解释在 MPP 模式下的 Statements
TiDB 支持使用 MPP mode 来执行查询。在 MPP 模式下，TiDB 优化器为 MPP 生成执行计划。注意，MPP 模式仅适用于在 TiFlash 上具有副本的表。
本文中的示例基于以下样例数据：
CREATE TABLE t1 (id int, value int);
INSERT INTO t1 values(1,2),(2,3),(1,3);
ALTER TABLE t1 set tiflash replica 1;
ANALYZE TABLE t1;
SET tidb_allow_mpp = 1;MPP 查询片段与 MPP 任务
在 MPP 模式下，一个查询在逻辑上被切分成多个查询片段。以以下语句为例：
EXPLAIN SELECT COUNT(*) FROM t1 GROUP BY id;该查询在 MPP 模式下被划分为两个片段：一个用于第一阶段的聚合，另一个用于第二阶段的聚合（也是最终的聚合）。当执行此查询时，每个查询片段会被实例化为一个或多个 MPP 任务。
Exchange 操作符
ExchangeReceiver 和 ExchangeSender 是专门用于 MPP 执行计划的两个交换操作符。ExchangeReceiver 从下游查询片段读取数据，ExchangeSender 将数据从下游查询片段发送到上游查询片段。在 MPP 模式下，每个 MPP 查询片段的根操作符是 ExchangeSender，意味着查询片段由 ExchangeSender 操作符界定。
以下是一个简单的 MPP 执行计划示例：
EXPLAIN SELECT COUNT(*) FROM t1 GROUP BY id;+------------------------------------+---------+-------------------+---------------+----------------------------------------------------+
| id | estRows | task | access object | operator info |
+------------------------------------+---------+-------------------+---------------+----------------------------------------------------+
| TableReader_31 | 2.00 | root | | data:ExchangeSender_30 |
| └─ExchangeSender_30 | 2.00 | batchCop[tiflash] | | ExchangeType: PassThrough |
| └─Projection_26 | 2.00 | batchCop[tiflash] | | Column#4 |
| └─HashAgg_27 | 2.00 | batchCop[tiflash] | | group by:test.t1.id, funcs:sum(Column#7)->Column#4 |
| └─ExchangeReceiver_29 | 2.00 | batchCop[tiflash] | | |
| └─ExchangeSender_28 | 2.00 | batchCop[tiflash] | | ExchangeType: HashPartition, Hash Cols: test.t1.id |
| └─HashAgg_9 | 2.00 | batchCop[tiflash] | | group by:test.t1.id, funcs:count(1)->Column#7 |
| └─TableFullScan_25 | 3.00 | batchCop[tiflash] | table:t1 | keep order:false |
+------------------------------------+---------+-------------------+---------------+----------------------------------------------------+上述执行计划包含两个查询片段：
- 第一个为
[TableFullScan_25, HashAgg_9, ExchangeSender_28]，主要负责第一阶段的聚合。 - 第二个为
[ExchangeReceiver_29, HashAgg_27, Projection_26, ExchangeSender_30]，主要负责第二阶段的聚合。
ExchangeSender 操作符的 operator info 列显示了交换类型信息。目前有三种交换类型，见下：
- HashPartition：
ExchangeSender操作符首先根据 Hash 值对数据进行分区，然后将数据分发到上游 MPP 任务的ExchangeReceiver。此交换类型常用于 Hash 聚合和 Shuffle Hash Join 算法。 - Broadcast：
ExchangeSender操作符通过广播将数据分发到上游 MPP 任务。此交换类型常用于 Broadcast Join。 - PassThrough：
ExchangeSender操作符将数据发送到唯一的上游 MPP 任务，与 Broadcast 类型不同。此交换类型常用于返回数据给 TiDB。
在示例执行计划中，ExchangeSender_28 的交换类型为 HashPartition，意味着它执行 Hash 聚合算法；ExchangeSender_30 的交换类型为 PassThrough，意味着它用于将数据返回给 TiDB。
MPP 也常用于连接操作。TiDB 中的 MPP 模式支持以下两种连接算法：
- Shuffle Hash Join：使用 HashPartition 交换类型对连接操作的输入数据进行洗牌，然后上游 MPP 任务在相同分区内进行连接。
- Broadcast Join：将连接操作中的小表数据广播到每个节点，然后每个节点分别进行连接。
以下是 Shuffle Hash Join 的典型执行计划示例：
SET tidb_broadcast_join_threshold_count=0;
SET tidb_broadcast_join_threshold_size=0;
EXPLAIN SELECT COUNT(*) FROM t1 a JOIN t1 b ON a.id = b.id;+----------------------------------------+---------+--------------+---------------+----------------------------------------------------+
| id | estRows | task | access object | operator info |
+----------------------------------------+---------+--------------+---------------+----------------------------------------------------+
| StreamAgg_14 | 1.00 | root | | funcs:count(1)->Column#7 |
| └─TableReader_48 | 9.00 | root | | data:ExchangeSender_47 |
| └─ExchangeSender_47 | 9.00 | cop[tiflash] | | ExchangeType: PassThrough |
| └─HashJoin_44 | 9.00 | cop[tiflash] | | inner join, equal:[eq(test.t1.id, test.t1.id)] |
| ├─ExchangeReceiver_19(Build) | 6.00 | cop[tiflash] | | |
| │ └─ExchangeSender_18 | 6.00 | cop[tiflash] | | ExchangeType: HashPartition, Hash Cols: test.t1.id |
