{"Entry":{"collection":"plan","key":"bitmapor","name":"BitmapOr","aliases":["BitmapOr","T_BitmapOr"],"metadata":{"aliases":["BitmapOr","T_BitmapOr"],"category":"Bitmap","content_hash":"7f9182fb8e68ec6e2d9cef66a3b2e1134d354dc29d296ee25b10a06ecfec7c3f","derived_content_hash":"d3e725a02e8a5e824be2e73372f8aaf6152c4b722740a2d79d737e0acf04255e","imported_at":"2026-09-30T00:40:44.03129+08:00","name":"BitmapOr","name_zh":"BitmapOr","slug":"bitmapor","summary":"Unions bitmaps produced by its child plans."}},"Definition":{"Collection":"plan","Key":"bitmapor","SourceDatabase":"center","Version":"18","SourceTable":"plan_node","SourceKey":"bitmapor","SourceRevision":"555610c24d53e4316da5b7d3fc25c279d96856d5e0e23ee308c328c5fa881d9f","Facts":{"comparison_data":{"initializer":"ExecInitBitmapOr","memory_mechanism":"bitmap-lossification","node_tag":"T_BitmapOr","parallel_callbacks":[],"partial_modes":[],"strategies":[],"text_names":["BitmapOr"]},"comparison_hash":"c0ca503a6029c37ec720213dcdc3094997eb194d4920da68f94a7420d3e8f1d2","description":["Unions bitmaps produced by its child plans."],"description_zh":"对各子计划生成的位图求并集。","description_zh_html":"\u003cp\u003e对各子计划生成的位图求并集。\u003c/p\u003e\u003cp\u003e核心节点标识：\u003ccode\u003eT_BitmapOr\u003c/code\u003e；EXPLAIN 名称：\u003ccode\u003eBitmapOr\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\u003ccode class=\"command\"\u003eEXPLAIN ANALYZE\u003c/code\u003e 测得的运行时间，可能以两种重要方式偏离同一查询的正常执行时间。第一，由于不会向客户端传递任何输出行，因此网络传输开销不会被计入。除非指定了 \u003ccode class=\"literal\"\u003eSERIALIZE\u003c/code\u003e，I/O 转换开销同样也不会被计入。第二，\u003ccode class=\"command\"\u003eEXPLAIN ANALYZE\u003c/code\u003e 附加的测量开销本身可能相当可观，尤其是在操作系统调用 \u003ccode class=\"function\"\u003egettimeofday()\u003c/code\u003e 较慢的机器上。可以使用 \u003ca class=\"xref\" href=\"/zh/docs/18/pgtesttiming.html\"\u003e\u003cspan class=\"refentrytitle\"\u003e\u003cspan class=\"application\"\u003epg_test_timing\u003c/span\u003e\u003c/span\u003e\u003c/a\u003e 工具来测量系统上的计时开销。\n   \u003c/p\u003e\u003cp\u003e\n    不应将 \u003ccode class=\"command\"\u003eEXPLAIN\u003c/code\u003e 结果外推到与实际测试场景差异很大的情况。例如，在一个很小的表上得到的结果，不能假定也适用于大型表。规划器的代价估计不是线性的，因此它可能会为更大或更小的表选择不同的计划。一个极端示例是：对于只占用一个磁盘页的表，无论索引是否可用，几乎总会得到顺序扫描计划。规划器认识到，无论如何处理该表都需要一次磁盘页读取，因此再额外读取页面去查看索引并没有价值。（前面的 \u003ccode class=\"literal\"\u003epolygon_tbl\u003c/code\u003e 示例已经展示过这种情况。）\n   \u003c/p\u003e\u003cp\u003e\n    在某些情况下，实际值和估计值不会很好地对应，但这并不表示出现了问题。其中一种情况是，计划节点的执行会被 \u003ccode class=\"literal\"\u003eLIMIT\u003c/code\u003e 或类似效果提前截断。例如，在前面用过的 \u003ccode class=\"literal\"\u003eLIMIT\u003c/code\u003e 查询中：\n\n\u003c/p\u003e\u003cp\u003e\n\n    Index Scan 节点的估计代价和行计数显示得像是它会运行到结束一样。但实际上，Limit 节点在拿到两行之后就停止请求更多行，因此实际行计数只有 2，运行时间也低于代价估计所暗示的水平。这并不是估计错误，只是估计值与真实值的显示方式不同而已。\n   \u003c/p\u003e\u003cp\u003e\u003ca href=\"/zh/docs/18/using-explain.html#USING-EXPLAIN-CAVEATS\"\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":["BitmapOr"],"explain_prefixes":["Parallel","Async"],"facts":[{"label":"Core node tag","value":"T_BitmapOr"},{"label":"Structured EXPLAIN Node Type","value":"BitmapOr"},{"label":"Inputs","value":"Bitmap-producing child plans"},{"label":"Output","value":"Tuple-location bitmap, not a tuple stream"},{"label":"Executor initializer","value":"ExecInitBitmapOr"},{"label":"Memory mechanism","value":"bitmap-lossification"}],"facts_zh":[{"label":"核心节点标签","value":"T_BitmapOr"},{"label":"结构化 EXPLAIN 节点类型","value":"BitmapOr"},{"label":"输入","value":"产生位图的子计划"},{"label":"输出","value":"元组位置位图，不是元组流"},{"label":"执行器初始化函数","value":"ExecInitBitmapOr"},{"label":"内存机制","value":"bitmap-lossification"}],"memory":{"description":"The node allocates a tuple-location bitmap using a work_mem-derived budget. 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Text-format spellings can also include operation, strategy, join type, scan direction or aggregation-stage attributes.","Text names recorded by this source: BitmapOr.","Parallel-aware and parallel-safe are different plan properties. A node running inside a parallel worker is not necessarily a parallel-aware node."],"title":"EXPLAIN names and attributes"},{"paragraphs":["The node allocates a tuple-location bitmap using a work_mem-derived budget. A bitmap can retain page-level lossy entries instead of every tuple location; heap rechecks then remain necessary."],"title":"Memory and temporary storage"},{"paragraphs":["The source callbacks below can coordinate execution or collect worker instrumentation. 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