1\u6570\u3002\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\u4f1a\u5bf9\u4ece\u5916\u4fa7\u5b50\u8282\u70b9\u5f97\u5230\u7684\u6bcf\u4e00\u884c\u6267\u884c\u4e00\u6b21\u7b2c\u4e8c\u4e2a\uff0c\u4e5f\u5c31\u662f \u201c \u5185\u4fa7 \u201d \u5b50\u8282\u70b9\u3002\u5f53\u524d\u5916\u4fa7\u884c\u4e2d\u7684\u5217\u503c\u53ef\u4ee5\u4ee3\u5165\u5185\u4fa7\u626b\u63cf\uff1b\u8fd9\u91cc\u5916\u4fa7\u884c\u7684 t1.unique2 \u503c\u53ef\u7528\uff0c\u56e0\u6b64\u5f97\u5230\u7684\u8ba1\u5212\u548c\u4ee3\u4ef7\u4e0e\u524d\u9762\u770b\u5230\u7684\u7b80\u5355 SELECT ... WHERE t2.unique2 = constant \u60c5\u5f62\u7c7b\u4f3c\u3002\uff08\u7531\u4e8e\u9884\u671f\u5728\u5bf9 t2 \u53cd\u590d\u6267\u884c\u7d22\u5f15\u626b\u63cf\u671f\u95f4\u4f1a\u53d1\u751f\u7f13\u5b58\u547d\u4e2d\uff0c\u4f30\u8ba1\u4ee3\u4ef7\u5b9e\u9645\u4e0a\u6bd4\u524d\u9762\u770b\u5230\u7684\u7565\u4f4e\u4e00\u4e9b\u3002\uff09\u968f\u540e\uff0c\u5faa\u73af\u8282\u70b9\u7684\u4ee3\u4ef7\u5efa\u7acb\u5728\u5916\u4fa7\u626b\u63cf\u4ee3\u4ef7\u4e4b\u4e0a\uff0c\u518d\u52a0\u4e0a\u6bcf\u4e2a\u5916\u4fa7\u884c\u90fd\u8981\u6267\u884c\u4e00\u6b21\u5185\u4fa7\u626b\u63cf\u7684\u4ee3\u4ef7\uff08\u8fd9\u91cc\u662f 10 * 7.90\uff09\uff0c\u4ee5\u53ca\u5c11\u91cf\u8fde\u63a5\u5904\u7406\u7684 CPU \u65f6\u95f4\u3002", "\u8fd9\u4e2a\u523b\u610f\u6784\u9020\u7684\u793a\u4f8b\u8bf4\u660e\u4e86\u4e24\u70b9\uff1a\u5916\u5c42\u8ba1\u5212\u7684\u503c\u53ef\u4f20\u5165\u5b50\u8ba1\u5212\uff08\u8fd9\u91cc\u4f20\u5165 t.four\uff09\uff0c\u5b50\u67e5\u8be2\u7ed3\u679c\u4e5f\u53ef\u4f9b\u5916\u5c42\u8ba1\u5212\u4f7f\u7528\u3002EXPLAIN \u7528 (subplan_name).col N \u4e00\u7c7b\u8bb0\u53f7\u663e\u793a\u8fd9\u4e9b\u7ed3\u679c\u503c\uff0c\u8868\u793a\u5b50 SELECT \u7684\u7b2c N \u4e2a\u8f93\u51fa\u5217\u3002", "\u53ef\u4f7f\u7528 EXPLAIN \u7684 ANALYZE \u9009\u9879\u68c0\u67e5\u89c4\u5212\u5668\u4f30\u7b97\u662f\u5426\u51c6\u786e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\uff0cEXPLAIN \u4f1a\u5b9e\u9645\u6267\u884c\u67e5\u8be2\uff0c\u7136\u540e\u663e\u793a\u6bcf\u4e2a\u8ba1\u5212\u8282\u70b9\u7d2f\u8ba1\u7684\u771f\u5b9e\u884c\u6570\u548c\u771f\u5b9e\u8fd0\u884c\u65f6\u95f4\uff0c\u4ee5\u53ca\u666e\u901a EXPLAIN \u6240\u663e\u793a\u7684\u4f30\u7b97\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u80fd\u5f97\u5230\u5982\u4e0b\u7ed3\u679c\uff1a", "\u7531\u4e8e\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u5c06\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u6267\u884c\u5230\u5e95\uff0c\u56e0\u6b64\u4e0d\u80fd\u7b80\u5355\u5730\u62ff\u4e00\u4e2a\u666e\u901a\u67e5\u8be2\u8ba1\u5212\u5e76\u8ba9\u591a\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u540c\u65f6\u8fd0\u884c\u3002\u90a3\u6837\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u751f\u6210\u5b8c\u6574\u8f93\u51fa\u7ed3\u679c\u96c6\u7684\u4e00\u4efd\u526f\u672c\uff0c\u6240\u4ee5\u67e5\u8be2\u4e0d\u4ec5\u4e0d\u4f1a\u6bd4\u5e73\u5e38\u66f4\u5feb\uff0c\u53cd\u800c\u4f1a\u4ea7\u751f\u9519\u8bef\u7ed3\u679c\u3002\u76f8\u53cd\uff0c\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u5fc5\u987b\u662f\u67e5\u8be2\u4f18\u5316\u5668\u5185\u90e8\u6240\u8bf4\u7684 \u90e8\u5206\u8ba1\u5212 \uff1b\u4e5f\u5c31\u662f\u8bf4\uff0c\u5b83\u5fc5\u987b\u88ab\u6784\u9020\u4e3a\u4f7f\u6267\u884c\u8be5\u8ba1\u5212\u7684\u6bcf\u4e2a\u8fdb\u7a0b\u53ea\u751f\u6210\u8f93\u51fa\u884c\u7684\u4e00\u4e2a\u5b50\u96c6\uff0c\u5e76\u4e14\u4fdd\u8bc1\u6bcf\u4e00\u6761\u6240\u9700\u8f93\u51fa\u884c\u90fd\u6070\u597d\u7531\u67d0\u4e2a\u534f\u4f5c\u8fdb\u7a0b\u751f\u6210\u4e00\u6b21\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u8fd9\u610f\u5473\u7740\u67e5\u8be2\u9a71\u52a8\u8868\u4e0a\u7684\u626b\u63cf\u5fc5\u987b\u662f\u5e76\u884c\u611f\u77e5\u626b\u63cf\u3002"]}, {"title": "\u672c\u7248\u624b\u518c\u4e2d\u7684\u793a\u4f8b", "blocks": [{"code": "EXPLAIN VERBOSE SELECT unique1\nFROM tenk1 t1 WHERE t1.ten = (SELECT (random() * 10)::integer);\n\n                             QUERY PLAN\n--------------------------------------------------------------------\n Seq Scan on public.tenk1 t1  (cost=0.02..470.02 rows=1000 width=4)\n   Output: t1.unique1\n   Filter: (t1.ten = (InitPlan 1).col1)\n   InitPlan 1\n     ->  Result  (cost=0.00..0.02 rows=1 width=4)\n           Output: ((random() * '10'::double precision))::integer", "source": {"url": "/docs/18/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 18.6 \u00b7 using-explain", "sha256": "60040c30180093418a0affe56dd27dff9df2504b705b38039589e458bf5c31ed"}, "paragraphs": ["\u793a\u4f8b\u6458\u81ea PostgreSQL 18.6 \u624b\u518c\uff1b\u672c\u767e\u79d1\u672a\u5b9e\u9645\u6267\u884c\u6b64\u793a\u4f8b\u3002", "\u5982\u679c\u5b50 SELECT \u4e0d\u4ec5\u4e0d\u5f15\u7528\u5916\u5c42\u67e5\u8be2\u7684\u4efb\u4f55\u53d8\u91cf\uff0c\u800c\u4e14\u6700\u591a\u53ea\u4f1a\u8fd4\u56de\u4e00\u884c\uff0c\u90a3\u4e48\u5b83\u8fd8\u53ef\u80fd\u88ab\u5b9e\u73b0\u6210\u4e00\u4e2a \u521d\u59cb\u8ba1\u5212 \uff1a"]}]}, {"title": "\u6267\u884c\u5668\u5b9e\u73b0\u8bf4\u660e", "paragraphs": ["nodeResult.c\uff1a\u652f\u6301\u9700\u8981\u7279\u6b8a\u4ee3\u7801\u7684\u5e38\u91cf\u8282\u70b9\u3002", "Result \u8282\u70b9\u7528\u4e8e\u4e0d\u626b\u63cf\u4efb\u4f55\u5173\u7cfb\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\uff08\u8bf7\u8bb0\u4f4f\uff0cINSERT \u6216 UPDATE \u9700\u8981\u4e00\u68f5\u751f\u6210\u65b0\u884c\u7684\u8ba1\u5212\u6811\u3002\uff09", "Result \u8282\u70b9\u4e5f\u7528\u4e8e\u4f18\u5316\u5e26\u6709\u5e38\u91cf\u6761\u4ef6\uff08\u5373\u4e0d\u4f9d\u8d56\u626b\u63cf\u6570\u636e\u7684\u6761\u4ef6\uff09\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\u8fd0\u884c\u65f6\uff0cResult \u8282\u70b9\u53ea\u8ba1\u7b97\u4e00\u6b21\u5e38\u91cf\u6761\u4ef6\uff0cEXPLAIN \u5c06\u5176\u663e\u793a\u4e3a One-Time Filter\u3002\u5982\u679c\u6761\u4ef6\u4e3a\u5047\uff0c\u65e0\u9700\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u4fbf\u53ef\u8fd4\u56de\u7a7a\u7ed3\u679c\u96c6\uff1b\u5982\u679c\u4e3a\u771f\uff0c\u5219\u6b63\u5e38\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u5e76\u4f20\u56de\u7ed3\u679c\u3002"]}, {"code": "case T_Result:\n\t\t\tpname = sname = \"Result\";\n\t\t\tbreak;", "title": "\u6838\u5fc3\u6e90\u7801\u4e2d\u7684 EXPLAIN \u6807\u8bc6"}], "strategies": [], "description": ["\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002"], "localization": {"status": "complete", "sources": [{"url": "/docs/18/parallel-plans.html", "method": "same-major semantic node", "sha256": "7fa104623c0b4cd22acf0929e40518fbed8fe368af3e3b124cf693bd7ab69f0c", "language": "zh", "matched_nodes": ["#PARALLEL-PLANS/p[2]"]}, {"url": "/docs/18/using-explain.html", "method": "same-major semantic node", "sha256": "b8835ec9adbc70ec150667a6b5443f8d298222dc0cc8c2bd1abb1c1d64895904", "language": "zh", "matched_nodes": ["#USING-EXPLAIN/div[7]/p[40]", "#USING-EXPLAIN/div[7]/p[64]"]}], "language": "zh", "original_text": {"/versions/18/description/0": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/versions/18/facts/0/label": "Core node tag", "/versions/18/facts/1/label": "Structured EXPLAIN Node Type", "/versions/18/facts/2/label": "Inputs", "/versions/18/facts/2/value": "Optional child plan", "/versions/18/facts/3/label": "Output", "/versions/18/facts/3/value": "Projected tuples", "/versions/18/facts/4/label": "Executor initializer", "/versions/18/facts/5/label": "Memory mechanism", "/versions/18/tables/0/title": "EXPLAIN labels in this source build", "/versions/18/related/1/label": "Using EXPLAIN", "/versions/18/related/2/label": "Parallel plans", "/versions/18/sections/0/title": "EXPLAIN names and attributes", "/versions/18/sections/1/title": "Memory and temporary storage", "/versions/18/sections/2/title": "Parallel execution and instrumentation", "/versions/18/sections/3/title": "Same-version manual discussion", "/versions/18/sections/4/title": "Examples from this manual build", "/versions/18/sections/5/title": "Executor implementation notes", "/versions/18/sections/6/title": "EXPLAIN identity in core source", "/versions/18/memory/description": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/18/sections/0/paragraphs/0": "Structured formats use the Node Type above. Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.", "/versions/18/sections/0/paragraphs/1": "Text names recorded by this source: Result.", "/versions/18/sections/0/paragraphs/2": "Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node.", "/versions/18/sections/1/paragraphs/0": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/18/sections/2/paragraphs/0": "The source callbacks below can coordinate execution or collect worker instrumentation. Their presence is not a blanket claim that this node supports a shared parallel scan or shared state.", "/versions/18/sections/2/paragraphs/1": "Callbacks in this build: none extracted from this node implementation.", "/versions/18/sections/3/paragraphs/0": "The rows value is a little tricky because it is not the number of rows processed or scanned by the plan node, but rather the number emitted by the node. This is often less than the number scanned, as a result of filtering by any WHERE -clause conditions that are being applied at the node. Ideally the top-level rows estimate will approximate the number of rows actually returned, updated, or deleted by the query.", "/versions/18/sections/3/paragraphs/1": "Compared to regular sorts, sorting incrementally allows returning tuples before the entire result set has been sorted, which particularly enables optimizations with LIMIT queries. It may also reduce memory usage and the likelihood of spilling sorts to disk, but it comes at the cost of the increased overhead of splitting the result set into multiple sorting batches.", "/versions/18/sections/3/paragraphs/2": "In this plan, we have a nested-loop join node with two table scans as inputs, or children. The indentation of the node summary lines reflects the plan tree structure. The join's first, or \u201c outer \u201d , child is a bitmap scan similar to those we saw before. Its cost and row count are the same as we'd get from SELECT ... WHERE unique1 < 10 because we are applying the WHERE clause unique1 < 10 at that node. The t1.unique2 = t2.unique2 clause is not relevant yet, so it doesn't affect the row count of the outer scan. The nested-loop join node will run