explain 实战-----查看hive sql执行计划

目录

[1.join/left join/full join 语句会过滤关联字段 null 的值吗？](#1.join/left join/full join 语句会过滤关联字段 null 的值吗？)

（1）join

[（2） left join /full join](#（2） left join /full join)

[2.group by 分组语句会进行排序吗？](#2.group by 分组语句会进行排序吗？)

---

1.join/left join/full join 语句会过滤关联字段 null 的值吗？

（1）join

sql：

explain 
select
	a.into_id,
	a.into_bus_id,
	b.customer_type  as customer_type
from
--进件表
(select * from dp_ods.o_fk_eagle_jsd_intopieces_s
where etl_date = '2023-09-06' and substr(into_time ,1,4) >= '2019' ) a
join 
(select * from dp_ods.o_hyd_jsd_loan_order_s  where etl_date = '2023-09-06') b
on a.into_id=b.loan_id 

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: o_fk_eagle_jsd_intopieces_s
            Statistics: Num rows: 36940508 Data size: 360575316992 Basic stats: COMPLETE Column stats: NONE
            Filter Operator
              predicate: ((substr(into_time, 1, 4) >= '2019') and into_id is not null) (type: boolean)
              Statistics: Num rows: 12313502 Data size: 120191765823 Basic stats: COMPLETE Column stats: NONE
              Select Operator
                expressions: into_id (type: string), into_bus_id (type: string)
                outputColumnNames: _col0, _col1
                Statistics: Num rows: 12313502 Data size: 120191765823 Basic stats: COMPLETE Column stats: NONE
                Reduce Output Operator
                  key expressions: _col0 (type: string)
                  sort order: +
                  Map-reduce partition columns: _col0 (type: string)
                  Statistics: Num rows: 12313502 Data size: 120191765823 Basic stats: COMPLETE Column stats: NONE
                  value expressions: _col1 (type: string)
          TableScan
            alias: o_hyd_jsd_loan_order_s
            Statistics: Num rows: 44174590 Data size: 84039429353 Basic stats: COMPLETE Column stats: NONE
            Filter Operator
              predicate: loan_id is not null (type: boolean)
              Statistics: Num rows: 44174590 Data size: 84039429353 Basic stats: COMPLETE Column stats: NONE
              Select Operator
                expressions: loan_id (type: string), customer_type (type: int)
                outputColumnNames: _col0, _col1
                Statistics: Num rows: 44174590 Data size: 84039429353 Basic stats: COMPLETE Column stats: NONE
                Reduce Output Operator
                  key expressions: _col0 (type: string)
                  sort order: +
                  Map-reduce partition columns: _col0 (type: string)
                  Statistics: Num rows: 44174590 Data size: 84039429353 Basic stats: COMPLETE Column stats: NONE
                  value expressions: _col1 (type: int)
      Reduce Operator Tree:
        Join Operator
          condition map:
               Inner Join 0 to 1
          keys:
            0 _col0 (type: string)
            1 _col0 (type: string)
          outputColumnNames: _col0, _col1, _col3
          Statistics: Num rows: 48592050 Data size: 92443374291 Basic stats: COMPLETE Column stats: NONE
          Select Operator
            expressions: _col0 (type: string), _col1 (type: string), _col3 (type: int)
            outputColumnNames: _col0, _col1, _col2
            Statistics: Num rows: 48592050 Data size: 92443374291 Basic stats: COMPLETE Column stats: NONE
            File Output Operator
              compressed: false
              Statistics: Num rows: 48592050 Data size: 92443374291 Basic stats: COMPLETE 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

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

可以看到filter 顾虑部分有比原sql多了关联字段不为空的判断

（2） left join /full join

没有相关的过滤空值操作

2.group by 分组语句会进行排序吗？

explain
select date(create_time),max(actual_amount) max_actual_amount 
from dp_ods.o_hyd_jsd_loan_order_s  
where etl_date = '2023-09-06'
group by date(create_time)

STAGE DEPENDENCIES:
  Stage-1 is a root stage
  Stage-2 depends on stages: Stage-1
  Stage-0 depends on stages: Stage-2

STAGE PLANS:
  Stage: Stage-1
    Map Reduce
      Map Operator Tree:
          TableScan
            alias: o_hyd_jsd_loan_order_s
            Statistics: Num rows: 44174590 Data size: 84039429353 Basic stats: COMPLETE Column stats: NONE
            Select Operator
              expressions: CAST( create_time AS DATE) (type: date), actual_amount (type: double)
              outputColumnNames: _col0, _col1
              Statistics: Num rows: 44174590 Data size: 84039429353 Basic stats: COMPLETE Column stats: NONE
              Group By Operator
                aggregations: max(_col1)
                keys: _col0 (type: date)
                mode: hash
                outputColumnNames: _col0, _col1
                Statistics: Num rows: 44174590 Data size: 84039429353 Basic stats: COMPLETE Column stats: NONE
                Reduce Output Operator
                  key expressions: _col0 (type: date)
                  sort order: +
                  Map-reduce partition columns: rand() (type: double)
                  Statistics: Num rows: 44174590 Data size: 84039429353 Basic stats: COMPLETE Column stats: NONE
                  value expressions: _col1 (type: double)
      Reduce Operator Tree:
        Group By Operator
          aggregations: max(VALUE._col0)
          keys: KEY._col0 (type: date)
          mode: partials
          outputColumnNames: _col0, _col1
          Statistics: Num rows: 44174590 Data size: 84039429353 Basic stats: COMPLETE Column stats: NONE
          File Output Operator
            compressed: false
            table:
                input format: org.apache.hadoop.mapred.SequenceFileInputFormat
                output format: org.apache.hadoop.hive.ql.io.HiveSequenceFileOutputFormat
                serde: org.apache.hadoop.hive.serde2.lazybinary.LazyBinarySerDe

  Stage: Stage-2
    Map Reduce
      Map Operator Tree:
          TableScan
            Reduce Output Operator
              key expressions: _col0 (type: date)
              sort order: +
              Map-reduce partition columns: _col0 (type: date)
              Statistics: Num rows: 44174590 Data size: 84039429353 Basic stats: COMPLETE Column stats: NONE
              value expressions: _col1 (type: double)
      Reduce Operator Tree:
        Group By Operator
          aggregations: max(VALUE._col0)
          keys: KEY._col0 (type: date)
          mode: final
          outputColumnNames: _col0, _col1
          Statistics: Num rows: 22087295 Data size: 42019714676 Basic stats: COMPLETE Column stats: NONE
          File Output Operator
            compressed: false
            Statistics: Num rows: 22087295 Data size: 42019714676 Basic stats: COMPLETE 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

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

可以看到group by 字段是进行了正序排序的，查看sql执行结果也能看到。