title | summary |
---|---|
用 EXPLAIN 查看子查询的执行计划 |
了解 TiDB 中 EXPLAIN 语句返回的执行计划信息。 |
TiDB 会执行多种子查询相关的优化,以提升子查询的执行性能。本文档介绍一些常见子查询的优化方式,以及如何解读 EXPLAIN
语句返回的执行计划信息。
本文档所使用的示例表数据如下:
CREATE TABLE t1 (id BIGINT NOT NULL PRIMARY KEY auto_increment, pad1 BLOB, pad2 BLOB, pad3 BLOB, int_col INT NOT NULL DEFAULT 0);
CREATE TABLE t2 (id BIGINT NOT NULL PRIMARY KEY auto_increment, t1_id BIGINT NOT NULL, pad1 BLOB, pad2 BLOB, pad3 BLOB, INDEX(t1_id));
CREATE TABLE t3 (
id INT NOT NULL PRIMARY KEY auto_increment,
t1_id INT NOT NULL,
UNIQUE (t1_id)
);
INSERT INTO t1 SELECT NULL, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024), 0 FROM dual;
INSERT INTO t1 SELECT NULL, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024), 0 FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024), 0 FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024), 0 FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024), 0 FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024), 0 FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024), 0 FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024), 0 FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024), 0 FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024), 0 FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024), 0 FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t2 SELECT NULL, a.id, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t2 SELECT NULL, a.id, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t2 SELECT NULL, a.id, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t2 SELECT NULL, a.id, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t2 SELECT NULL, a.id, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t2 SELECT NULL, a.id, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t2 SELECT NULL, a.id, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t2 SELECT NULL, a.id, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t2 SELECT NULL, a.id, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
UPDATE t1 SET int_col = 1 WHERE pad1 = (SELECT pad1 FROM t1 ORDER BY RAND() LIMIT 1);
INSERT INTO t3 SELECT NULL, id FROM t1 WHERE id < 1000;
SELECT SLEEP(1);
ANALYZE TABLE t1, t2, t3;
以下示例中,IN
子查询会从表 t2
中搜索一列 ID。为保证语义正确性,TiDB 需要保证 t1_id
列的值具有唯一性。使用 EXPLAIN
可查看到该查询的执行计划去掉重复项并执行 Inner Join
内连接操作:
EXPLAIN SELECT * FROM t1 WHERE id IN (SELECT t1_id FROM t2);
+--------------------------------+----------+-----------+------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| id | estRows | task | access object | operator info |
+--------------------------------+----------+-----------+------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| IndexJoin_15 | 21.11 | root | | inner join, inner:TableReader_12, outer key:test.t2.t1_id, inner key:test.t1.id, equal cond:eq(test.t2.t1_id, test.t1.id) |
| ├─StreamAgg_44(Build) | 21.11 | root | | group by:test.t2.t1_id, funcs:firstrow(test.t2.t1_id)->test.t2.t1_id |
| │ └─IndexReader_45 | 21.11 | root | | index:StreamAgg_34 |
| │ └─StreamAgg_34 | 21.11 | cop[tikv] | | group by:test.t2.t1_id, |
| │ └─IndexFullScan_26 | 90000.00 | cop[tikv] | table:t2, index:t1_id(t1_id) | keep order:true |