its second, or \u201c inner \u201d child once for each row obtained from the outer child. Column values from the current outer row can be plugged into the inner scan; here, the t1.unique2 value from the outer row is available, so we get a plan and costs similar to what we saw above for a simple SELECT ... WHERE t2.unique2 = constant case. (The estimated cost is actually a bit lower than what was seen above, as a result of caching that's expected to occur during the repeated index scans on t2 .) The costs of the loop node are then set on the basis of the cost of the outer scan, plus one repetition of the inner scan for each outer row (10 * 7.90, here), plus a little CPU time for join processing.", "/versions/18/sections/3/paragraphs/3": "This rather artificial example serves to illustrate a couple of points: values from the outer plan level can be passed down into a subplan (here, t.four is passed down) and the results of the sub-select are available to the outer plan. Those result values are shown by EXPLAIN with notations like ( subplan_name ).col N , which refers to the N 'th output column of the sub- SELECT .", "/versions/18/sections/3/paragraphs/4": "It is possible to check the accuracy of the planner's estimates by using EXPLAIN 's ANALYZE option. With this option, EXPLAIN actually executes the query, and then displays the true row counts and true run time accumulated within each plan node, along with the same estimates that a plain EXPLAIN shows. For example, we might get a result like this:", "/versions/18/sections/3/paragraphs/5": "Because each worker executes the parallel portion of the plan to completion, it is not possible to simply take an ordinary query plan and run it using multiple workers. Each worker would produce a full copy of the output result set, so the query would not run any faster than normal but would produce incorrect results. Instead, the parallel portion of the plan must be what is known internally to the query optimizer as a partial plan ; that is, it must be constructed so that each process that executes the plan will generate only a subset of the output rows in such a way that each required output row is guaranteed to be generated by exactly one of the cooperating processes. Generally, this means that the scan on the driving table of the query must be a parallel-aware scan.", "/versions/18/sections/5/paragraphs/0": "nodeResult.c support for constant nodes needing special code.", "/versions/18/sections/5/paragraphs/1": "Result nodes are used in queries where no relations are scanned. Examples of such queries are:", "/versions/18/sections/5/paragraphs/2": "(Remember that in an INSERT or UPDATE, we need a plan tree that generates the new rows.)", "/versions/18/sections/5/paragraphs/3": "Result nodes are also used to optimise queries with constant qualifications (ie, quals that do not depend on the scanned data), such as:", "/versions/18/sections/5/paragraphs/4": "At runtime, the Result node evaluates the constant qual once, which is shown by EXPLAIN as a One-Time Filter. If it's false, we can return an empty result set without running the controlled plan at all. If it's true, we run the controlled plan normally and pass back the results.", "/versions/18/tables/0/columns/0/label": "Text-format label", "/versions/18/tables/0/columns/1/label": "Structured node identity", "/versions/18/sections/4/blocks/0/paragraphs/0": "Example copied from the PostgreSQL 18.6 manual; it was not executed for this collection.", "/versions/18/sections/4/blocks/0/paragraphs/1": "If, in addition to not referencing any variables of the outer query, the sub- SELECT cannot return more than one row, it may instead be implemented as an initplan :"}, "fallback_fields": [], "source_language": "en", "original_snapshot_sha256": "083472e89b0d77b0d449941552fb54b7f3e90678fbd15e8c731429116e63db35"}, "evidence_kind": "source and documentation", "explain_names": ["Result"], "partial_modes": [], "comparison_data": {"node_tag": "T_Result", "strategies": [], "text_names": ["Result"], "initializer": "ExecInitResult", "partial_modes": [], "memory_mechanism": "unclassified", "parallel_callbacks": []}, "comparison_hash": "7d9e21f5e91321228505ba502e7faa5b9ebdda5ba4d71b8a9b97571a1f87b5f5", "explain_prefixes": ["Parallel", "Async"], "runtime_verified": false, "source_inventory": {"explain": "src/backend/commands/explain.c", "executor": "src/backend/executor/execProcnode.c", "implementation": "src/backend/executor/nodeResult.c"}, "parallel_callbacks": []}, "19": {"facts": [{"label": "\u6838\u5fc3\u8282\u70b9\u6807\u7b7e", "value": "T_Result"}, {"label": "\u7ed3\u6784\u5316 EXPLAIN \u8282\u70b9\u7c7b\u578b", "value": "Result"}, {"label": "\u8f93\u5165", "value": "\u53ef\u9009\u7684\u5b50\u8ba1\u5212"}, {"label": "\u8f93\u51fa", "value": "\u6295\u5f71\u540e\u7684\u5143\u7ec4"}, {"label": "\u6267\u884c\u5668\u521d\u59cb\u5316\u51fd\u6570", "value": "ExecInitResult"}, {"label": "\u5185\u5b58\u673a\u5236", "value": "unclassified"}], "memory": {"evidence": [{"url": "https://ftp.postgresql.org/pub/source/v19beta4/postgresql-19beta4.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "3de5782280c9d96398da2c356e5f601043885f33542057bcc1c5ba61a5ad4ca3", "archive_sha256": "83157ee9c599d03b2f7a3d73ef3a56ec24e0e79cc2b3501a64d1364f56398c86"}], "mechanism": "unclassified", "description": "\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002", "source_notes": []}, "tables": [{"key": "explain-labels", "rows": [{"label": "Result", "identity": "Result"}], "title": "\u672c\u6784\u5efa\u4e2d\u7684 EXPLAIN \u6807\u7b7e", "columns": [{"key": "label", "label": "\u6587\u672c\u683c\u5f0f\u6807\u7b7e"}, {"key": "identity", "label": "\u7ed3\u6784\u5316\u8282\u70b9\u6807\u8bc6"}]}], "related": [{"url": "/wiki/sql/explain/?v=19", "label": "EXPLAIN"}, {"url": "/docs/19/using-explain.html", "label": "\u4f7f\u7528 EXPLAIN"}, {"url": "/docs/19/parallel-plans.html", "label": "\u5e76\u884c\u8ba1\u5212"}], "release": {"ref": "PostgreSQL 19beta4 source archive", "label": "19beta4", "major": "19", "channel": "preview", "revision": "83157ee9c599d03b2f7a3d73ef3a56ec24e0e79cc2b3501a64d1364f56398c86", "source_url": "https://ftp.postgresql.org/pub/source/v19beta4/postgresql-19beta4.tar.bz2", "source_snapshot_utc": ""}, "sources": [{"url": "https://ftp.postgresql.org/pub/source/v19beta4/postgresql-19beta4.tar.bz2", "line": 1391, "path": "src/backend/commands/explain.c", "label": "src/backend/commands/explain.c:1391", "sha256": "8b115b1c194a4b54ae630209a741e293b1df49a9052f10b2de9ca092a48998e3", "archive_sha256": "83157ee9c599d03b2f7a3d73ef3a56ec24e0e79cc2b3501a64d1364f56398c86"}, {"url": "https://ftp.postgresql.org/pub/source/v19beta4/postgresql-19beta4.tar.bz2", "line": 166, "path": "src/backend/executor/execProcnode.c", "label": "src/backend/executor/execProcnode.c:166", "sha256": "5e39b2037bed672da55104229ecc32da5abde44c26bcad01479edcfa044d09ed", "archive_sha256": "83157ee9c599d03b2f7a3d73ef3a56ec24e0e79cc2b3501a64d1364f56398c86"}, {"url": "https://ftp.postgresql.org/pub/source/v19beta4/postgresql-19beta4.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "3de5782280c9d96398da2c356e5f601043885f33542057bcc1c5ba61a5ad4ca3", "archive_sha256": "83157ee9c599d03b2f7a3d73ef3a56ec24e0e79cc2b3501a64d1364f56398c86"}, {"url": "https://ftp.postgresql.org/pub/source/v19beta4/postgresql-19beta4.tar.bz2", "path": "src/include/nodes/plannodes.h", "label": "src/include/nodes/plannodes.h", "sha256": "1c65d5d6b6c81c71531685843647869bcae630779d815a5036b06e070c6c06c7", "archive_sha256": "83157ee9c599d03b2f7a3d73ef3a56ec24e0e79cc2b3501a64d1364f56398c86"}, {"url": "https://pg.center/docs/19/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 19beta4 \u00b7 using-explain", "sha256": "52f111fbd213e2200146319d01a9dcc2ea90001617d2a28edc52f7954c2dd70b", "language": "en", "original_url": "/docs/19/using-explain.html#USING-EXPLAIN-BASICS"}, {"url": "https://pg.center/docs/19/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 19beta4 \u00b7 using-explain", "sha256": "52f111fbd213e2200146319d01a9dcc2ea90001617d2a28edc52f7954c2dd70b", "language": "en", "original_url": "/docs/19/using-explain.html#USING-EXPLAIN-ANALYZE"}, {"url": "https://pg.center/docs/19/parallel-plans.html#PARALLEL-PLANS", "path": "parallel-plans.html", "label": "PostgreSQL 19beta4 \u00b7 parallel-plans", "sha256": "f99fee3456a48a5ce2c399d6b35ab93183c2c9012e8ed60c53c0c253f79c3756", "language": "en", "original_url": "/docs/19/parallel-plans.html#PARALLEL-PLANS"}], "node_tag": "T_Result", "sections": [{"title": "EXPLAIN \u540d\u79f0\u4e0e\u5c5e\u6027", "paragraphs": ["\u7ed3\u6784\u5316\u683c\u5f0f\u4f7f\u7528\u4e0a\u8ff0 Node Type\u3002\u6587\u672c\u683c\u5f0f\u540d\u79f0\u8fd8\u53ef\u80fd\u5305\u542b\u64cd\u4f5c\u3001\u7b56\u7565\u3001\u8fde\u63a5\u7c7b\u578b\u3001\u626b\u63cf\u65b9\u5411\u6216\u805a\u5408\u9636\u6bb5\u5c5e\u6027\u3002", "\u6b64\u6e90\u7801\u8bb0\u5f55\u7684\u6587\u672c\u540d\u79f0\uff1aResult.", "\u5e76\u884c\u611f\u77e5\u4e0e\u5e76\u884c\u5b89\u5168\u662f\u4e0d\u540c\u7684\u8ba1\u5212\u5c5e\u6027\u3002\u5728\u5e76\u884c\u5de5\u4f5c\u8fdb\u7a0b\u5185\u8fd0\u884c\u7684\u8282\u70b9\u4e0d\u4e00\u5b9a\u662f\u5e76\u884c\u611f\u77e5\u8282\u70b9\u3002"]}, {"title": "\u5185\u5b58\u4e0e\u4e34\u65f6\u5b58\u50a8", "paragraphs": ["\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002"]}, {"title": "\u5e76\u884c\u6267\u884c\u4e0e\u8fd0\u884c\u4fe1\u606f\u91c7\u96c6", "paragraphs": ["\u4ee5\u4e0b\u6e90\u7801\u56de\u8c03\u53ef\u4ee5\u534f\u8c03\u6267\u884c\u6216\u6536\u96c6\u5de5\u4f5c\u8fdb\u7a0b\u7684\u6d4b\u91cf\u6570\u636e\u3002\u56de\u8c03\u5b58\u5728\u4e0d\u4ee3\u8868\u8be5\u8282\u70b9\u666e\u904d\u652f\u6301\u5171\u4eab\u5e76\u884c\u626b\u63cf\u6216\u5171\u4eab\u72b6\u6001\u3002", "\u6b64\u6784\u5efa\u7684\u56de\u8c03\uff1anone extracted from this node implementation."]