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TEZ MRR optimize to MR?

发表于:2024-11-25 作者:热门IT资讯网编辑
编辑最后更新 2024年11月25日,https://issues.apache.org/jira/browse/HIVE-2340select userid,count(*) from u_data group by userid or

https://issues.apache.org/jira/browse/HIVE-2340

select userid,count(*) from u_data group by userid order by userid will product MRR.

I think when the result of userid,count(*) is small(one reduce can process the result) . This query plan can optimize to MR ?


To prevent bad reducer merging, the reducer merging only kicks in when the

optimizer thinks it gets a perf boost.

MR -> MRR is not a big win when it comes Tez, due to container-reuse -

going wide on the large cardinality in case of missing map-side

aggregation will be safer.

If hive.map.aggr=true and the userid set fits within memory, then smushing

the reducers would be nicer.

To reset the wide-narrow checks, do

set hive.optimize.reducededuplication.min.reducer=1;

But be aware that it will fail (I1ve seen full disks) as you scale upwards

to the 10+ Tb cases.

Cheers,

Gopal

hive.optimize.reducededuplication.min.reducer
  • Default Value: 4

  • Added In: Hive 0.11.0 with HIVE-2340

Reduce deduplication merges two RSs (reduce sink operators) by moving key/parts/reducer-num of the child RS to parent RS. That means if reducer-num of the child RS is fixed (order by or forced bucketing) and small, it can make very slow, single MR. The optimization will be disabled if number of reducers is less than specified value.


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