文档

查询执行器介绍

更新时间:

本文介绍PolarDB-X的SQL执行器的概念、执行模型和执行模式。

基本概念

SQL执行器是PolarDB-X中执行计算层算子的组件。对于简单的点查SQL,往往可以整体下推存储层MySQL执行,因而感觉不到执行器的存在,MySQL的结果经过简单的解包封包又被回传给用户。但是对于较复杂的SQL,往往无法将SQL中的算子全部下推,这时候就需要PolarDB-X执行器执行无法下推的计算。

SELECT l_orderkey, sum(l_extendedprice *(1 - l_discount)) AS revenue
FROM CUSTOMER, ORDERS, LINEITEM
WHERE c_mktsegment = 'AUTOMOBILE'
  and c_custkey = o_custkey
  and l_orderkey = o_orderkey
  and o_orderdate < '1995-03-13'
  and l_shipdate > '1995-03-13'
GROUP BY l_orderkey;

通过EXPLAIN命令看到PolarDB-X的执行计划如下:

HashAgg(group="l_orderkey", revenue="SUM(*)")
  HashJoin(condition="o_custkey = c_custkey", type="inner")
    Gather(concurrent=true)
      LogicalView(tables="ORDERS_[0-7],LINEITEM_[0-7]", shardCount=8, sql="SELECT `ORDERS`.`o_custkey`, `LINEITEM`.`l_orderkey`, (`LINEITEM`.`l_extendedprice` * (? - `LINEITEM`.`l_discount`)) AS `x` FROM `ORDERS` AS `ORDERS` INNER JOIN `LINEITEM` AS `LINEITEM` ON (((`ORDERS`.`o_orderkey` = `LINEITEM`.`l_orderkey`) AND (`ORDERS`.`o_orderdate` < ?)) AND (`LINEITEM`.`l_shipdate` > ?))")
    Gather(concurrent=true)
      LogicalView(tables="CUSTOMER_[0-7]", shardCount=8, sql="SELECT `c_custkey` FROM `CUSTOMER` AS `CUSTOMER` WHERE (`c_mktsegment` = ?)")

如下图所示,LogicalView的SQL在执行时被下发给MySQL,而不能下推的部分(除LogicalView以外的算子)由PolarDB-X执行器进行计算,得到最终用户SQL需要的结果。执行器计算

执行模型

与传统数据库采用Volcano执行模型不同,PolarDB-X采用的是Pull~Push混合执行模型。所有算子按照计算过程中是否需要缓存临时表,将执行过程切分成多个pipeline,pipeline内部采用next()接口,按批获取数据完成在pipeline内部的计算。pipeline间采用push接口,上游pipeline在计算完成后,会将数据源源不断推送给下游pipeline做计算。

如下示例中,计算被切分成两个pipeline,在pipeline-A中扫描Table-A数据,完成构建哈希表。Pipeline-B扫描Table-B的数据,然后在HashJoin算子内部做关联得到JOIN结果,再返回客户端。执行模型

执行模式

目前PolarDB-X支持了三种执行模式:

  • 单机单线程(TP_LOCAL):查询过程是单线程计算,TP负载的查询涉及到的扫描行数比较少,往往会采用这种执行模式,比如基于主键的点查。

  • 单机并行(AP_LOCAL):查询过程中会利用节点的多核资源做并行计算,如果您没有配置只读实例,针对AP负载的查询,往往会采用这种执行模式,一般也称之为Parallel Query模式。

  • 多机并行(MPP):您如果配置了只读实例,针对AP负载的查询,可以协调只读实例上多个节点的多核做分布式多机并行加速。

为了准确查看执行模式,在原有EXPLAIN和执行计划的基础上,扩展了 EXPLAIN PHYSICAL,例如以下查询,在返回信息中可以查看当前查询采用的是MPP模式,此外还可以获取到每个执行片段的并发数。

explain physical select a.k, count(*) cnt from sbtest1 a, sbtest1 b where a.id = b.k and a.id > 1000 group by k having cnt > 1300 or
der by cnt limit 5, 10;

返回执行计划信息如下:

+-------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| PLAN                                                                                                                                                              |
+-------------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ExecutorType: MPP                                                                                                                                                 |
| The Query's MaxConcurrentParallelism: 2                                                                                                                           |
| Fragment 1                                                                                                                                                        |
|     Shuffle Output layout: [BIGINT, BIGINT] Output layout: [BIGINT, BIGINT]                                                                                       |
|     Output partitioning: SINGLE [] Parallelism: 1                                                                                                                 |
|     TopN(sort="cnt ASC", offset=?2, fetch=?3)                                                                                                                     |
|   Filter(condition="cnt > ?1")                                                                                                                                    |
|     HashAgg(group="k", cnt="COUNT()")                                                                                                                             |
|       BKAJoin(condition="k = id", type="inner")                                                                                                                   |
|         RemoteSource(sourceFragmentIds=[0], type=RecordType(INTEGER_UNSIGNED id, INTEGER_UNSIGNED k))                                                             |
|         Gather(concurrent=true)                                                                                                                                   |
|           LogicalView(tables="[000000-000003].sbtest1_[00-15]", shardCount=16, sql="SELECT `k` FROM `sbtest1` AS `sbtest1` WHERE ((`k` > ?) AND (`k` IN (...)))") |
| Fragment 0                                                                                                                                                        |
|     Shuffle Output layout: [BIGINT, BIGINT] Output layout: [BIGINT, BIGINT]                                                                                       |
|     Output partitioning: SINGLE [] Parallelism: 1 Splits: 16                                                                                                      |
|     LogicalView(tables="[000000-000003].sbtest1_[00-15]", shardCount=16, sql="SELECT `id`, `k` FROM `sbtest1` AS `sbtest1` WHERE (`id` > ?)")                     |
+-------------------------------------------------------------------------------------------------------------------------------------------------------------------+

同样的也允许您通过HINT EXECUTOR_MODE语句指定执行模式。例如主实例空闲资源很多,可以考虑强制设置为单机或者多机并行模式来加速。

explain physical /*+TDDL:EXECUTOR_MODE=AP_LOCAL*/select a.k, count(*) cnt from sbtest1 a, sbtest1 b where a.id = b.k and a.id > 1000 group by k having cnt > 1300 order by cnt limit 5, 10;     

返回执行计划信息如下:

+-------------------------------------------------------------------------------------------------------------------------------------------------------------+
| ExecutorMode: AP_LOCAL                                                                                                                                      |
| Fragment 0 dependency: [] parallelism: 4                                                                                                                    |
| BKAJoin(condition="k = id", type="inner")                                                                                                                   |
|   Gather(concurrent=true)                                                                                                                                   |
|     LogicalView(tables="[000000-000003].sbtest1_[00-15]", shardCount=16, sql="SELECT `id`, `k` FROM `sbtest1` AS `sbtest1` WHERE (`id` > ?)")               |
|   Gather(concurrent=true)                                                                                                                                   |
|     LogicalView(tables="[000000-000003].sbtest1_[00-15]", shardCount=16, sql="SELECT `k` FROM `sbtest1` AS `sbtest1` WHERE ((`k` > ?) AND (`k` IN (...)))") |
| Fragment 1 dependency: [] parallelism: 8                                                                                                                    |
| LocalBuffer                                                                                                                                                 |
|   RemoteSource(sourceFragmentIds=[0], type=RecordType(INTEGER_UNSIGNED id, INTEGER_UNSIGNED k, INTEGER_UNSIGNED k0))                                        |
| Fragment 2 dependency: [0, 1] parallelism: 8                                                                                                                |
| Filter(condition="cnt > ?1")                                                                                                                                |
|   HashAgg(group="k", cnt="COUNT()")                                                                                                                         |
|     RemoteSource(sourceFragmentIds=[1], type=RecordType(INTEGER_UNSIGNED id, INTEGER_UNSIGNED k, INTEGER_UNSIGNED k0))                                      |
| Fragment 3 dependency: [0, 1] parallelism: 1                                                                                                                |
| LocalBuffer                                                                                                                                                 |
|   RemoteSource(sourceFragmentIds=[2], type=RecordType(INTEGER_UNSIGNED k, BIGINT cnt))                                                                      |
| Fragment 4 dependency: [2, 3] parallelism: 1                                                                                                                |
| TopN(sort="cnt ASC", offset=?2, fetch=?3)                                                                                                                   |
|   RemoteSource(sourceFragmentIds=[3], type=RecordType(INTEGER_UNSIGNED k, BIGINT cnt))                                                                      |
+-------------------------------------------------------------------------------------------------------------------------------------------------------------+

多机并行执行模式的并发度是根据物理扫描行数、实例规格和计算所涉及到表的分表数计算得出的,整体的并行度要考虑高并发场景,所以并行度的计算会偏保守,您可以通过上述EXPLAIN PHYSICAL指令查看并行度。也同样支持HINT MPP_PARALLELISM强制指定并行度。

/*+TDDL:EXECUTOR_MODE=MPP MPP_PARALLELISM=8*/select a.k, count(*) cnt from sbtest1 a, sbtest1 b where a.id = b.k and a.id > 1000 group by k having cnt > 1300 order by cnt limit 5, 10;
  • 本页导读 (0)
文档反馈