}, {"title": "\u540c\u7248\u672c\u624b\u518c\u8bf4\u660e", "paragraphs": ["rows \u5bb9\u6613\u4ee4\u4eba\u8bef\u89e3\uff1a\u5b83\u8868\u793a\u8282\u70b9\u8f93\u51fa\u7684\u884c\u6570\uff0c\u800c\u4e0d\u662f\u5904\u7406\u6216\u626b\u63cf\u7684\u884c\u6570\u3002\u8282\u70b9\u5e94\u7528 WHERE \u6761\u4ef6\u7b5b\u9009\u540e\uff0c\u8f93\u51fa\u884c\u6570\u901a\u5e38\u5c0f\u4e8e\u626b\u63cf\u884c\u6570\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u9876\u5c42 rows \u4f30\u8ba1\u5e94\u63a5\u8fd1\u67e5\u8be2\u5b9e\u9645\u8fd4\u56de\u3001\u66f4\u65b0\u6216\u5220\u9664\u7684\u884c\u6570\u3002", "\u4e0e\u666e\u901a\u6392\u5e8f\u76f8\u6bd4\uff0c\u589e\u91cf\u6392\u5e8f\u53ef\u5728\u6574\u4e2a\u7ed3\u679c\u96c6\u5c1a\u672a\u6392\u5b8c\u65f6\u5c31\u8fd4\u56de\u5143\u7ec4\uff0c\u5c24\u5176\u6709\u5229\u4e8e\u4f18\u5316\u5e26 LIMIT \u7684\u67e5\u8be2\u3002\u5b83\u8fd8\u53ef\u80fd\u51cf\u5c11\u5185\u5b58\u7528\u91cf\u548c\u6392\u5e8f\u6ea2\u5199\u78c1\u76d8\u7684\u6982\u7387\uff0c\u4f46\u4ee3\u4ef7\u662f\u5c06\u7ed3\u679c\u96c6\u62c6\u6210\u591a\u4e2a\u6392\u5e8f\u6279\u6b21\u6240\u5e26\u6765\u7684\u989d\u5916\u5f00\u9500\u3002", "\u5728\u8fd9\u4e2a\u8ba1\u5212\u4e2d\uff0c\u6709\u4e00\u4e2a\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\uff0c\u5b83\u7684\u4e24\u4e2a\u8f93\u5165\uff0c\u4e5f\u5c31\u662f\u4e24\u4e2a\u5b50\u8282\u70b9\uff0c\u90fd\u662f\u8868\u626b\u63cf\u3002\u8282\u70b9\u6458\u8981\u884c\u7684\u7f29\u8fdb\u53cd\u6620\u4e86\u8ba1\u5212\u6811\u7ed3\u6784\u3002\u8fde\u63a5\u7684\u7b2c\u4e00\u4e2a\u5b50\u8282\u70b9\uff0c\u4e5f\u5c31\u662f \u201c \u5916\u4fa7 \u201d \u5b50\u8282\u70b9\uff0c\u662f\u4e00\u4e2a\u4e0e\u524d\u9762\u89c1\u8fc7\u7684\u4f4d\u56fe\u626b\u63cf\u7c7b\u4f3c\u7684\u8282\u70b9\u3002\u5b83\u7684\u4ee3\u4ef7\u548c\u884c\u8ba1\u6570\u4e0e SELECT ... WHERE unique1 < 10 \u5f97\u5230\u7684\u7ed3\u679c\u76f8\u540c\uff0c\u56e0\u4e3a WHERE \u5b50\u53e5 unique1 < 10 \u6b63\u662f\u5728\u8be5\u8282\u70b9\u4e0a\u5e94\u7528\u7684\u3002 t1.unique2 = t2.unique2 \u5b50\u53e5\u6b64\u65f6\u8fd8\u65e0\u5173\uff0c\u56e0\u6b64\u4e0d\u4f1a\u5f71\u54cd\u5916\u4fa7\u626b\u63cf\u7684\u884c\u8ba1\u6570\u3002\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\u4f1a\u5bf9\u4ece\u5916\u4fa7\u5b50\u8282\u70b9\u5f97\u5230\u7684\u6bcf\u4e00\u884c\u6267\u884c\u4e00\u6b21\u7b2c\u4e8c\u4e2a\uff0c\u4e5f\u5c31\u662f \u201c \u5185\u4fa7 \u201d \u5b50\u8282\u70b9\u3002\u5f53\u524d\u5916\u4fa7\u884c\u4e2d\u7684\u5217\u503c\u53ef\u4ee5\u4ee3\u5165\u5185\u4fa7\u626b\u63cf\uff1b\u8fd9\u91cc\u5916\u4fa7\u884c\u7684 t1.unique2 \u503c\u53ef\u7528\uff0c\u56e0\u6b64\u5f97\u5230\u7684\u8ba1\u5212\u548c\u4ee3\u4ef7\u4e0e\u524d\u9762\u770b\u5230\u7684\u7b80\u5355 SELECT ... WHERE t2.unique2 = constant \u60c5\u5f62\u7c7b\u4f3c\u3002\uff08\u7531\u4e8e\u9884\u671f\u5728\u5bf9 t2 \u53cd\u590d\u6267\u884c\u7d22\u5f15\u626b\u63cf\u671f\u95f4\u4f1a\u53d1\u751f\u7f13\u5b58\u547d\u4e2d\uff0c\u4f30\u8ba1\u4ee3\u4ef7\u5b9e\u9645\u4e0a\u6bd4\u524d\u9762\u770b\u5230\u7684\u7565\u4f4e\u4e00\u4e9b\u3002\uff09\u968f\u540e\uff0c\u5faa\u73af\u8282\u70b9\u7684\u4ee3\u4ef7\u5efa\u7acb\u5728\u5916\u4fa7\u626b\u63cf\u4ee3\u4ef7\u4e4b\u4e0a\uff0c\u518d\u52a0\u4e0a\u6bcf\u4e2a\u5916\u4fa7\u884c\u90fd\u8981\u6267\u884c\u4e00\u6b21\u5185\u4fa7\u626b\u63cf\u7684\u4ee3\u4ef7\uff08\u8fd9\u91cc\u662f 10 * 7.90\uff09\uff0c\u4ee5\u53ca\u5c11\u91cf\u8fde\u63a5\u5904\u7406\u7684 CPU \u65f6\u95f4\u3002", "\u8fd9\u4e2a\u523b\u610f\u6784\u9020\u7684\u793a\u4f8b\u8bf4\u660e\u4e86\u4e24\u70b9\uff1a\u5916\u5c42\u8ba1\u5212\u7684\u503c\u53ef\u4f20\u5165\u5b50\u8ba1\u5212\uff08\u8fd9\u91cc\u4f20\u5165 t.four\uff09\uff0c\u5b50\u67e5\u8be2\u7ed3\u679c\u4e5f\u53ef\u4f9b\u5916\u5c42\u8ba1\u5212\u4f7f\u7528\u3002EXPLAIN \u7528 (subplan_name).col N \u4e00\u7c7b\u8bb0\u53f7\u663e\u793a\u8fd9\u4e9b\u7ed3\u679c\u503c\uff0c\u8868\u793a\u5b50 SELECT \u7684\u7b2c N \u4e2a\u8f93\u51fa\u5217\u3002", "\u53ef\u4f7f\u7528 EXPLAIN \u7684 ANALYZE \u9009\u9879\u68c0\u67e5\u89c4\u5212\u5668\u4f30\u7b97\u662f\u5426\u51c6\u786e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\uff0cEXPLAIN \u4f1a\u5b9e\u9645\u6267\u884c\u67e5\u8be2\uff0c\u7136\u540e\u663e\u793a\u6bcf\u4e2a\u8ba1\u5212\u8282\u70b9\u7d2f\u8ba1\u7684\u771f\u5b9e\u884c\u6570\u548c\u771f\u5b9e\u8fd0\u884c\u65f6\u95f4\uff0c\u4ee5\u53ca\u666e\u901a EXPLAIN \u6240\u663e\u793a\u7684\u4f30\u7b97\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u80fd\u5f97\u5230\u5982\u4e0b\u7ed3\u679c\uff1a", "\u7531\u4e8e\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u5c06\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u6267\u884c\u5230\u5e95\uff0c\u56e0\u6b64\u4e0d\u80fd\u7b80\u5355\u5730\u62ff\u4e00\u4e2a\u666e\u901a\u67e5\u8be2\u8ba1\u5212\u5e76\u8ba9\u591a\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u540c\u65f6\u8fd0\u884c\u3002\u90a3\u6837\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u751f\u6210\u5b8c\u6574\u8f93\u51fa\u7ed3\u679c\u96c6\u7684\u4e00\u4efd\u526f\u672c\uff0c\u6240\u4ee5\u67e5\u8be2\u4e0d\u4ec5\u4e0d\u4f1a\u6bd4\u5e73\u5e38\u66f4\u5feb\uff0c\u53cd\u800c\u4f1a\u4ea7\u751f\u9519\u8bef\u7ed3\u679c\u3002\u76f8\u53cd\uff0c\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u5fc5\u987b\u662f\u67e5\u8be2\u4f18\u5316\u5668\u5185\u90e8\u6240\u8bf4\u7684 \u90e8\u5206\u8ba1\u5212 \uff1b\u4e5f\u5c31\u662f\u8bf4\uff0c\u5b83\u5fc5\u987b\u88ab\u6784\u9020\u4e3a\u4f7f\u6267\u884c\u8be5\u8ba1\u5212\u7684\u6bcf\u4e2a\u8fdb\u7a0b\u53ea\u751f\u6210\u8f93\u51fa\u884c\u7684\u4e00\u4e2a\u5b50\u96c6\uff0c\u5e76\u4e14\u4fdd\u8bc1\u6bcf\u4e00\u6761\u6240\u9700\u8f93\u51fa\u884c\u90fd\u6070\u597d\u7531\u67d0\u4e2a\u534f\u4f5c\u8fdb\u7a0b\u751f\u6210\u4e00\u6b21\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u8fd9\u610f\u5473\u7740\u67e5\u8be2\u9a71\u52a8\u8868\u4e0a\u7684\u626b\u63cf\u5fc5\u987b\u662f\u5e76\u884c\u611f\u77e5\u626b\u63cf\u3002"]}, {"title": "\u672c\u7248\u624b\u518c\u4e2d\u7684\u793a\u4f8b", "blocks": [{"code": "EXPLAIN VERBOSE SELECT unique1\nFROM tenk1 t1 WHERE t1.ten = (SELECT (random() * 10)::integer);\n\n                             QUERY PLAN\n--------------------------------------------------------------------\n Seq Scan on public.tenk1 t1  (cost=0.02..470.02 rows=1000 width=4)\n   Output: t1.unique1\n   Filter: (t1.ten = (InitPlan 1).col1)\n   InitPlan 1\n     ->  Result  (cost=0.00..0.02 rows=1 width=4)\n           Output: ((random() * '10'::double precision))::integer", "source": {"url": "/docs/19/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 19beta4 \u00b7 using-explain", "sha256": "52f111fbd213e2200146319d01a9dcc2ea90001617d2a28edc52f7954c2dd70b"}, "paragraphs": ["\u793a\u4f8b\u6458\u81ea PostgreSQL 19beta4 \u624b\u518c\uff1b\u672c\u767e\u79d1\u672a\u5b9e\u9645\u6267\u884c\u6b64\u793a\u4f8b\u3002", "\u5982\u679c\u5b50 SELECT \u4e0d\u4ec5\u4e0d\u5f15\u7528\u5916\u5c42\u67e5\u8be2\u7684\u4efb\u4f55\u53d8\u91cf\uff0c\u800c\u4e14\u6700\u591a\u53ea\u4f1a\u8fd4\u56de\u4e00\u884c\uff0c\u90a3\u4e48\u5b83\u8fd8\u53ef\u80fd\u88ab\u5b9e\u73b0\u6210\u4e00\u4e2a \u521d\u59cb\u8ba1\u5212 \uff1a"]}]}, {"title": "\u6267\u884c\u5668\u5b9e\u73b0\u8bf4\u660e", "paragraphs": ["nodeResult.c\uff1a\u652f\u6301\u9700\u8981\u7279\u6b8a\u4ee3\u7801\u7684\u5e38\u91cf\u8282\u70b9\u3002", "Result \u8282\u70b9\u7528\u4e8e\u4e0d\u626b\u63cf\u4efb\u4f55\u5173\u7cfb\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\uff08\u8bf7\u8bb0\u4f4f\uff0cINSERT \u6216 UPDATE \u9700\u8981\u4e00\u68f5\u751f\u6210\u65b0\u884c\u7684\u8ba1\u5212\u6811\u3002\uff09", "Result \u8282\u70b9\u4e5f\u7528\u4e8e\u4f18\u5316\u5e26\u6709\u5e38\u91cf\u6761\u4ef6\uff08\u5373\u4e0d\u4f9d\u8d56\u626b\u63cf\u6570\u636e\u7684\u6761\u4ef6\uff09\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\u8fd0\u884c\u65f6\uff0cResult \u8282\u70b9\u53ea\u8ba1\u7b97\u4e00\u6b21\u5e38\u91cf\u6761\u4ef6\uff0cEXPLAIN \u5c06\u5176\u663e\u793a\u4e3a One-Time Filter\u3002\u5982\u679c\u6761\u4ef6\u4e3a\u5047\uff0c\u65e0\u9700\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u4fbf\u53ef\u8fd4\u56de\u7a7a\u7ed3\u679c\u96c6\uff1b\u5982\u679c\u4e3a\u771f\uff0c\u5219\u6b63\u5e38\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u5e76\u4f20\u56de\u7ed3\u679c\u3002"]}, {"code": "case T_Result:\n\t\t\tpname = sname = \"Result\";\n\t\t\tbreak;", "title": "\u6838\u5fc3\u6e90\u7801\u4e2d\u7684 EXPLAIN \u6807\u8bc6"}], "strategies": [], "description": ["\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002"], "localization": {"status": "complete", "sources": [{"url": "/docs/19/parallel-plans.html", "method": "same-major semantic node", "sha256": "c162417a8d7d4bf4b4b79ba445207cd01020c24ca11178e13a9fa3d7d8ca8e2e", "language": "zh", "matched_nodes": ["#PARALLEL-PLANS/p[2]"]}, {"url": "/docs/19/using-explain.html", "method": "same-major semantic node", "sha256": "7cc78f59bf29afb1811ece53e9d5c572a3f634d66d7422fb8761f19bc6811492", "language": "zh", "matched_nodes": ["#USING-EXPLAIN/div[7]/p[40]", "#USING-EXPLAIN/div[7]/p[64]"]}], "language": "zh", "original_text": {"/versions/19/description/0": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/versions/19/facts/0/label": "Core node tag", "/versions/19/facts/1/label": "Structured EXPLAIN Node Type", "/versions/19/facts/2/label": "Inputs", "/versions/19/facts/2/value": "Optional child plan", "/versions/19/facts/3/label": "Output", "/versions/19/facts/3/value": "Projected tuples", "/versions/19/facts/4/label": "Executor initializer", "/versions/19/facts/5/label": "Memory mechanism", "/versions/19/tables/0/title": "EXPLAIN labels in this source build", "/versions/19/related/1/label": "Using EXPLAIN", "/versions/19/related/2/label": "Parallel plans", "/versions/19/sections/0/title": "EXPLAIN names and attributes", "/versions/19/sections/1/title": "Memory and temporary storage", "/versions/19/sections/2/title": "Parallel execution and instrumentation", "/versions/19/sections/3/title": "Same-version manual discussion", "/versions/19/sections/4/title": "Examples from this manual build", "/versions/19/sections/5/title": "Executor implementation notes", "/versions/19/sections/6/title": "EXPLAIN identity in core source", "/versions/19/memory/description": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/19/sections/0/paragraphs/0": "Structured formats use the Node Type above. Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.", "/versions/19/sections/0/paragraphs/1": "Text names recorded by this source: Result.", "/versions/19/sections/0/paragraphs/2": "Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node.", "/versions/19/sections/1/paragraphs/0": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/19/sections/2/paragraphs/0": "The source callbacks below can coordinate execution or collect worker instrumentation. Their presence is not a blanket claim that this node supports a shared parallel scan or shared state.", "/versions/19/sections/2/paragraphs/1": "Callbacks in this build: none extracted from this node implementation.", "/versions/19/sections/3/paragraphs/0": "The rows value is a little tricky because it is not the number of rows processed or scanned by the plan node, but rather the number emitted by the node. This is often less than the number scanned, as a result of filtering by any WHERE -clause conditions that are being applied at the node. Ideally the top-level rows estimate will approximate the number of rows actually returned, updated, or deleted by the query.", "/versions/19/sections/3/paragraphs/1": "Compared to regular sorts, sorting incrementally allows returning tuples before the entire result set has been sorted, which particularly enables optimizations with LIMIT queries. It may also reduce memory usage and the likelihood of spilling sorts to disk, but it comes at the cost of the increased overhead of splitting the result set into multiple sorting batches.", "/versions/19/sections/3/paragraphs/2": "In this plan, we have a nested-loop join node with two table scans as inputs, or children. The indentation of the node summary lines reflects the plan tree structure. The join's first, or \u201c outer \u201d , child is a bitmap scan similar to those we saw before. Its cost and row count are the same as we'd get from SELECT ... WHERE unique1 < 10 because we are applying the WHERE clause unique1 < 10 at that node. The t1.unique2 = t2.unique2 clause is not relevant yet, so it doesn't affect the row count of the outer scan. The nested-loop join node will run its second, or \u201c inner \u201d child once for each row obtained from the outer child. Column values from the current outer row can be plugged into the inner scan; here, the t1.unique2 value from the outer row is available, so we get a plan and costs similar to what we saw above for a simple SELECT ... WHERE t2.unique2 = constant case. (The estimated cost is actually a bit lower than what was seen above, as a result of caching that's expected to occur during the repeated index scans on t2 .) The costs of the loop node are then set on the basis of the cost of the outer scan, plus one repetition of the inner scan for each outer row (10 * 7.90, here), plus a little CPU time for join processing.", "/versions/19/sections/3/paragraphs/3": "This rather artificial example serves to illustrate a couple of points: values from the outer plan level can be passed down into a subplan (here, t.four is passed down) and the results of the sub-select are available to the outer plan. Those result values are shown by EXPLAIN with notations like ( subplan_name ).col N , which refers to the N 'th output column of the sub- SELECT .", "/versions/19/sections/3/paragraphs/4": "It is possible to check the accuracy of the planner's estimates by using EXPLAIN 's ANALYZE option. With this option, EXPLAIN actually executes the query, and then displays the true row counts and true run time accumulated within each plan node, along with the same estimates that a plain EXPLAIN shows. For example, we might get a result like this:", "/versions/19/sections/3/paragraphs/5": "Because each worker executes the parallel portion of the plan to completion, it is not possible to simply take an ordinary query plan and run it using multiple workers. Each worker would produce a full copy of the output result set, so the query would not run any faster than normal but would produce incorrect results. Instead, the parallel portion of the plan must be what is known internally to the query optimizer as a partial plan ; that is, it must be constructed so that each process that executes the plan will generate only a subset of the output rows in such a way that each required output row is guaranteed to be generated by exactly one of the cooperating processes. Generally, this means that the scan on the driving table of the query must be a parallel-aware scan.", "/versions/19/sections/5/paragraphs/0": "nodeResult.c support for constant nodes needing special code.", "/versions/19/sections/5/paragraphs/1": "Result nodes are used in queries where no relations are scanned. Examples of such queries are:", "/versions/19/sections/5/paragraphs/2": "(Remember that in an INSERT or UPDATE, we need a plan tree that generates the new rows.)", "/versions/19/sections/5/paragraphs/3": "Result nodes are also used to optimise queries with constant qualifications (ie, quals that do not depend on the scanned data), such as:", "/versions/19/sections/5/paragraphs/4": "At runtime, the Result node evaluates the constant qual once, which is shown by EXPLAIN as a One-Time Filter. If it's false, we can return an empty result set without running the controlled plan at all. If it's true, we run the controlled plan normally and pass back the results.", "/versions/19/tables/0/columns/0/label": "Text-format label", "/versions/19/tables/0/columns/1/label": "Structured node identity", "/versions/19/sections/4/blocks/0/paragraphs/0": "Example copied from the PostgreSQL 19beta4 manual; it was not executed for this collection.", "/versions/19/sections/4/blocks/0/paragraphs/1": "If, in addition to not referencing any variables of the outer query, the sub- SELECT cannot return more than one row, it may instead be implemented as an initplan :"}, "fallback_fields": [], "source_language": "en", "original_snapshot_sha256": "afdba315de866a6f0ad13c26b140bfef3e76f361bcc5754af346b812429a3871"}, "evidence_kind": "source and documentation", "explain_names": ["Result"], "partial_modes": [], "comparison_data": {"node_tag": "T_Result", "strategies": [], "text_names": ["Result"], "initializer": "ExecInitResult", "partial_modes": [], "memory_mechanism": "unclassified", "parallel_callbacks": []}, "comparison_hash": "7d9e21f5e91321228505ba502e7faa5b9ebdda5ba4d71b8a9b97571a1f87b5f5", "explain_prefixes": ["Parallel", "Async"], "runtime_verified": false, "source_inventory": {"explain": "src/backend/commands/explain.c", "executor": "src/backend/executor/execProcnode.c", "implementation": "src/backend/executor/nodeResult.c"}, "parallel_callbacks": []}, "20": {"facts": [{"label": "\u6838\u5fc3\u8282\u70b9\u6807\u7b7e", "value": "T_Result"}, {"label": "\u7ed3\u6784\u5316 EXPLAIN \u8282\u70b9\u7c7b\u578b", "value": "Result"}, {"label": "\u8f93\u5165", "value": "\u53ef\u9009\u7684\u5b50\u8ba1\u5212"}, {"label": "\u8f93\u51fa", "value": "\u6295\u5f71\u540e\u7684\u5143\u7ec4"}, {"label": "\u6267\u884c\u5668\u521d\u59cb\u5316\u51fd\u6570", "value": "ExecInitResult"}, {"label": "\u5185\u5b58\u673a\u5236", "value": "unclassified"}], "memory": {"evidence": [{"url": "https://ftp.postgresql.org/pub/snapshot/dev/postgresql-snapshot.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "3de5782280c9d96398da2c356e5f601043885f33542057bcc1c5ba61a5ad4ca3", "archive_sha256": "4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41"}], "mechanism": "unclassified", "description": "\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002", "source_notes": []}, "tables": [{"key": "explain-labels", "rows": [{"label": "Result", "identity": "Result"}], "title": "\u672c\u6784\u5efa\u4e2d\u7684 EXPLAIN \u6807\u7b7e", "columns": [{"key": "label", "label": "\u6587\u672c\u683c\u5f0f\u6807\u7b7e"}, {"key": "identity", "label": "\u7ed3\u6784\u5316\u8282\u70b9\u6807\u8bc6"}]}], "related": [{"url": "/wiki/sql/explain/?v=20", "label": "EXPLAIN"}, {"url": "/docs/devel/using-explain.html", "label": "\u4f7f\u7528 EXPLAIN"}, {"url": "/docs/devel/parallel-plans.html", "label": "\u5e76\u884c\u8ba1\u5212"}], "release": {"ref": "PostgreSQL 20devel source archive", "label": "20devel", "major": "20", "channel": "devel", "revision": "4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41", "source_url": "https://ftp.postgresql.org/pub/snapshot/dev/postgresql-snapshot.tar.bz2", "source_snapshot_utc": "26-Sep-2026 20:22"}, "sources": [{"url": "https://ftp.postgresql.org/pub/snapshot/dev/postgresql-snapshot.tar.bz2", "line": 1391, "path": "src/backend/commands/explain.c", "label": "src/backend/commands/explain.c:1391", "sha256": "13402758013520451539427b5993db06d463ca11c4e2d4cc5444e82367688077", "archive_sha256": "4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41"}, {"url": "https://ftp.postgresql.org/pub/snapshot/dev/postgresql-snapshot.tar.bz2", "line": 166, "path": "src/backend/executor/execProcnode.c", "label": "src/backend/executor/execProcnode.c:166", "sha256": "5e39b2037bed672da55104229ecc32da5abde44c26bcad01479edcfa044d09ed", "archive_sha256": "4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41"}, {"url": "https://ftp.postgresql.org/pub/snapshot/dev/postgresql-snapshot.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "3de5782280c9d96398da2c356e5f601043885f33542057bcc1c5ba61a5ad4ca3", "archive_sha256": "4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41"}, {"url": "https://ftp.postgresql.org/pub/snapshot/dev/postgresql-snapshot.tar.bz2", "path": "src/include/nodes/plannodes.h", "label": "src/include/nodes/plannodes.h", "sha256": "7a94ed1652f0d74d50c39971d1cd3e8051dbc0d6058f31b6de71a433ca343521", "archive_sha256": "4d3346909b201ac1648232cf290462a7070c119326f56196f1f0253ed80fae41"}, {"url": "https://pg.center/docs/devel/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 20devel \u00b7 using-explain", "sha256": "99cfea3035876ea63f88b75ba8c964b51a32a70606544e09f769c0b60a234b31", "language": "en", "original_url": "/docs/devel/using-explain.html#USING-EXPLAIN-BASICS"}, {"url": "https://pg.center/docs/devel/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 20devel \u00b7 using-explain", "sha256": "99cfea3035876ea63f88b75ba8c964b51a32a70606544e09f769c0b60a234b31", "language": "en", "original_url": "/docs/devel/using-explain.html#USING-EXPLAIN-ANALYZE"}, {"url": "https://pg.center/docs/devel/parallel-plans.html#PARALLEL-PLANS", "path": "parallel-plans.html", "label": "PostgreSQL 20devel \u00b7 parallel-plans", "sha256": "6451d4254d26d789b8697ba7207288ac26e75e56f9711c8a5a3f5480171a4724", "language": "en", "original_url": "/docs/devel/parallel-plans.html#PARALLEL-PLANS"}], "node_tag": "T_Result", "sections": [{"title": "EXPLAIN \u540d\u79f0\u4e0e\u5c5e\u6027", "paragraphs": ["\u7ed3\u6784\u5316\u683c\u5f0f\u4f7f\u7528\u4e0a\u8ff0 Node Type\u3002\u6587\u672c\u683c\u5f0f\u540d\u79f0\u8fd8\u53ef\u80fd\u5305\u542b\u64cd\u4f5c\u3001\u7b56\u7565\u3001\u8fde\u63a5\u7c7b\u578b\u3001\u626b\u63cf\u65b9\u5411\u6216\u805a\u5408\u9636\u6bb5\u5c5e\u6027\u3002", "\u6b64\u6e90\u7801\u8bb0\u5f55\u7684\u6587\u672c\u540d\u79f0\uff1aResult.", "\u5e76\u884c\u611f\u77e5\u4e0e\u5e76\u884c\u5b89\u5168\u662f\u4e0d\u540c\u7684\u8ba1\u5212\u5c5e\u6027\u3002\u5728\u5e76\u884c\u5de5\u4f5c\u8fdb\u7a0b\u5185\u8fd0\u884c\u7684\u8282\u70b9\u4e0d\u4e00\u5b9a\u662f\u5e76\u884c\u611f\u77e5\u8282\u70b9\u3002"]}, {"title": "\u5185\u5b58\u4e0e\u4e34\u65f6\u5b58\u50a8", "paragraphs": ["\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002"]}, {"title": "\u5e76\u884c\u6267\u884c\u4e0e\u8fd0\u884c\u4fe1\u606f\u91c7\u96c6", "paragraphs": ["\u4ee5\u4e0b\u6e90\u7801\u56de\u8c03\u53ef\u4ee5\u534f\u8c03\u6267\u884c\u6216\u6536\u96c6\u5de5\u4f5c\u8fdb\u7a0b\u7684\u6d4b\u91cf\u6570\u636e\u3002\u56de\u8c03\u5b58\u5728\u4e0d\u4ee3\u8868\u8be5\u8282\u70b9\u666e\u904d\u652f\u6301\u5171\u4eab\u5e76\u884c\u626b\u63cf\u6216\u5171\u4eab\u72b6\u6001\u3002", "\u6b64\u6784\u5efa\u7684\u56de\u8c03\uff1anone extracted from this node implementation."]