| title | summary |
|---|---|
用 EXPLAIN 查看索引查询的执行计划 |
了解 TiDB 中 EXPLAIN 语句返回的执行计划信息。 |
SQL 查询可能会使用索引，可以通过 EXPLAIN 语句来查看索引查询的执行计划。本文提供多个示例，以帮助用户理解索引查询是如何执行的。
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 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 | 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 10 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)