重庆分公司,新征程启航
为企业提供网站建设、域名注册、服务器等服务
https://issues.apache.org/jira/browse/HIVE-2340
网站建设哪家好,找成都创新互联!专注于网页设计、网站建设、微信开发、小程序开发、集团企业网站建设等服务项目。为回馈新老客户创新互联还提供了湘东免费建站欢迎大家使用!
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
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.