title | summary |
---|---|
用 EXPLAIN 查看使用索引的 SQL 执行计划 |
了解 TiDB 中 EXPLAIN 语句返回的执行计划信息。 |
TiDB 支持以下使用索引的算子来提升查询速度:
本文档中的示例都基于以下数据:
{{< copyable "sql" >}}
CREATE TABLE t1 (
id INT NOT NULL PRIMARY KEY auto_increment,
intkey INT NOT NULL,
pad1 VARBINARY(1024),
INDEX (intkey)
);
INSERT INTO t1 SELECT NULL, FLOOR(RAND()*1024), RANDOM_BYTES(1024) FROM dual;
INSERT INTO t1 SELECT NULL, FLOOR(RAND()*1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, FLOOR(RAND()*1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, FLOOR(RAND()*1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
TiDB 从二级索引检索数据时会使用 IndexLookup
算子。例如,以下所有查询均会在 intkey
列的索引上使用 IndexLookup
算子:
{{< copyable "sql" >}}
EXPLAIN SELECT * FROM t1 WHERE intkey = 123;
EXPLAIN SELECT * FROM t1 WHERE intkey < 10;
EXPLAIN SELECT * FROM t1 WHERE intkey BETWEEN 300 AND 310;
EXPLAIN SELECT * FROM t1 WHERE intkey BETWEEN 300 AND 310;
EXPLAIN SELECT * FROM t1 WHERE intkey IN (123,29,98);
EXPLAIN SELECT * FROM t1 WHERE intkey >= 99 AND intkey <= 103;
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
| id | estRows | task | access object | operator info |
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
| IndexLookUp_10 | 1.00 | root | | |
| ├─IndexRangeScan_8(Build) | 1.00 | cop[tikv] | table:t1, index:intkey(intkey) | range:[123,123], keep order:false |
| └─TableRowIDScan_9(Probe) | 1.00 | cop[tikv] | table:t1 | keep order:false |
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
3 rows in set (0.00 sec)
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
| id | estRows | task | access object | operator info |
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
| IndexLookUp_10 | 3.60 | root | | |
| ├─IndexRangeScan_8(Build) | 3.60 | cop[tikv] | table:t1, index:intkey(intkey) | range:[-inf,10), keep order:false |
| └─TableRowIDScan_9(Probe) | 3.60 | cop[tikv] | table:t1 | keep order:false |
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
3 rows in set (0.00 sec)
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
| id | estRows | task | access object | operator info |
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
| IndexLookUp_10 | 5.67 | root | | |
| ├─IndexRangeScan_8(Build) | 5.67 | cop[tikv] | table:t1, index:intkey(intkey) | range:[300,310], keep order:false |
| └─TableRowIDScan_9(Probe) | 5.67 | cop[tikv] | table:t1 | keep order:false |
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
3 rows in set (0.00 sec)
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
| id | estRows | task | access object | operator info |
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
| IndexLookUp_10 | 5.67 | root | | |
| ├─IndexRangeScan_8(Build) | 5.67 | cop[tikv] | table:t1, index:intkey(intkey) | range:[300,310], keep order:false |
| └─TableRowIDScan_9(Probe) | 5.67 | cop[tikv] | table:t1 | keep order:false |
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
3 rows in set (0.00 sec)
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------------------------+
| id | estRows | task | access object | operator info |
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------------------------+
| IndexLookUp_10 | 4.00 | root | | |
| ├─IndexRangeScan_8(Build) | 4.00 | cop[tikv] | table:t1, index:intkey(intkey) | range:[29,29], [98,98], [123,123], keep order:false |
| └─TableRowIDScan_9(Probe) | 4.00 | cop[tikv] | table:t1 | keep order:false |
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------------------------+
3 rows in set (0.00 sec)
+-------------------------------+---------+-----------+--------------------------------+----------------------------------+
| id | estRows | task | access object | operator info |
+-------------------------------+---------+-----------+--------------------------------+----------------------------------+
| IndexLookUp_10 | 6.00 | root | | |
| ├─IndexRangeScan_8(Build) | 6.00 | cop[tikv] | table:t1, index:intkey(intkey) | range:[99,103], keep order:false |
| └─TableRowIDScan_9(Probe) | 6.00 | cop[tikv] | table:t1 | keep order:false |