}, {"title": "\u540c\u7248\u672c\u624b\u518c\u8bf4\u660e", "paragraphs": ["rows \u5bb9\u6613\u4ee4\u4eba\u8bef\u89e3\uff1a\u5b83\u8868\u793a\u8282\u70b9\u8f93\u51fa\u7684\u884c\u6570\uff0c\u800c\u4e0d\u662f\u5904\u7406\u6216\u626b\u63cf\u7684\u884c\u6570\u3002\u8282\u70b9\u5e94\u7528 WHERE \u6761\u4ef6\u7b5b\u9009\u540e\uff0c\u8f93\u51fa\u884c\u6570\u901a\u5e38\u5c0f\u4e8e\u626b\u63cf\u884c\u6570\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u9876\u5c42 rows \u4f30\u8ba1\u5e94\u63a5\u8fd1\u67e5\u8be2\u5b9e\u9645\u8fd4\u56de\u3001\u66f4\u65b0\u6216\u5220\u9664\u7684\u884c\u6570\u3002", "\u4e0e\u666e\u901a\u6392\u5e8f\u76f8\u6bd4\uff0c\u589e\u91cf\u6392\u5e8f\u53ef\u5728\u6574\u4e2a\u7ed3\u679c\u96c6\u5c1a\u672a\u6392\u5b8c\u65f6\u5c31\u8fd4\u56de\u5143\u7ec4\uff0c\u5c24\u5176\u6709\u5229\u4e8e\u4f18\u5316\u5e26 LIMIT \u7684\u67e5\u8be2\u3002\u5b83\u8fd8\u53ef\u80fd\u51cf\u5c11\u5185\u5b58\u7528\u91cf\u548c\u6392\u5e8f\u6ea2\u5199\u78c1\u76d8\u7684\u6982\u7387\uff0c\u4f46\u4ee3\u4ef7\u662f\u5c06\u7ed3\u679c\u96c6\u62c6\u6210\u591a\u4e2a\u6392\u5e8f\u6279\u6b21\u6240\u5e26\u6765\u7684\u989d\u5916\u5f00\u9500\u3002", "\u5728\u8fd9\u4e2a\u8ba1\u5212\u4e2d\uff0c\u6709\u4e00\u4e2a\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\uff0c\u5b83\u7684\u4e24\u4e2a\u8f93\u5165\uff0c\u4e5f\u5c31\u662f\u4e24\u4e2a\u5b50\u8282\u70b9\uff0c\u90fd\u662f\u8868\u626b\u63cf\u3002\u8282\u70b9\u6458\u8981\u884c\u7684\u7f29\u8fdb\u53cd\u6620\u4e86\u8ba1\u5212\u6811\u7ed3\u6784\u3002\u8fde\u63a5\u7684\u7b2c\u4e00\u4e2a\u5b50\u8282\u70b9\uff0c\u4e5f\u5c31\u662f \u201c \u5916\u4fa7 \u201d \u5b50\u8282\u70b9\uff0c\u662f\u4e00\u4e2a\u4e0e\u524d\u9762\u89c1\u8fc7\u7684\u4f4d\u56fe\u626b\u63cf\u7c7b\u4f3c\u7684\u8282\u70b9\u3002\u5b83\u7684\u4ee3\u4ef7\u548c\u884c\u8ba1\u6570\u4e0e SELECT ... WHERE unique1 < 10 \u5f97\u5230\u7684\u7ed3\u679c\u76f8\u540c\uff0c\u56e0\u4e3a WHERE \u5b50\u53e5 unique1 < 10 \u6b63\u662f\u5728\u8be5\u8282\u70b9\u4e0a\u5e94\u7528\u7684\u3002 t1.unique2 = t2.unique2 \u5b50\u53e5\u6b64\u65f6\u8fd8\u65e0\u5173\uff0c\u56e0\u6b64\u4e0d\u4f1a\u5f71\u54cd\u5916\u4fa7\u626b\u63cf\u7684\u884c\u8ba1\u6570\u3002\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\u4f1a\u5bf9\u4ece\u5916\u4fa7\u5b50\u8282\u70b9\u5f97\u5230\u7684\u6bcf\u4e00\u884c\u6267\u884c\u4e00\u6b21\u7b2c\u4e8c\u4e2a\uff0c\u4e5f\u5c31\u662f \u201c \u5185\u4fa7 \u201d \u5b50\u8282\u70b9\u3002\u5f53\u524d\u5916\u4fa7\u884c\u4e2d\u7684\u5217\u503c\u53ef\u4ee5\u4ee3\u5165\u5185\u4fa7\u626b\u63cf\uff1b\u8fd9\u91cc\u5916\u4fa7\u884c\u7684 t1.unique2 \u503c\u53ef\u7528\uff0c\u56e0\u6b64\u5f97\u5230\u7684\u8ba1\u5212\u548c\u4ee3\u4ef7\u4e0e\u524d\u9762\u770b\u5230\u7684\u7b80\u5355 SELECT ... WHERE t2.unique2 = constant \u60c5\u5f62\u7c7b\u4f3c\u3002\uff08\u7531\u4e8e\u9884\u671f\u5728\u5bf9 t2 \u53cd\u590d\u6267\u884c\u7d22\u5f15\u626b\u63cf\u671f\u95f4\u4f1a\u53d1\u751f\u7f13\u5b58\u547d\u4e2d\uff0c\u4f30\u8ba1\u4ee3\u4ef7\u5b9e\u9645\u4e0a\u6bd4\u524d\u9762\u770b\u5230\u7684\u7565\u4f4e\u4e00\u4e9b\u3002\uff09\u968f\u540e\uff0c\u5faa\u73af\u8282\u70b9\u7684\u4ee3\u4ef7\u5efa\u7acb\u5728\u5916\u4fa7\u626b\u63cf\u4ee3\u4ef7\u4e4b\u4e0a\uff0c\u518d\u52a0\u4e0a\u6bcf\u4e2a\u5916\u4fa7\u884c\u90fd\u8981\u6267\u884c\u4e00\u6b21\u5185\u4fa7\u626b\u63cf\u7684\u4ee3\u4ef7\uff08\u8fd9\u91cc\u662f 10 * 7.90\uff09\uff0c\u4ee5\u53ca\u5c11\u91cf\u8fde\u63a5\u5904\u7406\u7684 CPU \u65f6\u95f4\u3002", "\u8fd9\u4e2a\u523b\u610f\u6784\u9020\u7684\u793a\u4f8b\u8bf4\u660e\u4e86\u4e24\u70b9\uff1a\u5916\u5c42\u8ba1\u5212\u7684\u503c\u53ef\u4f20\u5165\u5b50\u8ba1\u5212\uff08\u8fd9\u91cc\u4f20\u5165 t.four\uff09\uff0c\u5b50\u67e5\u8be2\u7ed3\u679c\u4e5f\u53ef\u4f9b\u5916\u5c42\u8ba1\u5212\u4f7f\u7528\u3002EXPLAIN \u7528 (subplan_name).col N \u4e00\u7c7b\u8bb0\u53f7\u663e\u793a\u8fd9\u4e9b\u7ed3\u679c\u503c\uff0c\u8868\u793a\u5b50 SELECT \u7684\u7b2c N \u4e2a\u8f93\u51fa\u5217\u3002", "\u53ef\u4f7f\u7528 EXPLAIN \u7684 ANALYZE \u9009\u9879\u68c0\u67e5\u89c4\u5212\u5668\u4f30\u7b97\u662f\u5426\u51c6\u786e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\uff0cEXPLAIN \u4f1a\u5b9e\u9645\u6267\u884c\u67e5\u8be2\uff0c\u7136\u540e\u663e\u793a\u6bcf\u4e2a\u8ba1\u5212\u8282\u70b9\u7d2f\u8ba1\u7684\u771f\u5b9e\u884c\u6570\u548c\u771f\u5b9e\u8fd0\u884c\u65f6\u95f4\uff0c\u4ee5\u53ca\u666e\u901a EXPLAIN \u6240\u663e\u793a\u7684\u4f30\u7b97\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u80fd\u5f97\u5230\u5982\u4e0b\u7ed3\u679c\uff1a", "\u7531\u4e8e\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u5c06\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u6267\u884c\u5230\u5e95\uff0c\u56e0\u6b64\u4e0d\u80fd\u7b80\u5355\u5730\u62ff\u4e00\u4e2a\u666e\u901a\u67e5\u8be2\u8ba1\u5212\u5e76\u8ba9\u591a\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u540c\u65f6\u8fd0\u884c\u3002\u90a3\u6837\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u751f\u6210\u5b8c\u6574\u8f93\u51fa\u7ed3\u679c\u96c6\u7684\u4e00\u4efd\u526f\u672c\uff0c\u6240\u4ee5\u67e5\u8be2\u4e0d\u4ec5\u4e0d\u4f1a\u6bd4\u5e73\u5e38\u66f4\u5feb\uff0c\u53cd\u800c\u4f1a\u4ea7\u751f\u9519\u8bef\u7ed3\u679c\u3002\u76f8\u53cd\uff0c\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u5fc5\u987b\u662f\u67e5\u8be2\u4f18\u5316\u5668\u5185\u90e8\u6240\u8bf4\u7684 \u90e8\u5206\u8ba1\u5212 \uff1b\u4e5f\u5c31\u662f\u8bf4\uff0c\u5b83\u5fc5\u987b\u88ab\u6784\u9020\u4e3a\u4f7f\u6267\u884c\u8be5\u8ba1\u5212\u7684\u6bcf\u4e2a\u8fdb\u7a0b\u53ea\u751f\u6210\u8f93\u51fa\u884c\u7684\u4e00\u4e2a\u5b50\u96c6\uff0c\u5e76\u4e14\u4fdd\u8bc1\u6bcf\u4e00\u6761\u6240\u9700\u8f93\u51fa\u884c\u90fd\u6070\u597d\u7531\u67d0\u4e2a\u534f\u4f5c\u8fdb\u7a0b\u751f\u6210\u4e00\u6b21\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u8fd9\u610f\u5473\u7740\u67e5\u8be2\u9a71\u52a8\u8868\u4e0a\u7684\u626b\u63cf\u5fc5\u987b\u662f\u5e76\u884c\u611f\u77e5\u626b\u63cf\u3002"]}, {"title": "\u672c\u7248\u624b\u518c\u4e2d\u7684\u793a\u4f8b", "blocks": [{"code": "EXPLAIN VERBOSE SELECT unique1\nFROM tenk1 t1 WHERE t1.ten = (SELECT (random() * 10)::integer);\n\n                             QUERY PLAN\n--------------------------------------------------------------------\n Seq Scan on public.tenk1 t1  (cost=0.02..470.02 rows=1000 width=4)\n   Output: t1.unique1\n   Filter: (t1.ten = (InitPlan 1).col1)\n   InitPlan 1\n     ->  Result  (cost=0.00..0.02 rows=1 width=4)\n           Output: ((random() * '10'::double precision))::integer", "source": {"url": "/docs/devel/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 20devel \u00b7 using-explain", "sha256": "99cfea3035876ea63f88b75ba8c964b51a32a70606544e09f769c0b60a234b31"}, "paragraphs": ["\u793a\u4f8b\u6458\u81ea PostgreSQL 20devel \u624b\u518c\uff1b\u672c\u767e\u79d1\u672a\u5b9e\u9645\u6267\u884c\u6b64\u793a\u4f8b\u3002", "\u5982\u679c\u5b50 SELECT \u4e0d\u4ec5\u4e0d\u5f15\u7528\u5916\u5c42\u67e5\u8be2\u7684\u4efb\u4f55\u53d8\u91cf\uff0c\u800c\u4e14\u6700\u591a\u53ea\u4f1a\u8fd4\u56de\u4e00\u884c\uff0c\u90a3\u4e48\u5b83\u8fd8\u53ef\u80fd\u88ab\u5b9e\u73b0\u6210\u4e00\u4e2a \u521d\u59cb\u8ba1\u5212 \uff1a"]}]}, {"title": "\u6267\u884c\u5668\u5b9e\u73b0\u8bf4\u660e", "paragraphs": ["nodeResult.c\uff1a\u652f\u6301\u9700\u8981\u7279\u6b8a\u4ee3\u7801\u7684\u5e38\u91cf\u8282\u70b9\u3002", "Result \u8282\u70b9\u7528\u4e8e\u4e0d\u626b\u63cf\u4efb\u4f55\u5173\u7cfb\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\uff08\u8bf7\u8bb0\u4f4f\uff0cINSERT \u6216 UPDATE \u9700\u8981\u4e00\u68f5\u751f\u6210\u65b0\u884c\u7684\u8ba1\u5212\u6811\u3002\uff09", "Result \u8282\u70b9\u4e5f\u7528\u4e8e\u4f18\u5316\u5e26\u6709\u5e38\u91cf\u6761\u4ef6\uff08\u5373\u4e0d\u4f9d\u8d56\u626b\u63cf\u6570\u636e\u7684\u6761\u4ef6\uff09\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\u8fd0\u884c\u65f6\uff0cResult \u8282\u70b9\u53ea\u8ba1\u7b97\u4e00\u6b21\u5e38\u91cf\u6761\u4ef6\uff0cEXPLAIN \u5c06\u5176\u663e\u793a\u4e3a One-Time Filter\u3002\u5982\u679c\u6761\u4ef6\u4e3a\u5047\uff0c\u65e0\u9700\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u4fbf\u53ef\u8fd4\u56de\u7a7a\u7ed3\u679c\u96c6\uff1b\u5982\u679c\u4e3a\u771f\uff0c\u5219\u6b63\u5e38\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u5e76\u4f20\u56de\u7ed3\u679c\u3002"]}, {"code": "case T_Result:\n\t\t\tpname = sname = \"Result\";\n\t\t\tbreak;", "title": "\u6838\u5fc3\u6e90\u7801\u4e2d\u7684 EXPLAIN \u6807\u8bc6"}], "strategies": [], "description": ["\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002"], "localization": {"status": "complete", "sources": [{"url": "/docs/devel/parallel-plans.html", "method": "same-major semantic node", "sha256": "322333100879d0971d33685d4924d0c6b79bc429a74a35f9cca60c247e02b545", "language": "zh", "matched_nodes": ["#PARALLEL-PLANS/p[2]"]}, {"url": "/docs/devel/using-explain.html", "method": "same-major semantic node", "sha256": "2744ee0e88d132c504bf5e102765edaabd393eb12c59294093db6d90b26dd65c", "language": "zh", "matched_nodes": ["#USING-EXPLAIN/div[7]/p[40]", "#USING-EXPLAIN/div[7]/p[64]"]}], "language": "zh", "original_text": {"/summary": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/category": "Control", "/versions/20/description/0": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/versions/20/facts/0/label": "Core node tag", "/versions/20/facts/1/label": "Structured EXPLAIN Node Type", "/versions/20/facts/2/label": "Inputs", "/versions/20/facts/2/value": "Optional child plan", "/versions/20/facts/3/label": "Output", "/versions/20/facts/3/value": "Projected tuples", "/versions/20/facts/4/label": "Executor initializer", "/versions/20/facts/5/label": "Memory mechanism", "/versions/20/tables/0/title": "EXPLAIN labels in this source build", "/versions/20/related/1/label": "Using EXPLAIN", "/versions/20/related/2/label": "Parallel plans", "/versions/20/sections/0/title": "EXPLAIN names and attributes", "/versions/20/sections/1/title": "Memory and temporary storage", "/versions/20/sections/2/title": "Parallel execution and instrumentation", "/versions/20/sections/3/title": "Same-version manual discussion", "/versions/20/sections/4/title": "Examples from this manual build", "/versions/20/sections/5/title": "Executor implementation notes", "/versions/20/sections/6/title": "EXPLAIN identity in core source", "/versions/20/memory/description": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/20/sections/0/paragraphs/0": "Structured formats use the Node Type above. Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.", "/versions/20/sections/0/paragraphs/1": "Text names recorded by this source: Result.", "/versions/20/sections/0/paragraphs/2": "Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node.", "/versions/20/sections/1/paragraphs/0": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/20/sections/2/paragraphs/0": "The source callbacks below can coordinate execution or collect worker instrumentation. Their presence is not a blanket claim that this node supports a shared parallel scan or shared state.", "/versions/20/sections/2/paragraphs/1": "Callbacks in this build: none extracted from this node implementation.", "/versions/20/sections/3/paragraphs/0": "The rows value is a little tricky because it is not the number of rows processed or scanned by the plan node, but rather the number emitted by the node. This is often less than the number scanned, as a result of filtering by any WHERE -clause conditions that are being applied at the node. Ideally the top-level rows estimate will approximate the number of rows actually returned, updated, or deleted by the query.", "/versions/20/sections/3/paragraphs/1": "Compared to regular sorts, sorting incrementally allows returning tuples before the entire result set has been sorted, which particularly enables optimizations with LIMIT queries. It may also reduce memory usage and the likelihood of spilling sorts to disk, but it comes at the cost of the increased overhead of splitting the result set into multiple sorting batches.", "/versions/20/sections/3/paragraphs/2": "In this plan, we have a nested-loop join node with two table scans as inputs, or children. The indentation of the node summary lines reflects the plan tree structure. The join's first, or \u201c outer \u201d , child is a bitmap scan similar to those we saw before. Its cost and row count are the same as we'd get from SELECT ... WHERE unique1 < 10 because we are applying the WHERE clause unique1 < 10 at that node. The t1.unique2 = t2.unique2 clause is not relevant yet, so it doesn't affect the row count of the outer scan. The nested-loop join node will run its second, or \u201c inner \u201d child once for each row obtained from the outer child. Column values from the current outer row can be plugged into the inner scan; here, the t1.unique2 value from the outer row is available, so we get a plan and costs similar to what we saw above for a simple SELECT ... WHERE t2.unique2 = constant case. (The estimated cost is actually a bit lower than what was seen above, as a result of caching that's expected to occur during the repeated index scans on t2 .) The costs of the loop node are then set on the basis of the cost of the outer scan, plus one repetition of the inner scan for each outer row (10 * 7.90, here), plus a little CPU time for join processing.", "/versions/20/sections/3/paragraphs/3": "This rather artificial example serves to illustrate a couple of points: values from the outer plan level can be passed down into a subplan (here, t.four is passed down) and the results of the sub-select are available to the outer plan. Those result values are shown by EXPLAIN with notations like ( subplan_name ).col N , which refers to the N 'th output column of the sub- SELECT .", "/versions/20/sections/3/paragraphs/4": "It is possible to check the accuracy of the planner's estimates by using EXPLAIN 's ANALYZE option. With this option, EXPLAIN actually executes the query, and then displays the true row counts and true run time accumulated within each plan node, along with the same estimates that a plain EXPLAIN shows. For example, we might get a result like this:", "/versions/20/sections/3/paragraphs/5": "Because each worker executes the parallel portion of the plan to completion, it is not possible to simply take an ordinary query plan and run it using multiple workers. Each worker would produce a full copy of the output result set, so the query would not run any faster than normal but would produce incorrect results. Instead, the parallel portion of the plan must be what is known internally to the query optimizer as a partial plan ; that is, it must be constructed so that each process that executes the plan will generate only a subset of the output rows in such a way that each required output row is guaranteed to be generated by exactly one of the cooperating processes. Generally, this means that the scan on the driving table of the query must be a parallel-aware scan.", "/versions/20/sections/5/paragraphs/0": "nodeResult.c support for constant nodes needing special code.", "/versions/20/sections/5/paragraphs/1": "Result nodes are used in queries where no relations are scanned. Examples of such queries are:", "/versions/20/sections/5/paragraphs/2": "(Remember that in an INSERT or UPDATE, we need a plan tree that generates the new rows.)", "/versions/20/sections/5/paragraphs/3": "Result nodes are also used to optimise queries with constant qualifications (ie, quals that do not depend on the scanned data), such as:", "/versions/20/sections/5/paragraphs/4": "At runtime, the Result node evaluates the constant qual once, which is shown by EXPLAIN as a One-Time Filter. If it's false, we can return an empty result set without running the controlled plan at all. If it's true, we run the controlled plan normally and pass back the results.", "/versions/20/tables/0/columns/0/label": "Text-format label", "/versions/20/tables/0/columns/1/label": "Structured node identity", "/versions/20/sections/4/blocks/0/paragraphs/0": "Example copied from the PostgreSQL 20devel manual; it was not executed for this collection.", "/versions/20/sections/4/blocks/0/paragraphs/1": "If, in addition to not referencing any variables of the outer query, the sub- SELECT cannot return more than one row, it may instead be implemented as an initplan :"}, "fallback_fields": [], "source_language": "en", "original_snapshot_sha256": "2d0ea74b723d2e059b21232d674d8954d84bffd7598068a64a067d58aca4670b"}, "evidence_kind": "source and documentation", "explain_names": ["Result"], "partial_modes": [], "comparison_data": {"node_tag": "T_Result", "strategies": [], "text_names": ["Result"], "initializer": "ExecInitResult", "partial_modes": [], "memory_mechanism": "unclassified", "parallel_callbacks": []}, "comparison_hash": "7d9e21f5e91321228505ba502e7faa5b9ebdda5ba4d71b8a9b97571a1f87b5f5", "explain_prefixes": ["Parallel", "Async"], "runtime_verified": false, "source_inventory": {"explain": "src/backend/commands/explain.c", "executor": "src/backend/executor/execProcnode.c", "implementation": "src/backend/executor/nodeResult.c"}, "parallel_callbacks": []}}}, "snapshot": {"facts": [{"label": "\u6838\u5fc3\u8282\u70b9\u6807\u7b7e", "value": "T_Result"}, {"label": "\u7ed3\u6784\u5316 EXPLAIN \u8282\u70b9\u7c7b\u578b", "value": "Result"}, {"label": "\u8f93\u5165", "value": "\u53ef\u9009\u7684\u5b50\u8ba1\u5212"}, {"label": "\u8f93\u51fa", "value": "\u6295\u5f71\u540e\u7684\u5143\u7ec4"}, {"label": "\u6267\u884c\u5668\u521d\u59cb\u5316\u51fd\u6570", "value": "ExecInitResult"}, {"label": "\u5185\u5b58\u673a\u5236", "value": "unclassified"}], "memory": {"evidence": [{"url": "https://ftp.postgresql.org/pub/source/v18.6/postgresql-18.6.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "32410ec3fc47eea05d944207a7abbf25625029ca8480f5eafee927f896578b9b", "archive_sha256": "555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f"}], "mechanism": "unclassified", "description": "\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002", "source_notes": []}, "tables": [{"key": "explain-labels", "rows": [{"label": "Result", "identity": "Result"}], "title": "\u672c\u6784\u5efa\u4e2d\u7684 EXPLAIN \u6807\u7b7e", "columns": [{"key": "label", "label": "\u6587\u672c\u683c\u5f0f\u6807\u7b7e"}, {"key": "identity", "label": "\u7ed3\u6784\u5316\u8282\u70b9\u6807\u8bc6"}]}], "related": [{"url": "/wiki/sql/explain/?v=18", "label": "EXPLAIN"}, {"url": "/docs/18/using-explain.html", "label": "\u4f7f\u7528 EXPLAIN"}, {"url": "/docs/18/parallel-plans.html", "label": "\u5e76\u884c\u8ba1\u5212"}], "release": {"ref": "PostgreSQL 18.6 source archive", "label": "18.6", "major": "18", "channel": "stable", "revision": "555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f", "source_url": "https://ftp.postgresql.org/pub/source/v18.6/postgresql-18.6.tar.bz2", "source_snapshot_utc": ""}, "sources": [{"url": "https://ftp.postgresql.org/pub/source/v18.6/postgresql-18.6.tar.bz2", "line": 1379, "path": "src/backend/commands/explain.c", "label": "src/backend/commands/explain.c:1379", "sha256": "34c86d6070224a0e981efef51f79101d6d505e5874f1684ace183034bab14bb4", "archive_sha256": "555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f"}, {"url": "https://ftp.postgresql.org/pub/source/v18.6/postgresql-18.6.tar.bz2", "line": 