| └─TableReader_12(Probe) | 21.11 | root | | data:TableRangeScan_11 |
| └─TableRangeScan_11 | 21.11 | cop[tikv] | table:t1 | range: decided by [test.t2.t1_id], keep order:false |
+--------------------------------+----------+-----------+------------------------------+---------------------------------------------------------------------------------------------------------------------------+
由上述查询结果可知,TiDB 通过索引连接操作 | IndexJoin_14
将子查询做了连接转化。该执行计划首先在 TiKV 侧通过索引扫描算子 └─IndexFullScan_31
读取 t2.t1_id
列的值,然后由 └─StreamAgg_39
算子的部分任务在 TiKV 中对 t1_id
值进行去重,然后采用 ├─StreamAgg_49(Build)
算子的部分任务在 TiDB 中对 t1_id
值再次进行去重,去重操作由聚合函数 firstrow(test.t2.t1_id)
执行;之后将操作结果与 t1
表的主键相连接,连接条件是 eq(test.t1.id, test.t2.t1_id)
。
在上述示例中,为了确保 t1_id
值在与表 t1
连接前具有唯一性,需要执行聚合运算。在以下示例中,由于 UNIQUE
约束已能确保 t3.t1_id
列值的唯一:
EXPLAIN SELECT * FROM t1 WHERE id IN (SELECT t1_id FROM t3);
+-----------------------------+---------+-----------+------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| id | estRows | task | access object | operator info |
+-----------------------------+---------+-----------+------------------------------+---------------------------------------------------------------------------------------------------------------------------+
| IndexJoin_18 | 999.00 | root | | inner join, inner:TableReader_15, outer key:test.t3.t1_id, inner key:test.t1.id, equal cond:eq(test.t3.t1_id, test.t1.id) |
| ├─IndexReader_41(Build) | 999.00 | root | | index:IndexFullScan_40 |
| │ └─IndexFullScan_40 | 999.00 | cop[tikv] | table:t3, index:t1_id(t1_id) | keep order:false |
| └─TableReader_15(Probe) | 999.00 | root | | data:TableRangeScan_14 |
| └─TableRangeScan_14 | 999.00 | cop[tikv] | table:t1 | range: decided by [test.t3.t1_id], keep order:false |
+-----------------------------+---------+-----------+------------------------------+---------------------------------------------------------------------------------------------------------------------------+
从语义上看,因为约束保证了 t3.t1_id
列值的唯一性,TiDB 可以直接执行 INNER JOIN
查询。
在前两个示例中,通过 StreamAgg
聚合操作或通过 UNIQUE
约束保证子查询数据的唯一性之后,TiDB 才能够执行 Inner Join
操作。这两种连接均使用了 Index Join
。
下面的例子中,TiDB 优化器则选择了一种不同的执行计划:
EXPLAIN SELECT * FROM t1 WHERE id IN (SELECT t1_id FROM t2 WHERE t1_id != t1.int_col);
+-----------------------------+----------+-----------+------------------------------+--------------------------------------------------------------------------------------------------------+
| id | estRows | task | access object | operator info |
+-----------------------------+----------+-----------+------------------------------+--------------------------------------------------------------------------------------------------------+
| MergeJoin_9 | 45446.40 | root | | semi join, left key:test.t1.id, right key:test.t2.t1_id, other cond:ne(test.t2.t1_id, test.t1.int_col) |
| ├─IndexReader_24(Build) | 90000.00 | root | | index:IndexFullScan_23 |
| │ └─IndexFullScan_23 | 90000.00 | cop[tikv] | table:t2, index:t1_id(t1_id) | keep order:true |
| └─TableReader_22(Probe) | 56808.00 | root | | data:Selection_21 |
| └─Selection_21 | 56808.00 | cop[tikv] | | ne(test.t1.id, test.t1.int_col) |
| └─TableFullScan_20 | 71010.00 | cop[tikv] | table:t1 | keep order:true |
