112 lines
3.8 KiB
Markdown
112 lines
3.8 KiB
Markdown
分布式聚合下压
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============================
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总的来看，聚合算子的下压可以分为 Partition-Wise Aggregation 计划和下压加两阶段聚合计划。
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Partition-Wise Aggregation
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-----------------------------------
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如果聚合查询的语意是按照分区键去做分组且在分组内做聚合，那么这样的聚合操作称为 Partition-Wise Aggregation。所有的操作都被下压到分区内并行的执行。需要注意的是，Partition-Wise Aggregation 不一定是最优的执行，因为并行度会受限于分区的数量。
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```javascript
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explain select sum(c2) from t2 group by c1\G;
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*************************** 1. row ***************************
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Query Plan:
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============================================
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|ID|OPERATOR |NAME|EST. ROWS|COST|
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--------------------------------------------
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|0 |EXCHANGE IN DISTR | |1000 |2834|
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|1 | EXCHANGE OUT DISTR| |1000 |2740|
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|2 | HASH GROUP BY | |1000 |2740|
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|3 | TABLE SCAN |t2 |4000 |499 |
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============================================
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Outputs & filters:
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-------------------------------------
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0 - output([T_FUN_SUM(t2.c2)]), filter(nil)
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1 - output([T_FUN_SUM(t2.c2)]), filter(nil)
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2 - output([T_FUN_SUM(t2.c2)]), filter(nil),
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group([t2.c1]), agg_func([T_FUN_SUM(t2.c2)])
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3 - output([t2.c1], [t2.c2]), filter(nil),
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access([t2.c1], [t2.c2]), partitions(p[0-3])
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```
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下压加两阶段聚合
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-----------------
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在更一般的情况下，aggregation 操作可能不是按照分区键作为分组来做的，在这样的情况下，OceanBase 数据库会采用两阶段聚合的方式，如下例所示。
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1. 将 aggregation 操作下压，获得部分的聚合结果。
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2. 进行汇总的方式获得最终结果。
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```javascript
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explain select sum(c1) from t2 group by c2\G;
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*************************** 1. row ***************************
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Query Plan:
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=============================================
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|ID|OPERATOR |NAME|EST. ROWS|COST|
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---------------------------------------------
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|0 |HASH GROUP BY | |1000 |3395|
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|1 | EXCHANGE IN DISTR | |1000 |2834|
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|2 | EXCHANGE OUT DISTR| |1000 |2740|
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|3 | HASH GROUP BY | |1000 |2740|
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|4 | TABLE SCAN |t2 |4000 |499 |
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=============================================
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Outputs & filters:
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-------------------------------------
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0 - output([T_FUN_SUM(T_FUN_SUM(t2.c1))]), filter(nil),
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group([t2.c2]), agg_func([T_FUN_SUM(T_FUN_SUM(t2.c1))])
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1 - output([T_FUN_SUM(t2.c1)], [t2.c2]), filter(nil)
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2 - output([T_FUN_SUM(t2.c1)], [t2.c2]), filter(nil)
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3 - output([T_FUN_SUM(t2.c1)], [t2.c2]), filter(nil),
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group([t2.c2]), agg_func([T_FUN_SUM(t2.c1)])
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4 - output([t2.c1], [t2.c2]), filter(nil),
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access([t2.c1], [t2.c2]), partitions(p[0-3])
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```
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```javascript
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explain select sum(c1) from t2 group by c2\G;
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*************************** 1. row ***************************
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Query Plan:
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=============================================
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|ID|OPERATOR |NAME|EST. ROWS|COST|
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---------------------------------------------
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|0 |HASH GROUP BY | |1000 |3395|
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|1 | EXCHANGE IN DISTR | |1000 |2834|
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|2 | EXCHANGE OUT DISTR| |1000 |2740|
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|3 | HASH GROUP BY | |1000 |2740|
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|4 | TABLE SCAN |t2 |4000 |499 |
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=============================================
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Outputs & filters:
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-------------------------------------
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0 - output([T_FUN_SUM(T_FUN_SUM(t2.c1))]), filter(nil),
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group([t2.c2]), agg_func([T_FUN_SUM(T_FUN_SUM(t2.c1))])
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1 - output([T_FUN_SUM(t2.c1)], [t2.c2]), filter(nil)
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2 - output([T_FUN_SUM(t2.c1)], [t2.c2]), filter(nil)
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3 - output([T_FUN_SUM(t2.c1)], [t2.c2]), filter(nil),
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group([t2.c2]), agg_func([T_FUN_SUM(t2.c1)])
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4 - output([t2.c1], [t2.c2]), filter(nil),
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access([t2.c1], [t2.c2]), partitions(p[0-3])
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```
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