+-------------------------------+---------+-----------+--------------------------------+----------------------------------+
3 rows in set (0.00 sec)
IndexLookup
算子有以下两个子节点:
├─IndexRangeScan_8(Build)
算子节点对intkey
列的索引执行范围扫描,并检索内部的RowID
值(对此表而言,即为主键)。└─TableRowIDScan_9(Probe)
算子节点随后从表数据中检索整行。
IndexLookup
任务分以上两步执行。如果满足条件的行较多,SQL 优化器可能会根据统计信息选择使用 TableFullScan
算子。在以下示例中,很多行都满足 intkey > 100
这一条件,因此优化器选择了 TableFullScan
:
{{< copyable "sql" >}}
EXPLAIN SELECT * FROM t1 WHERE intkey > 100;
+-------------------------+---------+-----------+---------------+-------------------------+
| id | estRows | task | access object | operator info |
+-------------------------+---------+-----------+---------------+-------------------------+
| TableReader_7 | 898.50 | root | | data:Selection_6 |
| └─Selection_6 | 898.50 | cop[tikv] | | gt(test.t1.intkey, 100) |
| └─TableFullScan_5 | 1010.00 | cop[tikv] | table:t1 | keep order:false |
+-------------------------+---------+-----------+---------------+-------------------------+
3 rows in set (0.00 sec)
IndexLookup
算子能在带索引的列上有效优化 LIMIT
:
{{< copyable "sql" >}}
EXPLAIN SELECT * FROM t1 ORDER BY intkey DESC LIMIT 10;
+--------------------------------+---------+-----------+--------------------------------+------------------------------------+
| id | estRows | task | access object | operator info |
+--------------------------------+---------+-----------+--------------------------------+------------------------------------+
| IndexLookUp_21 | 10.00 | root | | limit embedded(offset:0, count:10) |
| ├─Limit_20(Build) | 10.00 | cop[tikv] | | offset:0, count:10 |
| │ └─IndexFullScan_18 | 10.00 | cop[tikv] | table:t1, index:intkey(intkey) | keep order:true, desc |
| └─TableRowIDScan_19(Probe) | 10.00 | cop[tikv] | table:t1 | keep order:false, stats:pseudo |
+--------------------------------+---------+-----------+--------------------------------+------------------------------------+
4 rows in set (0.00 sec)
以上示例中,TiDB 从 intkey
索引读取最后 20 行,然后从表数据中检索这些行的 RowID
值。
TiDB 支持覆盖索引优化 (covering index optimization)。如果 TiDB 能从索引中检索出所有行,就会跳过 IndexLookup
任务中通常所需的第二步(即从表数据中检索整行)。示例如下:
{{< copyable "sql" >}}
EXPLAIN SELECT * FROM t1 WHERE intkey = 123;
EXPLAIN SELECT id FROM t1 WHERE intkey = 123;
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
| id | estRows | task | access object | operator info |
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
| IndexLookUp_10 | 1.00 | root | | |
| ├─IndexRangeScan_8(Build) | 1.00 | cop[tikv] | table:t1, index:intkey(intkey) | range:[123,123], keep order:false |
| └─TableRowIDScan_9(Probe) | 1.00 | cop[tikv] | table:t1 | keep order:false |
+-------------------------------+---------+-----------+--------------------------------+-----------------------------------+
3 rows in set (0.00 sec)
+--------------------------+---------+-----------+--------------------------------+-----------------------------------+
| id | estRows | task | access object | operator info |
+--------------------------+---------+-----------+--------------------------------+-----------------------------------+
| Projection_4 | 1.00 | root | | test.t1.id |
| └─IndexReader_6 | 1.00 | root | | index:IndexRangeScan_5 |
| └─IndexRangeScan_5 | 1.00 | cop[tikv] | table:t1, index:intkey(intkey) | range:[123,123], keep order:false |
+--------------------------+---------+-----------+--------------------------------+-----------------------------------+
3 rows in set (0.00 sec)
以上结果中,id
也是内部的 RowID
值,因此 id
也存储在 intkey
索引中。部分 └─IndexRangeScan_5
任务使用 intkey
索引后,可直接返回 RowID
值。
TiDB 直接从主键或唯一键检索数据时会使用 Point_Get
或 Batch_Point_Get
算子。这两个算子比 IndexLookup
更有效率。示例如下:
{{< copyable "sql" >}}
EXPLAIN SELECT * FROM t1 WHERE id = 1234;
EXPLAIN SELECT * FROM t1 WHERE id IN (1234,123);
ALTER TABLE t1 ADD unique_key INT;
UPDATE t1 SET unique_key = id;
ALTER TABLE t1 ADD UNIQUE KEY (unique_key);
EXPLAIN SELECT * FROM t1 WHERE unique_key = 1234;
EXPLAIN SELECT * FROM t1 WHERE unique_key IN (1234, 123);
+-------------+---------+------+---------------+---------------+