+-----------------------------+----------+-----------+------------------------------+--------------------------------------------------------------------------------------------------------+
由上述查询结果可知,TiDB 执行了 Semi Join
。不同于 Inner Join
,Semi Join
仅允许右键 (t2.t1_id
) 上的第一个值,也就是该操作将去除 Join
算子任务中的重复数据。Join
算法也包含 Merge Join
,会按照排序顺序同时从左侧和右侧读取数据,这是一种高效的 Zipper Merge
。
可以将原语句视为关联子查询,因为它引入了子查询外的 t1.int_col
列。然而,EXPLAIN
语句的返回结果显示的是关联子查询去关联后的执行计划。条件 t1_id != t1.int_col
会被重写为 t1.id != t1.int_col
。TiDB 可以从表 t1
中读取数据并且在 └─Selection_21
中执行此操作,因此这种去关联和重写操作会极大提高执行效率。
在以下示例中,除非子查询中存在 t3.t1_id
,否则该查询将(从语义上)返回表 t3
中的所有行:
EXPLAIN SELECT * FROM t3 WHERE t1_id NOT IN (SELECT id FROM t1 WHERE int_col < 100);
+-----------------------------+---------+-----------+---------------+-------------------------------------------------------------------------------------------------------------------------------+
| id | estRows | task | access object | operator info |
+-----------------------------+---------+-----------+---------------+-------------------------------------------------------------------------------------------------------------------------------+
| IndexJoin_16 | 799.20 | root | | anti semi join, inner:TableReader_12, outer key:test.t3.t1_id, inner key:test.t1.id, equal cond:eq(test.t3.t1_id, test.t1.id) |
| ├─TableReader_28(Build) | 999.00 | root | | data:TableFullScan_27 |
| │ └─TableFullScan_27 | 999.00 | cop[tikv] | table:t3 | keep order:false |
| └─TableReader_12(Probe) | 999.00 | root | | data:Selection_11 |
| └─Selection_11 | 999.00 | cop[tikv] | | lt(test.t1.int_col, 100) |
| └─TableRangeScan_10 | 999.00 | cop[tikv] | table:t1 | range: decided by [test.t3.t1_id], keep order:false |
+-----------------------------+---------+-----------+---------------+-------------------------------------------------------------------------------------------------------------------------------+
上述查询首先读取了表 t3
,然后根据主键开始探测 (probe) 表 t1
。连接类型是 anti semi join,即反半连接:之所以使用 anti,是因为上述示例有不存在匹配值(即 NOT IN
)的情况;使用 Semi Join
则是因为仅需要匹配第一行后就可以停止查询。
IN
和 = ANY
的集合运算符号具有特殊的三值属性(true
、false
和 NULL
)。这意味着在该运算符所转化得到的 Join 类型中需要对 Join key 两侧的 NULL
进行特殊的感知和处理。
IN
和 = ANY
算子引导的子查询会分别转为 Semi Join 和 Left Outer Semi Join。在上述 Semi Join 小节中,示例中 Join key 两侧的列 test.t1.id
和 test.t2.t1_id
都为 not NULL
属性,所以 Semi Join 本身不需要 Null-Aware 的性质来辅助运算,即不需要特殊处理 NULL
。当前 TiDB 对于 Null-Aware Semi Join 没有特定的优化,其实现本质都是基于笛卡尔积加过滤 (filter) 的模式。以下为 Null-Aware Semi Join 的例子:
CREATE TABLE t(a INT, b INT);
CREATE TABLE s(a INT, b INT);
EXPLAIN SELECT (a,b) IN (SELECT * FROM s) FROM t;
EXPLAIN SELECT * FROM t WHERE (a,b) IN (SELECT * FROM s);
tidb> EXPLAIN SELECT (a,b) IN (SELECT * FROM s) FROM t;
+-----------------------------+---------+-----------+---------------+-------------------------------------------------------------------------------------------+
| id | estRows | task | access object | operator info |
+-----------------------------+---------+-----------+---------------+-------------------------------------------------------------------------------------------+
| HashJoin_8 | 1.00 | root | | CARTESIAN left outer semi join, other cond:eq(test.t.a, test.s.a), eq(test.t.b, test.s.b) |