| │ └─Selection_17 | 6.00 | cop[tiflash] | | not(isnull(test.t1.id)) |
| │ └─TableFullScan_16 | 6.00 | cop[tiflash] | table:a | keep order:false |
| └─ExchangeReceiver_23(Probe) | 6.00 | cop[tiflash] | | |
| └─ExchangeSender_22 | 6.00 | cop[tiflash] | | ExchangeType: HashPartition, Hash Cols: test.t1.id |
| └─Selection_21 | 6.00 | cop[tiflash] | | not(isnull(test.t1.id)) |
| └─TableFullScan_20 | 6.00 | cop[tiflash] | table:b | keep order:false |
+----------------------------------------+---------+--------------+---------------+----------------------------------------------------+
12 rows in set (0.00 sec)在上述执行计划中：
- 查询片段
[TableFullScan_20, Selection_21, ExchangeSender_22]从表 b 读取数据并将数据洗牌到上游 MPP 任务。 - 查询片段
[TableFullScan_16, Selection_17, ExchangeSender_18]从表 a 读取数据并将数据洗牌到上游 MPP 任务。 - 查询片段
[ExchangeReceiver_19, ExchangeReceiver_23, HashJoin_44, ExchangeSender_47]将所有数据连接后返回给 TiDB。
一个典型的 Broadcast Join 执行计划如下：
EXPLAIN SELECT COUNT(*) FROM t1 a JOIN t1 b ON a.id = b.id;+----------------------------------------+---------+--------------+---------------+------------------------------------------------+
| id | estRows | task | access object | operator info |
+----------------------------------------+---------+--------------+---------------+------------------------------------------------+
| StreamAgg_15 | 1.00 | root | | funcs:count(1)->Column#7 |
| └─TableReader_47 | 9.00 | root | | data:ExchangeSender_46 |
| └─ExchangeSender_46 | 9.00 | cop[tiflash] | | ExchangeType: PassThrough |
| └─HashJoin_43 | 9.00 | cop[tiflash] | | inner join, equal:[eq(test.t1.id, test.t1.id)] |
| ├─ExchangeReceiver_20(Build) | 6.00 | cop[tiflash] | | |
| │ └─ExchangeSender_19 | 6.00 | cop[tiflash] | | ExchangeType: Broadcast |
| │ └─Selection_18 | 6.00 | cop[tiflash] | | not(isnull(test.t1.id)) |
| │ └─TableFullScan_17 | 6.00 | cop[tiflash] | table:a | keep order:false |
| └─Selection_22(Probe) | 6.00 | cop[tiflash] | | not(isnull(test.t1.id)) |
| └─TableFullScan_21 | 6.00 | cop[tiflash] | table:b | keep order:false |
+----------------------------------------+---------+--------------+---------------+------------------------------------------------+在上述执行计划中：
- 查询片段
[TableFullScan_17, Selection_18, ExchangeSender_19]从小表（表 a）读取数据，并将数据广播到每个包含大表（表 b）数据的节点。 - 查询片段
[TableFullScan_21, Selection_22, ExchangeReceiver_20, HashJoin_43, ExchangeSender_46]将所有数据连接后返回给 TiDB。
EXPLAIN ANALYZE 在 MPP 模式下的 Statements
EXPLAIN ANALYZE 语句类似于 EXPLAIN，但会输出一些运行时信息。
以下是一个简单的 EXPLAIN ANALYZE 示例的输出：
EXPLAIN ANALYZE SELECT COUNT(*) FROM t1 GROUP BY id;+------------------------------------+---------+---------+-------------------+---------------+---------------------------------------------------------------------------------------------------+----------------------------------------------------------------+--------+------+
| id | estRows | actRows | task | access object | execution info | operator info | memory | disk |
+------------------------------------+---------+---------+-------------------+---------------+---------------------------------------------------------------------------------------------------+----------------------------------------------------------------+--------+------+
| TableReader_31 | 4.00 | 2 | root | | time:44.5ms, loops:2, cop_task: {num: 1, max: 0s, proc_keys: 0, copr_cache_hit_ratio: 0.00} | data:ExchangeSender_30 | N/A | N/A |
| └─ExchangeSender_30 | 4.00 | 2 | batchCop[tiflash] | | tiflash_task:{time:16.5ms, loops:1, threads:1} | ExchangeType: PassThrough, tasks: [2, 3, 4] | N/A | N/A |
