{"Entry":{"collection":"plan","key":"gather-merge","name":"Gather Merge","aliases":["Gather Merge","GatherMerge","T_GatherMerge"],"metadata":{"aliases":["Gather Merge","GatherMerge","T_GatherMerge"],"category":"Parallelism","content_hash":"60a783e74d1850b9432b5b97c5799704bd4e9d917faa54bb6fb742f37bf78f8d","derived_content_hash":"d444561c3b7cd698a7cbe68538401d7475fe4958abbc15efaede535d4cd7f2c2","imported_at":"2026-09-30T00:40:44.19904+08:00","name":"Gather Merge","name_zh":"GatherMerge","slug":"gather-merge","summary":"Merges ordered tuple streams from parallel workers and any participating leader execution."}},"Definition":{"Collection":"plan","Key":"gather-merge","SourceDatabase":"center","Version":"18","SourceTable":"plan_node","SourceKey":"gather-merge","SourceRevision":"555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f","Facts":{"comparison_data":{"initializer":"ExecInitGatherMerge","memory_mechanism":"unclassified","node_tag":"T_GatherMerge","parallel_callbacks":[],"partial_modes":[],"strategies":[],"text_names":["Gather Merge"]},"comparison_hash":"7a1c97656626af0791de9743def719924b5c292f47f0634adc2b0e6e4fd2ad21","description":["Merges ordered tuple streams from parallel workers and any participating leader execution."],"description_zh":"归并并行工作进程以及参与执行的领导进程的有序输出流。","description_zh_html":"\u003cp\u003e归并并行工作进程以及参与执行的领导进程的有序输出流。\u003c/p\u003e\u003cp\u003e核心节点标识：\u003ccode\u003eT_GatherMerge\u003c/code\u003e；EXPLAIN 名称：\u003ccode\u003eGather Merge\u003c/code\u003e。\u003c/p\u003e\u003cp\u003e本版本源码中的并行执行或观测回调：该节点实现中未提取到此类回调。回调的存在不表示该节点必然支持共享并行扫描；在并行工作进程中执行也不等于具有并行感知能力。\u003c/p\u003e\u003ch3\u003e同版本中文手册节选\u003c/h3\u003e\u003cp\u003e\n\u003cspan class=\"productname\"\u003ePostgreSQL\u003c/span\u003e 通过分两个阶段进行聚合来支持并行聚合。首先，每个参与查询并行部分的进程执行一个聚合步骤，为该进程所见到的每个分组产生一个部分结果。这在计划中体现为一个 \u003ccode class=\"literal\"\u003ePartial Aggregate\u003c/code\u003e 节点。然后，部分结果通过 \u003ccode class=\"literal\"\u003eGather\u003c/code\u003e 或 \u003ccode class=\"literal\"\u003eGather Merge\u003c/code\u003e 传送给领导者。最后，领导者会把来自所有工作进程的结果再次聚合，以产生最终结果。这在计划中体现为一个 \u003ccode class=\"literal\"\u003eFinalize Aggregate\u003c/code\u003e 节点。\n  \u003c/p\u003e\u003cp\u003e\n    由于 \u003ccode class=\"literal\"\u003eFinalize Aggregate\u003c/code\u003e 节点运行在领导者进程上，因此对于那些相对于输入行数会产生较多分组的查询，查询规划器会认为它不太有利。例如，在最坏情况下，\u003ccode class=\"literal\"\u003eFinalize Aggregate\u003c/code\u003e 节点看到的分组数可能与所有工作进程在 \u003ccode class=\"literal\"\u003ePartial Aggregate\u003c/code\u003e 阶段看到的输入行数一样多。对于这种情况，使用并行聚合显然不会带来性能收益。查询规划器会在规划过程中考虑这一点，因此在这种场景下不太可能选择并行聚合。\n  \u003c/p\u003e\u003cp\u003e\n    并行聚合并非在所有情况下都受支持。每个聚合都必须是\u003ca class=\"link\" href=\"/zh/docs/18/parallel-safety.html\"\u003e并行安全\u003c/a\u003e的，并且必须具有合并函数。如果该聚合具有类型为 \u003ccode class=\"literal\"\u003einternal\u003c/code\u003e 的转移状态，那么它还必须具有序列化和反序列化函数。更多细节请参见 \u003ca class=\"xref\" href=\"/zh/docs/18/sql-createaggregate.html\"\u003e\u003cspan class=\"refentrytitle\"\u003eCREATE AGGREGATE\u003c/span\u003e\u003c/a\u003e。如果任何聚合函数调用包含 \u003ccode class=\"literal\"\u003eDISTINCT\u003c/code\u003e 或 \u003ccode class=\"literal\"\u003eORDER BY\u003c/code\u003e 子句，则不支持并行聚合。对于有序集聚合，或者当查询涉及 \u003ccode class=\"literal\"\u003eGROUPING SETS\u003c/code\u003e 时，也不支持并行聚合。只有当查询涉及的所有连接也都属于计划并行部分时，才能使用并行聚合。\n  \u003c/p\u003e\u003cp\u003e\u003ca href=\"/zh/docs/18/parallel-plans.html#PARALLEL-AGGREGATION\"\u003e查看完整中文手册与上下文\u003c/a\u003e。\u003c/p\u003e\u003cp\u003e本页开头的中文说明为 PG.CENTER 对编辑说明的翻译；手册节选保留对应版本中文文档原文。源码信息及手册示例不代表重新进行过运行测试。\u003c/p\u003e","evidence_kind":"source and documentation","explain_names":["Gather Merge"],"explain_prefixes":["Parallel","Async"],"facts":[{"label":"Core node tag","value":"T_GatherMerge"},{"label":"Structured EXPLAIN Node Type","value":"Gather Merge"},{"label":"Inputs","value":"One ordered parallel child plan"},{"label":"Output","value":"Merged ordered tuples"},{"label":"Executor initializer","value":"ExecInitGatherMerge"},{"label":"Memory mechanism","value":"unclassified"}],"facts_zh":[{"label":"核心节点标签","value":"T_GatherMerge"},{"label":"结构化 EXPLAIN 节点类型","value":"Gather Merge"},{"label":"输入","value":"一个有序并行子计划"},{"label":"输出","value":"按顺序归并的元组"},{"label":"执行器初始化函数","value":"ExecInitGatherMerge"},{"label":"内存机制","value":"unclassified"}],"memory":{"description":"This extraction does not assign a universal memory limit or spill policy to this node. 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