| ├─TableReader_12(Build) | 1.00 | root | | data:TableFullScan_11 |
| │ └─TableFullScan_11 | 1.00 | cop[tikv] | table:s | keep order:false, stats:pseudo |
| └─TableReader_10(Probe) | 1.00 | root | | data:TableFullScan_9 |
| └─TableFullScan_9 | 1.00 | cop[tikv] | table:t | keep order:false, stats:pseudo |
+-----------------------------+---------+-----------+---------------+-------------------------------------------------------------------------------------------+
5 rows in set (0.00 sec)
tidb> EXPLAIN SELECT * FROM t WHERE (a,b) IN (SELECT * FROM s);
+------------------------------+---------+-----------+---------------+-----------------------------------------------------------------------------------------------------+
| id | estRows | task | access object | operator info |
+------------------------------+---------+-----------+---------------+-----------------------------------------------------------------------------------------------------+
| HashJoin_11 | 1.00 | root | | inner join, equal:[eq(test.t.a, test.s.a) eq(test.t.b, test.s.b)] |
| ├─TableReader_14(Build) | 1.00 | root | | data:Selection_13 |
| │ └─Selection_13 | 1.00 | cop[tikv] | | not(isnull(test.t.a)), not(isnull(test.t.b)) |
| │ └─TableFullScan_12 | 1.00 | cop[tikv] | table:t | keep order:false, stats:pseudo |
| └─HashAgg_17(Probe) | 1.00 | root | | group by:test.s.a, test.s.b, funcs:firstrow(test.s.a)->test.s.a, funcs:firstrow(test.s.b)->test.s.b |
| └─TableReader_24 | 1.00 | root | | data:Selection_23 |
| └─Selection_23 | 1.00 | cop[tikv] | | not(isnull(test.s.a)), not(isnull(test.s.b)) |
| └─TableFullScan_22 | 1.00 | cop[tikv] | table:s | keep order:false, stats:pseudo |
+------------------------------+---------+-----------+---------------+-----------------------------------------------------------------------------------------------------+
8 rows in set (0.01 sec)
第一个查询 EXPLAIN SELECT (a,b) IN (SELECT * FROM s) FROM t;
中,由于 t
表和 s
表的 a
、b
列都是 NULLABLE 的,所以 IN
子查询所转化的 Left Outer Semi Join 是具有 Null-Aware 性质的。具体实现是先进行笛卡尔积,然后将 IN
或 = ANY
所连接的列作为普通等值条件放到 other condition 进行过滤(filter)。
第二个查询 EXPLAIN SELECT * FROM t WHERE (a,b) IN (SELECT * FROM s);
中,由于 t
表和 s
表的 a
、b
列都是 NULLABLE 的,IN
子查询本应该转为具有 Null-Aware 性质的 Semi Join,但当前 TiDB 进行了优化,直接将 Semi Join 转为了 Inner Join + Aggregate 的方式来实现。这是因为在非 scalar 输出的 IN
子查询中,NULL
和 false
是等效的。下推过滤的 NULL
行导致了 WHERE
子句的否定语义,因此可以事先忽略这些行。
注意:
Exists
操作符也会被转成 Semi Join,但是Exists
操作符号本身不具有集合运算 Null-Aware 的性质。
NOT IN
和 != ALL
的集合运算运算具有特殊的三值属性(true
、false
和 NULL
)。这意味着在其所转化得到的 Join 类型中需要对 Join key 两侧的 NULL
进行特殊的感知和处理。
NOT IN
和 != ALL
算子引导的子查询会对应地转为 Anti Semi Join 和 Anti Left Outer Semi Join。在上述的 Anti Semi Join 小节中,由于示例中 Join key 两侧的列 test.t3.t1_id
和 test.t1.id
都是 not NULL
属性的,所以 Anti Semi Join 本身不需要 Null-Aware 的性质来辅助计算,即不需要特殊处理 NULL
。
在 TiDB v6.3.0 版本,TiDB 引入了针对 Null-Aware Anti Join (NAAJ) 的如下特殊优化:
-
利用 Null-Aware 的等值条件 (NA-EQ) 构建哈希连接
由于集合操作符引入的等值需要对等值两侧操作符数的
NULL
值做特殊处理,这里称需要 Null-Aware 的等值条件为 NA-EQ 条件。与 v6.3.0 之前版本不同的是,TiDB 不会再将 NA-EQ 条件处理成普通 EQ 条件,而是专门放置于 Join 后置的 other condition 中,匹配笛卡尔积后再判断结果集的合法性。在 TiDB v6.3.0 版本中,NA-EQ 这种弱化的等值条件依然会被用来构建哈希值 (Hash Join),大大减少了匹配时所需遍历的数据量,加速匹配过程。在 build 表