| id | estRows | task | access object | operator info |
+-------------+---------+------+---------------+---------------+
| Point_Get_1 | 1.00 | root | table:t1 | handle:1234 |
+-------------+---------+------+---------------+---------------+
1 row in set (0.00 sec)
+-------------------+---------+------+---------------+-------------------------------------------------+
| id | estRows | task | access object | operator info |
+-------------------+---------+------+---------------+-------------------------------------------------+
| Batch_Point_Get_1 | 2.00 | root | table:t1 | handle:[1234 123], keep order:false, desc:false |
+-------------------+---------+------+---------------+-------------------------------------------------+
1 row in set (0.00 sec)
Query OK, 0 rows affected (0.27 sec)
Query OK, 1010 rows affected (0.06 sec)
Rows matched: 1010 Changed: 1010 Warnings: 0
Query OK, 0 rows affected (0.37 sec)
+-------------+---------+------+----------------------------------------+---------------+
| id | estRows | task | access object | operator info |
+-------------+---------+------+----------------------------------------+---------------+
| Point_Get_1 | 1.00 | root | table:t1, index:unique_key(unique_key) | |
+-------------+---------+------+----------------------------------------+---------------+
1 row in set (0.00 sec)
+-------------------+---------+------+----------------------------------------+------------------------------+
| id | estRows | task | access object | operator info |
+-------------------+---------+------+----------------------------------------+------------------------------+
| Batch_Point_Get_1 | 2.00 | root | table:t1, index:unique_key(unique_key) | keep order:false, desc:false |
+-------------------+---------+------+----------------------------------------+------------------------------+
1 row in set (0.00 sec)
索引是有序的,所以优化器可以使用 IndexFullScan
算子来优化常见的查询,例如在索引值上使用 MIN
或 Max
函数:
{{< copyable "sql" >}}
EXPLAIN SELECT MIN(intkey) FROM t1;
EXPLAIN SELECT MAX(intkey) FROM t1;
+------------------------------+---------+-----------+--------------------------------+-------------------------------------+
| id | estRows | task | access object | operator info |
+------------------------------+---------+-----------+--------------------------------+-------------------------------------+
| StreamAgg_12 | 1.00 | root | | funcs:min(test.t1.intkey)->Column#4 |
| └─Limit_16 | 1.00 | root | | offset:0, count:1 |
| └─IndexReader_29 | 1.00 | root | | index:Limit_28 |
| └─Limit_28 | 1.00 | cop[tikv] | | offset:0, count:1 |
| └─IndexFullScan_27 | 1.00 | cop[tikv] | table:t1, index:intkey(intkey) | keep order:true |
+------------------------------+---------+-----------+--------------------------------+-------------------------------------+
5 rows in set (0.00 sec)
+------------------------------+---------+-----------+--------------------------------+-------------------------------------+
| id | estRows | task | access object | operator info |
+------------------------------+---------+-----------+--------------------------------+-------------------------------------+
| StreamAgg_12 | 1.00 | root | | funcs:max(test.t1.intkey)->Column#4 |
| └─Limit_16 | 1.00 | root | | offset:0, count:1 |
| └─IndexReader_29 | 1.00 | root | | index:Limit_28 |
| └─Limit_28 | 1.00 | cop[tikv] | | offset:0, count:1 |
| └─IndexFullScan_27 | 1.00 | cop[tikv] | table:t1, index:intkey(intkey) | keep order:true, desc |
+------------------------------+---------+-----------+--------------------------------+-------------------------------------+
5 rows in set (0.00 sec)
以上语句的执行过程中,TiDB 在每一个 TiKV Region 上执行 IndexFullScan
操作。虽然算子名为 FullScan
即全扫描,TiDB 只读取第一行 (└─Limit_28
)。每个 TiKV Region 返回各自的 MIN
或 MAX
值给 TiDB,TiDB 再执行流聚合运算来过滤出一行数据。即使表为空,带 MAX
或 MIN
函数的流聚合运算也能保证返回 NULL
值。
相反,在没有索引的值上执行 MIN
函数会在每一个 TiKV Region 上执行 TableFullScan
操作。该查询会要求在 TiKV 中扫描所有行,但 TopN
计算可保证每个 TiKV Region 只返回一行数据给 TiDB。尽管 TopN
能减少 TiDB 和 TiKV 之间的多余数据传输,但该查询的效率仍远不及以上示例(MIN
能够使用索引)。
