with as 语句真的会把查询的数据存内存嘛？

数据仓库践行者

发布于 2021-04-09 10:24:04

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发布于 2021-04-09 10:24:04

文章被收录于专栏：数据仓库践行者数据仓库践行者

面对网上的一些结论，我们要有自己的判断。从源码中找真相~~

最近有好几个朋友都有咨询这个问题，大概有两类：

1、为啥我用了with..as效率没有提高？

2、sql跑不动，改成with..as的写法，会不会更好些？

网上博客几乎都有结论with ... as语句会把数据放在内存：

hive-sql

在hive中有一个参数

hive.optimize.cte.materialize.threshold

这个参数在默认情况下是-1（关闭的）；当开启（大于0），比如设置为2，则如果with..as语句被引用2次及以上时，会把with..as语句生成的table物化，从而做到with..as语句只执行一次，来提高效率。

测试

explain
with atable as (
     SELECT  id,source,channel
            FROM  test

)
select source from atable WHERE   channel = '直播'
union ALL
select source from atable WHERE   channel = '视频'

不设置该参数时，执行计划：

STAGE DEPENDENCIES:
 Stage-1 is a root stage
 Stage-0 depends on stages: Stage-1

STAGE PLANS:
 Stage: Stage-1
  Map Reduce
   Map Operator Tree:
     TableScan
      alias: test
      Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
      Filter Operator
       predicate: (channel = '直播') (type: boolean)
       Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
       Select Operator
        expressions: source (type: string)
        outputColumnNames: _col0
        Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
        Union
         Statistics: Num rows: 2 Data size: 0 Basic stats: PARTIAL Column stats: NONE
         File Output Operator
          compressed: false
          Statistics: Num rows: 2 Data size: 0 Basic stats: PARTIAL Column stats: NONE
          table:
            input format: org.apache.hadoop.mapred.SequenceFileInputFormat
            output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
            serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
     TableScan
      alias: test
      Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
      Filter Operator
       predicate: (channel = '视频') (type: boolean)
       Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
       Select Operator
        expressions: source (type: string)
        outputColumnNames: _col0
        Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
        Union
         Statistics: Num rows: 2 Data size: 0 Basic stats: PARTIAL Column stats: NONE
         File Output Operator
          compressed: false
          Statistics: Num rows: 2 Data size: 0 Basic stats: PARTIAL Column stats: NONE
          table:
            input format: org.apache.hadoop.mapred.SequenceFileInputFormat
            output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
            serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe

 Stage: Stage-0
  Fetch Operator
   limit: -1
   Processor Tree:
    ListSink

从执行计划上看，test表被读两次。

设置set hive.optimize.cte.materialize.threshold=1

，执行计划：

STAGE DEPENDENCIES:
 Stage-1 is a root stage
 Stage-6 depends on stages: Stage-1 , consists of Stage-3, Stage-2, Stage-4
 Stage-3
 Stage-0 depends on stages: Stage-3, Stage-2, Stage-5
 Stage-8 depends on stages: Stage-0
 Stage-2
 Stage-4
 Stage-5 depends on stages: Stage-4
 Stage-7 depends on stages: Stage-8

STAGE PLANS:
 Stage: Stage-1
  Map Reduce
   Map Operator Tree:
     TableScan
      alias: test
      Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
      Select Operator
       expressions: id (type: int), source (type: string), channel (type: string)
       outputColumnNames: _col0, _col1, _col2
       Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
       File Output Operator
        compressed: false
        Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
        table:
          input format: org.apache.hadoop.mapred.TextInputFormat
          output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
          serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
          name: default.atable

 Stage: Stage-6
  Conditional Operator

 Stage: Stage-3
  Move Operator
   files:
     hdfs directory: true
     destination: hdfs://localhost:9000/tmp/hive/bytedance/bae441cb-0ef6-4e9c-9f7a-8a5f97d0e560/_tmp_space.db/ce44793b-6eed-4299-b737-f05c66b2281b/.hive-staging_hive_2021-03-24_20-17-38_169_5695913330535939856-1/-ext-10002

 Stage: Stage-0
  Move Operator
   files:
     hdfs directory: true
     destination: hdfs://localhost:9000/tmp/hive/bytedance/bae441cb-0ef6-4e9c-9f7a-8a5f97d0e560/_tmp_space.db/ce44793b-6eed-4299-b737-f05c66b2281b

 Stage: Stage-8
  Map Reduce
   Map Operator Tree:
     TableScan
      alias: atable
      Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
      Filter Operator
       predicate: (channel = '直播') (type: boolean)
       Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
       Select Operator
        expressions: source (type: string)
        outputColumnNames: _col0
        Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
        Union
         Statistics: Num rows: 2 Data size: 0 Basic stats: PARTIAL Column stats: NONE
         File Output Operator
          compressed: false
          Statistics: Num rows: 2 Data size: 0 Basic stats: PARTIAL Column stats: NONE
          table:
            input format: org.apache.hadoop.mapred.SequenceFileInputFormat
            output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
            serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
     TableScan
      alias: atable
      Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
      Filter Operator
       predicate: (channel = '视频') (type: boolean)
       Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
       Select Operator
        expressions: source (type: string)
        outputColumnNames: _col0
        Statistics: Num rows: 1 Data size: 0 Basic stats: PARTIAL Column stats: NONE
        Union
         Statistics: Num rows: 2 Data size: 0 Basic stats: PARTIAL Column stats: NONE
         File Output Operator
          compressed: false
          Statistics: Num rows: 2 Data size: 0 Basic stats: PARTIAL Column stats: NONE
          table:
            input format: org.apache.hadoop.mapred.SequenceFileInputFormat
            output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
            serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe

 Stage: Stage-2
  Map Reduce
   Map Operator Tree:
     TableScan
      File Output Operator
       compressed: false
       table:
         input format: org.apache.hadoop.mapred.TextInputFormat
         output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
         serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
         name: default.atable

 Stage: Stage-4
  Map Reduce
   Map Operator Tree:
     TableScan
      File Output Operator
       compressed: false
       table:
         input format: org.apache.hadoop.mapred.TextInputFormat
         output format: org.apache.hadoop.hive.ql.io.HiveIgnoreKeyTextOutputFormat
         serde: org.apache.hadoop.hive.serde2.lazy.LazySimpleSerDe
         name: default.atable

 Stage: Stage-5
  Move Operator
   files:
     hdfs directory: true
     destination: hdfs://localhost:9000/tmp/hive/bytedance/bae441cb-0ef6-4e9c-9f7a-8a5f97d0e560/_tmp_space.db/ce44793b-6eed-4299-b737-f05c66b2281b/.hive-staging_hive_2021-03-24_20-17-38_169_5695913330535939856-1/-ext-10002

 Stage: Stage-7
  Fetch Operator
   limit: -1
   Processor Tree:
    ListSink

可以看到test表被物化了。

源码：

从源码看，在获取元数据时，会做参数判断，判断参数阈值及cte的引用次数

spark-sql

spark对cte的操作比较少，在spark侧，现在还没发现有相关的优化参数

with atable as (
     SELECT  content_type,
                    channel,
                    channel_note,
                    enter_method,
                    enter_method_note
            FROM    search_dw.dim_ecom_enter_channel_df
            
)
select channel from atable WHERE   content_type = '直播'
union ALL
select channel from atable WHERE   content_type = '视频'