| └─Projection_26 | 4.00 | 2 | batchCop[tiflash] | | tiflash_task:{time:16.5ms, loops:1, threads:1} | Column#4 | N/A | N/A |
| └─HashAgg_27 | 4.00 | 2 | batchCop[tiflash] | | tiflash_task:{time:16.5ms, loops:1, threads:1} | group by:test.t1.id, funcs:sum(Column#7)->Column#4 | N/A | N/A |
| └─ExchangeReceiver_29 | 4.00 | 2 | batchCop[tiflash] | | tiflash_task:{time:14.5ms, loops:1, threads:20} | | N/A | N/A |
| └─ExchangeSender_28 | 4.00 | 0 | batchCop[tiflash] | | tiflash_task:{time:9.49ms, loops:0, threads:0} | ExchangeType: HashPartition, Hash Cols: test.t1.id, tasks: [1] | N/A | N/A |
| └─HashAgg_9 | 4.00 | 0 | batchCop[tiflash] | | tiflash_task:{time:9.49ms, loops:0, threads:0} | group by:test.t1.id, funcs:count(1)->Column#7 | N/A | N/A |
| └─TableFullScan_25 | 6.00 | 0 | batchCop[tiflash] | table:t1 | tiflash_task:{time:9.49ms, loops:0, threads:0}, tiflash_scan:{dtfile:{total_scanned_packs:1,...}} | keep order:false | N/A | N/A |
+------------------------------------+---------+---------+-------------------+---------------+---------------------------------------------------------------------------------------------------+----------------------------------------------------------------+--------+------+与 EXPLAIN 的输出相比，operator info 列中的 ExchangeSender 还显示了 tasks，记录了查询片段实例化的 MPP 任务的编号。此外，每个 MPP 操作符在 execution info 列中还包含 threads 字段，记录了 TiDB 执行此操作符时的并发数。如果集群由多个节点组成，此并发数为所有节点并发数的总和。
MPP 版本与交换数据压缩
从 v6.6.0 版本开始，MPP 执行计划中新增字段 MPPVersion 和 Compression。
MppVersion：MPP 执行计划的版本号，可通过系统变量mpp_version设置。Compression：Exchange操作符的数据压缩模式，可通过系统变量mpp_exchange_compression_mode设置。如果未启用数据压缩，则在执行计划中不显示此字段。
示例如下：
mysql > EXPLAIN SELECT COUNT(*) AS count_order FROM lineitem GROUP BY l_returnflag, l_linestatus ORDER BY l_returnflag, l_linestatus;
+----------------------------------------+--------------+--------------+----------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| id | estRows | task | access object | operator info |
+----------------------------------------+--------------+--------------+----------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| Projection_6 | 3.00 | root | | Column#18 |
| └─Sort_8 | 3.00 | root | | tpch100.lineitem.l_returnflag, tpch100.lineitem.l_linestatus |
| └─TableReader_36 | 3.00 | root | | MppVersion: 1, data:ExchangeSender_35 |
| └─ExchangeSender_35 | 3.00 | mpp[tiflash] | | ExchangeType: PassThrough |
| └─Projection_31 | 3.00 | mpp[tiflash] | | Column#18, tpch100.lineitem.l_returnflag, tpch100.lineitem.l_linestatus |
| └─HashAgg_32 | 3.00 | mpp[tiflash] | | group by:tpch100.lineitem.l_linestatus, tpch100.lineitem.l_returnflag, funcs:sum(Column#23)->Column#18, funcs:firstrow(tpch100.lineitem.l_returnflag)->tpch100.lineitem.l_returnflag, funcs:firstrow(tpch100.lineitem.l_linestatus)->tpch100.lineitem.l_linestatus, stream_count: 20 |
| └─ExchangeReceiver_34 | 3.00 | mpp[tiflash] | | stream_count: 20 |
| └─ExchangeSender_33 | 3.00 | mpp[tiflash] | | ExchangeType: HashPartition, Compression: FAST, Hash Cols: [name: tpch100.lineitem.l_returnflag, collate: utf8mb4_bin], [name: tpch100.lineitem.l_linestatus, collate: utf8mb4_bin], stream_count: 20 |
| └─HashAgg_14 | 3.00 | mpp[tiflash] | | group by:tpch100.lineitem.l_linestatus, tpch100.lineitem.l_returnflag, funcs:count(1)->Column#23 |
| └─TableFullScan_30 | 600037902.00 | mpp[tiflash] | table:lineitem | keep order:false |
+----------------------------------------+--------------+--------------+----------------+--------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------+在上述执行计划结果中，TiDB 使用版本 1 的 MPP 执行计划构建 TableReader。HashPartition 类型的 ExchangeSender 操作符使用了 FAST 数据压缩模式，而 PassThrough 类型的 ExchangeSender 则未启用数据压缩。