{{< copyable "sql" >}}
EXPLAIN SELECT MIN(pad1) FROM t1;
+--------------------------------+---------+-----------+---------------+-----------------------------------+
| id | estRows | task | access object | operator info |
+--------------------------------+---------+-----------+---------------+-----------------------------------+
| StreamAgg_13 | 1.00 | root | | funcs:min(test.t1.pad1)->Column#4 |
| └─TopN_14 | 1.00 | root | | test.t1.pad1, offset:0, count:1 |
| └─TableReader_23 | 1.00 | root | | data:TopN_22 |
| └─TopN_22 | 1.00 | cop[tikv] | | test.t1.pad1, offset:0, count:1 |
| └─Selection_21 | 1008.99 | cop[tikv] | | not(isnull(test.t1.pad1)) |
| └─TableFullScan_20 | 1010.00 | cop[tikv] | table:t1 | keep order:false |
+--------------------------------+---------+-----------+---------------+-----------------------------------+
6 rows in set (0.00 sec)
执行以下语句时,TiDB 将使用 IndexFullScan
算子扫描索引中的每一行:
{{< copyable "sql" >}}
EXPLAIN SELECT SUM(intkey) FROM t1;
EXPLAIN SELECT AVG(intkey) FROM t1;
+----------------------------+---------+-----------+--------------------------------+-------------------------------------+
| id | estRows | task | access object | operator info |
+----------------------------+---------+-----------+--------------------------------+-------------------------------------+
| StreamAgg_20 | 1.00 | root | | funcs:sum(Column#6)->Column#4 |
| └─IndexReader_21 | 1.00 | root | | index:StreamAgg_8 |
| └─StreamAgg_8 | 1.00 | cop[tikv] | | funcs:sum(test.t1.intkey)->Column#6 |
| └─IndexFullScan_19 | 1010.00 | cop[tikv] | table:t1, index:intkey(intkey) | keep order:false |
+----------------------------+---------+-----------+--------------------------------+-------------------------------------+
4 rows in set (0.00 sec)
+----------------------------+---------+-----------+--------------------------------+----------------------------------------------------------------------------+
| id | estRows | task | access object | operator info |
+----------------------------+---------+-----------+--------------------------------+----------------------------------------------------------------------------+
| StreamAgg_20 | 1.00 | root | | funcs:avg(Column#7, Column#8)->Column#4 |
| └─IndexReader_21 | 1.00 | root | | index:StreamAgg_8 |
| └─StreamAgg_8 | 1.00 | cop[tikv] | | funcs:count(test.t1.intkey)->Column#7, funcs:sum(test.t1.intkey)->Column#8 |
| └─IndexFullScan_19 | 1010.00 | cop[tikv] | table:t1, index:intkey(intkey) | keep order:false |
+----------------------------+---------+-----------+--------------------------------+----------------------------------------------------------------------------+
4 rows in set (0.00 sec)
以上示例中,IndexFullScan
比 TableFullScan
更有效率,因为 (intkey + RowID)
索引中值的长度小于整行的长度。
以下语句不支持使用 IndexFullScan
算子,因为涉及该表中的其他列:
{{< copyable "sql" >}}
EXPLAIN SELECT AVG(intkey), ANY_VALUE(pad1) FROM t1;
+------------------------------+---------+-----------+---------------+-----------------------------------------------------------------------------------------------------------------------+
| id | estRows | task | access object | operator info |
+------------------------------+---------+-----------+---------------+-----------------------------------------------------------------------------------------------------------------------+
| Projection_4 | 1.00 | root | | Column#4, any_value(test.t1.pad1)->Column#5 |
| └─StreamAgg_16 | 1.00 | root | | funcs:avg(Column#10, Column#11)->Column#4, funcs:firstrow(Column#12)->test.t1.pad1 |
| └─TableReader_17 | 1.00 | root | | data:StreamAgg_8 |
| └─StreamAgg_8 | 1.00 | cop[tikv] | | funcs:count(test.t1.intkey)->Column#10, funcs:sum(test.t1.intkey)->Column#11, funcs:firstrow(test.t1.pad1)->Column#12 |
| └─TableFullScan_15 | 1010.00 | cop[tikv] | table:t1 | keep order:false |
+------------------------------+---------+-----------+---------------+-----------------------------------------------------------------------------------------------------------------------+
5 rows in set (0.00 sec)