DISTINCT
值比例趋近 1 的时候,加速效果更为显著。 -
利用两侧数据源
NULL
值的特殊性质加速匹配过程的返回由于 Anti Semi Join 自身具有 CNF (Conjunctive normal form) 表达式的属性,其任何一侧出现的
NULL
值都会导致确定的结果。利用这个性质可以来加速整个匹配过程。
以下为 Null-Aware Anti Semi Join 的例子:
CREATE TABLE t(a INT, b INT);
CREATE TABLE s(a INT, b INT);
EXPLAIN SELECT (a, b) NOT IN (SELECT * FROM s) FROM t;
EXPLAIN SELECT * FROM t WHERE (a, b) NOT IN (SELECT * FROM s);
tidb> EXPLAIN SELECT (a, b) NOT IN (SELECT * FROM s) FROM t;
+-----------------------------+----------+-----------+---------------+---------------------------------------------------------------------------------------------+
| id | estRows | task | access object | operator info |
+-----------------------------+----------+-----------+---------------+---------------------------------------------------------------------------------------------+
| HashJoin_8 | 10000.00 | root | | Null-aware anti left outer semi join, equal:[eq(test.t.b, test.s.b) eq(test.t.a, test.s.a)] |
| ├─TableReader_12(Build) | 10000.00 | root | | data:TableFullScan_11 |
| │ └─TableFullScan_11 | 10000.00 | cop[tikv] | table:s | keep order:false, stats:pseudo |
| └─TableReader_10(Probe) | 10000.00 | root | | data:TableFullScan_9 |
| └─TableFullScan_9 | 10000.00 | cop[tikv] | table:t | keep order:false, stats:pseudo |
+-----------------------------+----------+-----------+---------------+---------------------------------------------------------------------------------------------+
5 rows in set (0.00 sec)
tidb> EXPLAIN SELECT * FROM t WHERE (a, b) NOT IN (SELECT * FROM s);
+-----------------------------+----------+-----------+---------------+----------------------------------------------------------------------------------+
| id | estRows | task | access object | operator info |
+-----------------------------+----------+-----------+---------------+----------------------------------------------------------------------------------+
| HashJoin_8 | 8000.00 | root | | Null-aware anti semi join, equal:[eq(test.t.b, test.s.b) eq(test.t.a, test.s.a)] |
| ├─TableReader_12(Build) | 10000.00 | root | | data:TableFullScan_11 |
| │ └─TableFullScan_11 | 10000.00 | cop[tikv] | table:s | keep order:false, stats:pseudo |
| └─TableReader_10(Probe) | 10000.00 | root | | data:TableFullScan_9 |
| └─TableFullScan_9 | 10000.00 | cop[tikv] | table:t | keep order:false, stats:pseudo |
+-----------------------------+----------+-----------+---------------+----------------------------------------------------------------------------------+
5 rows in set (0.00 sec)
第一个查询 EXPLAIN SELECT (a, b) NOT IN (SELECT * FROM s) FROM t;
中,由于 t
表和 s
表的 a
、b
列都是 NULLABLE 的,所以 NOT IN
子查询所转化的 Left Outer Semi Join 是具有 Null-Aware 性质的。不同的是,NAAJ 优化将 NA-EQ 条件也作为了 Hash Join 的连接条件,大大加速了 Join 的计算。
第二个查询 EXPLAIN SELECT * FROM t WHERE (a, b) NOT IN (SELECT * FROM s);
中,由于 t
表和 s
表的 a
、b
列都是 NULLABLE 的,所以 NOT IN
子查询所转化的 Anti Semi Join 是具有 Null-Aware 性质的。不同的是,NAAJ 优化将 NA-EQ 条件也作为了 Hash Join 的连接条件,大大加速了 Join 的计算。
当前 TiDB 仅针对 Anti Semi Join 和 Anti Left Outer Semi Join 实现了 NULL
感知。目前仅支持 Hash Join 类型且其 build 表只能固定为右侧表。
注意:
Not Exists
操作符也会被转成 Anti Semi Join,但是Not Exists
符号本身不具有集合运算 Null-Aware 的性质。