使用分区解释语句
EXPLAIN 语句显示 TiDB 在执行查询时需要访问的分区。由于 partition pruning，显示的分区通常只是全部分区的一个子集。本文档描述了一些针对常见分区表的优化方法，以及如何解读 EXPLAIN 的输出。
本文档中使用的示例数据：
CREATE TABLE t1 (
id BIGINT NOT NULL auto_increment,
d date NOT NULL,
pad1 BLOB,
pad2 BLOB,
pad3 BLOB,
PRIMARY KEY (id,d)
) PARTITION BY RANGE (YEAR(d)) (
PARTITION p2016 VALUES LESS THAN (2017),
PARTITION p2017 VALUES LESS THAN (2018),
PARTITION p2018 VALUES LESS THAN (2019),
PARTITION p2019 VALUES LESS THAN (2020),
PARTITION pmax VALUES LESS THAN MAXVALUE
);
INSERT INTO t1 (d, pad1, pad2, pad3) VALUES
('2016-01-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2016-06-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2016-09-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2017-01-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2017-06-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2017-09-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2018-01-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2018-06-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2018-09-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2019-01-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2019-06-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2019-09-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2020-01-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2020-06-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024)),
('2020-09-01', RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024));
INSERT INTO t1 SELECT NULL, a.d, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, a.d, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, a.d, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
INSERT INTO t1 SELECT NULL, a.d, RANDOM_BYTES(1024), RANDOM_BYTES(1024), RANDOM_BYTES(1024) FROM t1 a JOIN t1 b JOIN t1 c LIMIT 10000;
SELECT SLEEP(1);
ANALYZE TABLE t1;
以下示例展示了对新建分区表的查询语句：
EXPLAIN SELECT COUNT(*) FROM t1 WHERE d = '2017-06-01';
+------------------------------+---------+-----------+---------------------------+-------------------------------------------+
| id | estRows | task | access object | operator info |
+------------------------------+---------+-----------+---------------------------+-------------------------------------------+
| StreamAgg_21 | 1.00 | root | | funcs:count(Column#8)->Column#6 |
| └─TableReader_22 | 1.00 | root | | data:StreamAgg_10 |
| └─StreamAgg_10 | 1.00 | cop[tikv] | | funcs:count(1)->Column#8 |
| └─Selection_20 | 8.87 | cop[tikv] | | eq(test.t1.d, 2017-06-01 00:00:00.000000) |
| └─TableFullScan_19 | 8870.00 | cop[tikv] | table:t1, partition:p2017 | keep order:false |
+------------------------------+---------+-----------+---------------------------+-------------------------------------------+
5 rows in set (0.01 sec)
从最内层（└─TableFullScan_19）操作符开始，逐步向根操作符（StreamAgg_21）回溯：
- TiDB 成功识别出只需要访问一个分区（
p2017）。这在access object中有所体现。 - 该分区在操作符
└─TableFullScan_19中被扫描，然后└─Selection_20被应用，用于筛选出开始日期为2017-06-01 00:00:00.000000的行。 - 匹配
└─Selection_20的行随后在协处理器中进行流式聚合，协处理器原生支持count函数。 - 每个协处理请求返回一行数据到 TiDB 内部的
└─TableReader_22，然后在StreamAgg_21中进行流式聚合，最后将一行结果返回给客户端。
在以下示例中，分区修剪未能排除任何分区：
EXPLAIN SELECT COUNT(*) FROM t1 WHERE YEAR(d) = 2017;
+------------------------------------+----------+-----------+---------------------------+----------------------------------+
| id | estRows | task | access object | operator info |
+------------------------------------+----------+-----------+---------------------------+----------------------------------+
| HashAgg_20 | 1.00 | root | | funcs:count(Column#7)->Column#6 |
| └─PartitionUnion_21 | 5.00 | root | | |
| ├─StreamAgg_36 | 1.00 | root | | funcs:count(Column#9)->Column#7 |
| │ └─TableReader_37 | 1.00 | root | | data:StreamAgg_25 |
| │ └─StreamAgg_25 | 1.00 | cop[tikv] | | funcs:count(1)->Column#9 |
| │ └─Selection_35 | 6000.00 | cop[tikv] | | eq(year(test.t1.d), 2017) |
| │ └─TableFullScan_34 | 7500.00 | cop[tikv] | table:t1, partition:p2016 | keep order:false |
| ├─StreamAgg_55 | 1.00 | root | | funcs:count(Column#11)->Column#7 |
| │ └─TableReader_56 | 1.00 | root | | data:StreamAgg_44 |
| │ └─StreamAgg_44 | 1.00 | cop[tikv] | | funcs:count(1)->Column#11 |
| │ └─Selection_54 | 14192.00 | cop[tikv] | | eq(year(test.t1.d), 2017) |
| │ └─TableFullScan_53 | 17740.00 | cop[tikv] | table:t1, partition:p2017 | keep order:false |
| ├─StreamAgg_74 | 1.00 | root | | funcs:count(Column#13)->Column#7 |
| │ └─TableReader_75 | 1.00 | root | | data:StreamAgg_63 |
| │ └─StreamAgg_63 | 1.00 | cop[tikv] | | funcs:count(1)->Column#13 |
| │ └─Selection_73 | 3977.60 | cop[tikv] | | eq(year(test.t1.d), 2017) |
| │ └─TableFullScan_72 | 4972.00 | cop[tikv] | table:t1, partition:p2018 | keep order:false |
| ├─StreamAgg_93 | 1.00 | root | | funcs:count(Column#15)->Column#7 |
| │ └─TableReader_94 | 1.00 | root | | data:StreamAgg_82 |
| │ └─StreamAgg_82 | 1.00 | cop[tikv] | | funcs:count(1)->Column#15 |
| │ └─Selection_92 | 20361.60 | cop[tikv] | | eq(year(test.t1.d), 2017) |
| │ └─TableFullScan_91 | 25452.00 | cop[tikv] | table:t1, partition:p2019 | keep order:false |
| └─StreamAgg_112 | 1.00 | root | | funcs:count(Column#17)->Column#7 |
| └─TableReader_113 | 1.00 | root | | data:StreamAgg_101 |
| └─StreamAgg_101 | 1.00 | cop[tikv] | | funcs:count(1)->Column#17 |
| └─Selection_111 | 8892.80 | cop[tikv] | | eq(year(test.t1.d), 2017) |
| └─TableFullScan_110 | 11116.00 | cop[tikv] | table:t1, partition:pmax | keep order:false |
+------------------------------------+----------+-----------+---------------------------+----------------------------------+
27 rows in set (0.00 sec)
从上述输出可以看出：
- TiDB 认为需要访问所有分区（
p2016..pMax）。这是因为谓词YEAR(d) = 2017被认为是 non-sargable。这个问题并非 TiDB 独有。 - 每个分区在扫描时，
Selection操作符会筛选出年份不为 2017 的行。 - 对每个分区进行流式聚合，统计匹配的行数。
- 操作符
└─PartitionUnion_21将访问每个分区的结果合并。