166, "path": "src/backend/executor/execProcnode.c", "label": "src/backend/executor/execProcnode.c:166", "sha256": "f8a06a3f539077249b20664b2812433db6d7bd12b2c0ca633525db43d06f112a", "archive_sha256": "555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f"}, {"url": "https://ftp.postgresql.org/pub/source/v18.6/postgresql-18.6.tar.bz2", "path": "src/backend/executor/nodeResult.c", "label": "src/backend/executor/nodeResult.c", "sha256": "32410ec3fc47eea05d944207a7abbf25625029ca8480f5eafee927f896578b9b", "archive_sha256": "555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f"}, {"url": "https://ftp.postgresql.org/pub/source/v18.6/postgresql-18.6.tar.bz2", "path": "src/include/nodes/plannodes.h", "label": "src/include/nodes/plannodes.h", "sha256": "52422b327a8049fbbb20d8b96008a0fc0a6fafa60f7eff3c695d5b2e83830120", "archive_sha256": "555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f"}, {"url": "https://pg.center/docs/18/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 18.6 \u00b7 using-explain", "sha256": "60040c30180093418a0affe56dd27dff9df2504b705b38039589e458bf5c31ed", "language": "en", "original_url": "/docs/18/using-explain.html#USING-EXPLAIN-BASICS"}, {"url": "https://pg.center/docs/18/using-explain.html#USING-EXPLAIN-ANALYZE", "path": "using-explain.html", "label": "PostgreSQL 18.6 \u00b7 using-explain", "sha256": "60040c30180093418a0affe56dd27dff9df2504b705b38039589e458bf5c31ed", "language": "en", "original_url": "/docs/18/using-explain.html#USING-EXPLAIN-ANALYZE"}, {"url": "https://pg.center/docs/18/parallel-plans.html#PARALLEL-PLANS", "path": "parallel-plans.html", "label": "PostgreSQL 18.6 \u00b7 parallel-plans", "sha256": "62207d207bead82b01b59dc119c4f95856f08655cc11d4699a05a40867ed2070", "language": "en", "original_url": "/docs/18/parallel-plans.html#PARALLEL-PLANS"}], "node_tag": "T_Result", "sections": [{"title": "EXPLAIN \u540d\u79f0\u4e0e\u5c5e\u6027", "paragraphs": ["\u7ed3\u6784\u5316\u683c\u5f0f\u4f7f\u7528\u4e0a\u8ff0 Node Type\u3002\u6587\u672c\u683c\u5f0f\u540d\u79f0\u8fd8\u53ef\u80fd\u5305\u542b\u64cd\u4f5c\u3001\u7b56\u7565\u3001\u8fde\u63a5\u7c7b\u578b\u3001\u626b\u63cf\u65b9\u5411\u6216\u805a\u5408\u9636\u6bb5\u5c5e\u6027\u3002", "\u6b64\u6e90\u7801\u8bb0\u5f55\u7684\u6587\u672c\u540d\u79f0\uff1aResult.", "\u5e76\u884c\u611f\u77e5\u4e0e\u5e76\u884c\u5b89\u5168\u662f\u4e0d\u540c\u7684\u8ba1\u5212\u5c5e\u6027\u3002\u5728\u5e76\u884c\u5de5\u4f5c\u8fdb\u7a0b\u5185\u8fd0\u884c\u7684\u8282\u70b9\u4e0d\u4e00\u5b9a\u662f\u5e76\u884c\u611f\u77e5\u8282\u70b9\u3002"]}, {"title": "\u5185\u5b58\u4e0e\u4e34\u65f6\u5b58\u50a8", "paragraphs": ["\u672c\u6b21\u62bd\u53d6\u4e0d\u4e3a\u6b64\u8282\u70b9\u8bbe\u5b9a\u7edf\u4e00\u7684\u5185\u5b58\u4e0a\u9650\u6216\u843d\u76d8\u7b56\u7565\u3002\u8bf7\u67e5\u770b\u540c\u4e00\u6784\u5efa\u7684\u5b9e\u73b0\u3001\u76f8\u5173\u8868\u8fbe\u5f0f\u6216\u63d0\u4f9b\u65b9\u3002"]}, {"title": "\u5e76\u884c\u6267\u884c\u4e0e\u8fd0\u884c\u4fe1\u606f\u91c7\u96c6", "paragraphs": ["\u4ee5\u4e0b\u6e90\u7801\u56de\u8c03\u53ef\u4ee5\u534f\u8c03\u6267\u884c\u6216\u6536\u96c6\u5de5\u4f5c\u8fdb\u7a0b\u7684\u6d4b\u91cf\u6570\u636e\u3002\u56de\u8c03\u5b58\u5728\u4e0d\u4ee3\u8868\u8be5\u8282\u70b9\u666e\u904d\u652f\u6301\u5171\u4eab\u5e76\u884c\u626b\u63cf\u6216\u5171\u4eab\u72b6\u6001\u3002", "\u6b64\u6784\u5efa\u7684\u56de\u8c03\uff1anone extracted from this node implementation."]}, {"title": "\u540c\u7248\u672c\u624b\u518c\u8bf4\u660e", "paragraphs": ["rows \u5bb9\u6613\u4ee4\u4eba\u8bef\u89e3\uff1a\u5b83\u8868\u793a\u8282\u70b9\u8f93\u51fa\u7684\u884c\u6570\uff0c\u800c\u4e0d\u662f\u5904\u7406\u6216\u626b\u63cf\u7684\u884c\u6570\u3002\u8282\u70b9\u5e94\u7528 WHERE \u6761\u4ef6\u7b5b\u9009\u540e\uff0c\u8f93\u51fa\u884c\u6570\u901a\u5e38\u5c0f\u4e8e\u626b\u63cf\u884c\u6570\u3002\u7406\u60f3\u60c5\u51b5\u4e0b\uff0c\u9876\u5c42 rows \u4f30\u8ba1\u5e94\u63a5\u8fd1\u67e5\u8be2\u5b9e\u9645\u8fd4\u56de\u3001\u66f4\u65b0\u6216\u5220\u9664\u7684\u884c\u6570\u3002", "\u4e0e\u666e\u901a\u6392\u5e8f\u76f8\u6bd4\uff0c\u589e\u91cf\u6392\u5e8f\u53ef\u5728\u6574\u4e2a\u7ed3\u679c\u96c6\u5c1a\u672a\u6392\u5b8c\u65f6\u5c31\u8fd4\u56de\u5143\u7ec4\uff0c\u5c24\u5176\u6709\u5229\u4e8e\u4f18\u5316\u5e26 LIMIT \u7684\u67e5\u8be2\u3002\u5b83\u8fd8\u53ef\u80fd\u51cf\u5c11\u5185\u5b58\u7528\u91cf\u548c\u6392\u5e8f\u6ea2\u5199\u78c1\u76d8\u7684\u6982\u7387\uff0c\u4f46\u4ee3\u4ef7\u662f\u5c06\u7ed3\u679c\u96c6\u62c6\u6210\u591a\u4e2a\u6392\u5e8f\u6279\u6b21\u6240\u5e26\u6765\u7684\u989d\u5916\u5f00\u9500\u3002", "\u5728\u8fd9\u4e2a\u8ba1\u5212\u4e2d\uff0c\u6709\u4e00\u4e2a\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\uff0c\u5b83\u7684\u4e24\u4e2a\u8f93\u5165\uff0c\u4e5f\u5c31\u662f\u4e24\u4e2a\u5b50\u8282\u70b9\uff0c\u90fd\u662f\u8868\u626b\u63cf\u3002\u8282\u70b9\u6458\u8981\u884c\u7684\u7f29\u8fdb\u53cd\u6620\u4e86\u8ba1\u5212\u6811\u7ed3\u6784\u3002\u8fde\u63a5\u7684\u7b2c\u4e00\u4e2a\u5b50\u8282\u70b9\uff0c\u4e5f\u5c31\u662f \u201c \u5916\u4fa7 \u201d \u5b50\u8282\u70b9\uff0c\u662f\u4e00\u4e2a\u4e0e\u524d\u9762\u89c1\u8fc7\u7684\u4f4d\u56fe\u626b\u63cf\u7c7b\u4f3c\u7684\u8282\u70b9\u3002\u5b83\u7684\u4ee3\u4ef7\u548c\u884c\u8ba1\u6570\u4e0e SELECT ... WHERE unique1 < 10 \u5f97\u5230\u7684\u7ed3\u679c\u76f8\u540c\uff0c\u56e0\u4e3a WHERE \u5b50\u53e5 unique1 < 10 \u6b63\u662f\u5728\u8be5\u8282\u70b9\u4e0a\u5e94\u7528\u7684\u3002 t1.unique2 = t2.unique2 \u5b50\u53e5\u6b64\u65f6\u8fd8\u65e0\u5173\uff0c\u56e0\u6b64\u4e0d\u4f1a\u5f71\u54cd\u5916\u4fa7\u626b\u63cf\u7684\u884c\u8ba1\u6570\u3002\u5d4c\u5957\u5faa\u73af\u8fde\u63a5\u8282\u70b9\u4f1a\u5bf9\u4ece\u5916\u4fa7\u5b50\u8282\u70b9\u5f97\u5230\u7684\u6bcf\u4e00\u884c\u6267\u884c\u4e00\u6b21\u7b2c\u4e8c\u4e2a\uff0c\u4e5f\u5c31\u662f \u201c \u5185\u4fa7 \u201d \u5b50\u8282\u70b9\u3002\u5f53\u524d\u5916\u4fa7\u884c\u4e2d\u7684\u5217\u503c\u53ef\u4ee5\u4ee3\u5165\u5185\u4fa7\u626b\u63cf\uff1b\u8fd9\u91cc\u5916\u4fa7\u884c\u7684 t1.unique2 \u503c\u53ef\u7528\uff0c\u56e0\u6b64\u5f97\u5230\u7684\u8ba1\u5212\u548c\u4ee3\u4ef7\u4e0e\u524d\u9762\u770b\u5230\u7684\u7b80\u5355 SELECT ... WHERE t2.unique2 = constant \u60c5\u5f62\u7c7b\u4f3c\u3002\uff08\u7531\u4e8e\u9884\u671f\u5728\u5bf9 t2 \u53cd\u590d\u6267\u884c\u7d22\u5f15\u626b\u63cf\u671f\u95f4\u4f1a\u53d1\u751f\u7f13\u5b58\u547d\u4e2d\uff0c\u4f30\u8ba1\u4ee3\u4ef7\u5b9e\u9645\u4e0a\u6bd4\u524d\u9762\u770b\u5230\u7684\u7565\u4f4e\u4e00\u4e9b\u3002\uff09\u968f\u540e\uff0c\u5faa\u73af\u8282\u70b9\u7684\u4ee3\u4ef7\u5efa\u7acb\u5728\u5916\u4fa7\u626b\u63cf\u4ee3\u4ef7\u4e4b\u4e0a\uff0c\u518d\u52a0\u4e0a\u6bcf\u4e2a\u5916\u4fa7\u884c\u90fd\u8981\u6267\u884c\u4e00\u6b21\u5185\u4fa7\u626b\u63cf\u7684\u4ee3\u4ef7\uff08\u8fd9\u91cc\u662f 10 * 7.90\uff09\uff0c\u4ee5\u53ca\u5c11\u91cf\u8fde\u63a5\u5904\u7406\u7684 CPU \u65f6\u95f4\u3002", "\u8fd9\u4e2a\u523b\u610f\u6784\u9020\u7684\u793a\u4f8b\u8bf4\u660e\u4e86\u4e24\u70b9\uff1a\u5916\u5c42\u8ba1\u5212\u7684\u503c\u53ef\u4f20\u5165\u5b50\u8ba1\u5212\uff08\u8fd9\u91cc\u4f20\u5165 t.four\uff09\uff0c\u5b50\u67e5\u8be2\u7ed3\u679c\u4e5f\u53ef\u4f9b\u5916\u5c42\u8ba1\u5212\u4f7f\u7528\u3002EXPLAIN \u7528 (subplan_name).col N \u4e00\u7c7b\u8bb0\u53f7\u663e\u793a\u8fd9\u4e9b\u7ed3\u679c\u503c\uff0c\u8868\u793a\u5b50 SELECT \u7684\u7b2c N \u4e2a\u8f93\u51fa\u5217\u3002", "\u53ef\u4f7f\u7528 EXPLAIN \u7684 ANALYZE \u9009\u9879\u68c0\u67e5\u89c4\u5212\u5668\u4f30\u7b97\u662f\u5426\u51c6\u786e\u3002\u4f7f\u7528\u6b64\u9009\u9879\u65f6\uff0cEXPLAIN \u4f1a\u5b9e\u9645\u6267\u884c\u67e5\u8be2\uff0c\u7136\u540e\u663e\u793a\u6bcf\u4e2a\u8ba1\u5212\u8282\u70b9\u7d2f\u8ba1\u7684\u771f\u5b9e\u884c\u6570\u548c\u771f\u5b9e\u8fd0\u884c\u65f6\u95f4\uff0c\u4ee5\u53ca\u666e\u901a EXPLAIN \u6240\u663e\u793a\u7684\u4f30\u7b97\u503c\u3002\u4f8b\u5982\uff0c\u53ef\u80fd\u5f97\u5230\u5982\u4e0b\u7ed3\u679c\uff1a", "\u7531\u4e8e\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u5c06\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u6267\u884c\u5230\u5e95\uff0c\u56e0\u6b64\u4e0d\u80fd\u7b80\u5355\u5730\u62ff\u4e00\u4e2a\u666e\u901a\u67e5\u8be2\u8ba1\u5212\u5e76\u8ba9\u591a\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u540c\u65f6\u8fd0\u884c\u3002\u90a3\u6837\u6bcf\u4e2a\u5de5\u4f5c\u8fdb\u7a0b\u90fd\u4f1a\u751f\u6210\u5b8c\u6574\u8f93\u51fa\u7ed3\u679c\u96c6\u7684\u4e00\u4efd\u526f\u672c\uff0c\u6240\u4ee5\u67e5\u8be2\u4e0d\u4ec5\u4e0d\u4f1a\u6bd4\u5e73\u5e38\u66f4\u5feb\uff0c\u53cd\u800c\u4f1a\u4ea7\u751f\u9519\u8bef\u7ed3\u679c\u3002\u76f8\u53cd\uff0c\u8ba1\u5212\u7684\u5e76\u884c\u90e8\u5206\u5fc5\u987b\u662f\u67e5\u8be2\u4f18\u5316\u5668\u5185\u90e8\u6240\u8bf4\u7684 \u90e8\u5206\u8ba1\u5212 \uff1b\u4e5f\u5c31\u662f\u8bf4\uff0c\u5b83\u5fc5\u987b\u88ab\u6784\u9020\u4e3a\u4f7f\u6267\u884c\u8be5\u8ba1\u5212\u7684\u6bcf\u4e2a\u8fdb\u7a0b\u53ea\u751f\u6210\u8f93\u51fa\u884c\u7684\u4e00\u4e2a\u5b50\u96c6\uff0c\u5e76\u4e14\u4fdd\u8bc1\u6bcf\u4e00\u6761\u6240\u9700\u8f93\u51fa\u884c\u90fd\u6070\u597d\u7531\u67d0\u4e2a\u534f\u4f5c\u8fdb\u7a0b\u751f\u6210\u4e00\u6b21\u3002\u4e00\u822c\u6765\u8bf4\uff0c\u8fd9\u610f\u5473\u7740\u67e5\u8be2\u9a71\u52a8\u8868\u4e0a\u7684\u626b\u63cf\u5fc5\u987b\u662f\u5e76\u884c\u611f\u77e5\u626b\u63cf\u3002"]}, {"title": "\u672c\u7248\u624b\u518c\u4e2d\u7684\u793a\u4f8b", "blocks": [{"code": "EXPLAIN VERBOSE SELECT unique1\nFROM tenk1 t1 WHERE t1.ten = (SELECT (random() * 10)::integer);\n\n                             QUERY PLAN\n--------------------------------------------------------------------\n Seq Scan on public.tenk1 t1  (cost=0.02..470.02 rows=1000 width=4)\n   Output: t1.unique1\n   Filter: (t1.ten = (InitPlan 1).col1)\n   InitPlan 1\n     ->  Result  (cost=0.00..0.02 rows=1 width=4)\n           Output: ((random() * '10'::double precision))::integer", "source": {"url": "/docs/18/using-explain.html#USING-EXPLAIN-BASICS", "path": "using-explain.html", "label": "PostgreSQL 18.6 \u00b7 using-explain", "sha256": "60040c30180093418a0affe56dd27dff9df2504b705b38039589e458bf5c31ed"}, "paragraphs": ["\u793a\u4f8b\u6458\u81ea PostgreSQL 18.6 \u624b\u518c\uff1b\u672c\u767e\u79d1\u672a\u5b9e\u9645\u6267\u884c\u6b64\u793a\u4f8b\u3002", "\u5982\u679c\u5b50 SELECT \u4e0d\u4ec5\u4e0d\u5f15\u7528\u5916\u5c42\u67e5\u8be2\u7684\u4efb\u4f55\u53d8\u91cf\uff0c\u800c\u4e14\u6700\u591a\u53ea\u4f1a\u8fd4\u56de\u4e00\u884c\uff0c\u90a3\u4e48\u5b83\u8fd8\u53ef\u80fd\u88ab\u5b9e\u73b0\u6210\u4e00\u4e2a \u521d\u59cb\u8ba1\u5212 \uff1a"]}]}, {"title": "\u6267\u884c\u5668\u5b9e\u73b0\u8bf4\u660e", "paragraphs": ["nodeResult.c\uff1a\u652f\u6301\u9700\u8981\u7279\u6b8a\u4ee3\u7801\u7684\u5e38\u91cf\u8282\u70b9\u3002", "Result \u8282\u70b9\u7528\u4e8e\u4e0d\u626b\u63cf\u4efb\u4f55\u5173\u7cfb\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\uff08\u8bf7\u8bb0\u4f4f\uff0cINSERT \u6216 UPDATE \u9700\u8981\u4e00\u68f5\u751f\u6210\u65b0\u884c\u7684\u8ba1\u5212\u6811\u3002\uff09", "Result \u8282\u70b9\u4e5f\u7528\u4e8e\u4f18\u5316\u5e26\u6709\u5e38\u91cf\u6761\u4ef6\uff08\u5373\u4e0d\u4f9d\u8d56\u626b\u63cf\u6570\u636e\u7684\u6761\u4ef6\uff09\u7684\u67e5\u8be2\uff0c\u4f8b\u5982\uff1a", "\u8fd0\u884c\u65f6\uff0cResult \u8282\u70b9\u53ea\u8ba1\u7b97\u4e00\u6b21\u5e38\u91cf\u6761\u4ef6\uff0cEXPLAIN \u5c06\u5176\u663e\u793a\u4e3a One-Time Filter\u3002\u5982\u679c\u6761\u4ef6\u4e3a\u5047\uff0c\u65e0\u9700\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u4fbf\u53ef\u8fd4\u56de\u7a7a\u7ed3\u679c\u96c6\uff1b\u5982\u679c\u4e3a\u771f\uff0c\u5219\u6b63\u5e38\u8fd0\u884c\u53d7\u63a7\u8ba1\u5212\u5e76\u4f20\u56de\u7ed3\u679c\u3002"]}, {"code": "case T_Result:\n\t\t\tpname = sname = \"Result\";\n\t\t\tbreak;", "title": "\u6838\u5fc3\u6e90\u7801\u4e2d\u7684 EXPLAIN \u6807\u8bc6"}], "strategies": [], "description": ["\u8ba1\u7b97\u6295\u5f71\u548c\u53ef\u9009\u7684\u4e00\u6b21\u6027\u6761\u4ef6\uff0c\u53ef\u5e26\u6216\u4e0d\u5e26\u8f93\u5165\u8ba1\u5212\u3002"], "localization": {"status": "complete", "sources": [{"url": "/docs/18/parallel-plans.html", "method": "same-major semantic node", "sha256": "7fa104623c0b4cd22acf0929e40518fbed8fe368af3e3b124cf693bd7ab69f0c", "language": "zh", "matched_nodes": ["#PARALLEL-PLANS/p[2]"]}, {"url": "/docs/18/using-explain.html", "method": "same-major semantic node", "sha256": "b8835ec9adbc70ec150667a6b5443f8d298222dc0cc8c2bd1abb1c1d64895904", "language": "zh", "matched_nodes": ["#USING-EXPLAIN/div[7]/p[40]", "#USING-EXPLAIN/div[7]/p[64]"]}], "language": "zh", "original_text": {"/versions/18/description/0": "Evaluates a projection and an optional one-time condition, with or without an input plan.", "/versions/18/facts/0/label": "Core node tag", "/versions/18/facts/1/label": "Structured EXPLAIN Node Type", "/versions/18/facts/2/label": "Inputs", "/versions/18/facts/2/value": "Optional child plan", "/versions/18/facts/3/label": "Output", "/versions/18/facts/3/value": "Projected tuples", "/versions/18/facts/4/label": "Executor initializer", "/versions/18/facts/5/label": "Memory mechanism", "/versions/18/tables/0/title": "EXPLAIN labels in this source build", "/versions/18/related/1/label": "Using EXPLAIN", "/versions/18/related/2/label": "Parallel plans", "/versions/18/sections/0/title": "EXPLAIN names and attributes", "/versions/18/sections/1/title": "Memory and temporary storage", "/versions/18/sections/2/title": "Parallel execution and instrumentation", "/versions/18/sections/3/title": "Same-version manual discussion", "/versions/18/sections/4/title": "Examples from this manual build", "/versions/18/sections/5/title": "Executor implementation notes", "/versions/18/sections/6/title": "EXPLAIN identity in core source", "/versions/18/memory/description": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/18/sections/0/paragraphs/0": "Structured formats use the Node Type above. Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.", "/versions/18/sections/0/paragraphs/1": "Text names recorded by this source: Result.", "/versions/18/sections/0/paragraphs/2": "Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node.", "/versions/18/sections/1/paragraphs/0": "This extraction does not assign a universal memory limit or spill policy to this node. Inspect the same-build implementation and its expressions or provider.", "/versions/18/sections/2/paragraphs/0": "The source callbacks below can coordinate execution or collect worker instrumentation. Their presence is not a blanket claim that this node supports a shared parallel scan or shared state.", "/versions/18/sections/2/paragraphs/1": "Callbacks in this build: none extracted from this node implementation.", "/versions/18/sections/3/paragraphs/0": "The rows value is a little tricky because it is not the number of rows processed or scanned by the plan node, but rather the number emitted by the node. This is often less than the number scanned, as a result of filtering by any WHERE -clause conditions that are being applied at the node. Ideally the top-level rows estimate will approximate the number of rows actually returned, updated, or deleted by the query.", "/versions/18/sections/3/paragraphs/1": "Compared to regular sorts, sorting incrementally allows returning tuples before the entire result set has been sorted, which particularly enables optimizations with LIMIT queries. It may also reduce memory usage and the likelihood of spilling sorts to disk, but it comes at the cost of the increased overhead of splitting the result set into multiple sorting batches.", "/versions/18/sections/3/paragraphs/2": "In this plan, we have a nested-loop join node with two table scans as inputs, or children. The indentation of the node summary lines reflects the plan tree structure. The join's first, or \u201c outer \u201d , child is a bitmap scan similar to those we saw before. Its cost and row count are the same as we'd get from SELECT ... WHERE unique1 < 10 because we are applying the WHERE clause unique1 < 10 at that node. The t1.unique2 = t2.unique2 clause is not relevant yet, so it doesn't affect the row count of the outer scan. The nested-loop join node will run its second, or \u201c inner \u201d child once for each row obtained from the outer child. Column values from the current outer row can be plugged into the inner scan; here, the t1.unique2 value from the outer row is available, so we get a plan and costs similar to what we saw above for a simple SELECT ... WHERE t2.unique2 = constant case. (The estimated cost is actually a bit lower than what was seen above, as a result of caching that's expected to occur during the repeated index scans on t2 .) The costs of the loop node are then set on the basis of the cost of the outer scan, plus one repetition of the inner scan for each outer row (10 * 7.90, here), plus a little CPU time for join processing.", "/versions/18/sections/3/paragraphs/3": "This rather artificial example serves to illustrate a couple of points: values from the outer plan level can be passed down into a subplan (here, t.four is passed down) and the results of the sub-select are available to the outer plan. Those result values are shown by EXPLAIN with notations like ( subplan_name ).col N , which refers to the N 'th output column of the sub- SELECT .", "/versions/18/sections/3/paragraphs/4": "It is possible to check the accuracy of the planner's estimates by using EXPLAIN 's ANALYZE option. With this option, EXPLAIN actually executes the query, and then displays the true row counts and true run time accumulated within each plan node, along with the same estimates that a plain EXPLAIN shows. For example, we might get a result like this:", "/versions/18/sections/3/paragraphs/5": "Because each worker executes the parallel portion of the plan to completion, it is not possible to simply take an ordinary query plan and run it using multiple workers. Each worker would produce a full copy of the output result set, so the query would not run any faster than normal but would produce incorrect results. Instead, the parallel portion of the plan must be what is known internally to the query optimizer as a partial plan ; that is, it must be constructed so that each process that executes the plan will generate only a subset of the output rows in such a way that each required output row is guaranteed to be generated by exactly one of the cooperating processes. Generally, this means that the scan on the driving table of the query must be a parallel-aware scan.", "/versions/18/sections/5/paragraphs/0": "nodeResult.c support for constant nodes needing special code.", "/versions/18/sections/5/paragraphs/1": "Result nodes are used in queries where no relations are scanned. Examples of such queries are:", "/versions/18/sections/5/paragraphs/2": "(Remember that in an INSERT or UPDATE, we need a plan tree that generates the new rows.)", "/versions/18/sections/5/paragraphs/3": "Result nodes are also used to optimise queries with constant qualifications (ie, quals that do not depend on the scanned data), such as:", "/versions/18/sections/5/paragraphs/4": "At runtime, the Result node evaluates the constant qual once, which is shown by EXPLAIN as a One-Time Filter. If it's false, we can return an empty result set without running the controlled plan at all. If it's true, we run the controlled plan normally and pass back the results.", "/versions/18/tables/0/columns/0/label": "Text-format label", "/versions/18/tables/0/columns/1/label": "Structured node identity", "/versions/18/sections/4/blocks/0/paragraphs/0": "Example copied from the PostgreSQL 18.6 manual; it was not executed for this collection.", "/versions/18/sections/4/blocks/0/paragraphs/1": "If, in addition to not referencing any variables of the outer query, the sub- SELECT cannot return more than one row, it may instead be implemented as an initplan :"}, "fallback_fields": [], "source_language": "en", "original_snapshot_sha256": "083472e89b0d77b0d449941552fb54b7f3e90678fbd15e8c731429116e63db35"}, "evidence_kind": "source and documentation", "explain_names": ["Result"], "partial_modes": [], "comparison_data": {"node_tag": "T_Result", "strategies": [], "text_names": ["Result"], "initializer": "ExecInitResult", "partial_modes": [], "memory_mechanism": "unclassified", "parallel_callbacks": []}, "comparison_hash": "7d9e21f5e91321228505ba502e7faa5b9ebdda5ba4d71b8a9b97571a1f87b5f5", "explain_prefixes": ["Parallel", "Async"], "runtime_verified": false, "source_inventory": {"explain": "src/backend/commands/explain.c", "executor": "src/backend/executor/execProcnode.c", "implementation": "src/backend/executor/nodeResult.c"}, "parallel_callbacks": []}, "comparison": {"left": "17", "right": "18", "status": "unchanged", "diff": ""}}