請問:hive中avg聚合函式會使用到combiner功能嗎?
例如下面這條SQL, 肯定是用上了combiner功能的
select deptno, sum(sal) as sum_sal from emp group by deptno
hive (test)> explain select deptno, sum(sal) as sum_sal from emp group by deptno;
OK
Explain
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: emp
Statistics: Num rows: 5 Data size: 603 Basic stats: COMPLETE Column stats: NONE
Select Operator
expressions: deptno (type: int), sal (type: decimal(22,2))
outputColumnNames: deptno, sal
Statistics: Num rows: 5 Data size: 603 Basic stats: COMPLETE Column stats: NONE
Group By Operator
aggregations: sum(sal)
keys: deptno (type: int)
mode: hash
outputColumnNames: _col0, _col1
Statistics: Num rows: 5 Data size: 603 Basic stats: COMPLETE Column stats: NONE
Reduce Output Operator
key expressions: _col0 (type: int)
sort order: +
Map-reduce partition columns: _col0 (type: int)
Statistics: Num rows: 5 Data size: 603 Basic stats: COMPLETE Column stats: NONE
value expressions: _col1 (type: decimal(32,2))
Reduce Operator Tree:
Group By Operator
aggregations: sum(VALUE._col0)
keys: KEY._col0 (type: int)
mode: mergepartial
outputColumnNames: _col0, _col1
Statistics: Num rows: 2 Data size: 241 Basic stats: COMPLETE Column stats: NONE
File Output Operator
compressed: false
Statistics: Num rows: 2 Data size: 241 Basic stats: COMPLETE 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
如果是這個SQL,是否能用上combiner功能?? 之前學習的時候說combiner不能處理avg這種函式的
select deptno, avg(sal) as avg_sal from emp group by deptno
我看執行計劃和使用sum聚合函式無差異
hive (test)> explain select deptno, avg(sal) as avg_sal from emp group by deptno;
OK
Explain
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: emp
Statistics: Num rows: 5 Data size: 603 Basic stats: COMPLETE Column stats: NONE
Select Operator
expressions: deptno (type: int), sal (type: decimal(22,2))
outputColumnNames: deptno, sal
Statistics: Num rows: 5 Data size: 603 Basic stats: COMPLETE Column stats: NONE
Group By Operator
aggregations: avg(sal)
keys: deptno (type: int)
mode: hash
outputColumnNames: _col0, _col1
Statistics: Num rows: 5 Data size: 603 Basic stats: COMPLETE Column stats: NONE
Reduce Output Operator
key expressions: _col0 (type: int)
sort order: +
Map-reduce partition columns: _col0 (type: int)
Statistics: Num rows: 5 Data size: 603 Basic stats: COMPLETE Column stats: NONE
value expressions: _col1 (type: struct<count:bigint,sum:decimal(32,2),input:decimal(22,2)>)
Reduce Operator Tree:
Group By Operator
aggregations: avg(VALUE._col0)
keys: KEY._col0 (type: int)
mode: mergepartial
outputColumnNames: _col0, _col1
Statistics: Num rows: 2 Data size: 241 Basic stats: COMPLETE Column stats: NONE
File Output Operator
compressed: false
Statistics: Num rows: 2 Data size: 241 Basic stats: COMPLETE 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
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