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Dmitriy V. Ryaboy commented on PIG-1846: ---------------------------------------- The DISTINCT optimization is often not applicable; consider, for example, a script that takes all pages on a website and generates COUNT(impressions), COUNT(distinct users). Doing the distinct operation first means we can no longer do COUNT(impressions). An algebraic function applied to non-distinct bags can be decomposed in this case as follows: {code} gby = GROUP in BY (c1, c2) PARALLEL 100; res = FOREACH gby GENERATE FLATTEN(group) as (c1, c2), FUNC(distinct in.c3), ALGFUNC(in.c4); {code} becomes {code} in = FOREACH in GENERATE *, ALGFUNC$Initial(c4) as init; gby_dist = GROUP in BY (c1, c2, c3) PARALLEL 100; res_dist = FOREACH gby_dist GENERATE FLATTEN(group) as (c1, c2, c3), ALGFUNC$Intermed(in.init) as intermed; gby = GROUP res_dist BY (c1, c2) PARALLEL 100; res = FOREACH gby GENERATE FLATTEN(group) as (c1, c2), FUNC(res_dist.c3), ALGFUNC$Final(res_dist.intermed); {code} > optimize queries like - count distinct users for each gender > ------------------------------------------------------------ > > Key: PIG-1846 > URL: https://issues.apache.org/jira/browse/PIG-1846 > Project: Pig > Issue Type: Improvement > Affects Versions: 0.9.0 > Reporter: Thejas M Nair > Fix For: 0.10 > > > The pig group operation does not usually have to deal with skew on the > group-by keys if the foreach statement that works on the results of group has > only algebraic functions on the bags. But for some queries like the > following, skew can be a problem - > {code} > user_data = load 'file' as (user, gender, age); > user_group_gender = group user_data by gender parallel 100; > dist_users_per_gender = foreach user_group_gender > { > dist_user = distinct user_data.user; > generate group as gender, COUNT(dist_user) as > user_count; > } > {code} > Since there are only 2 distinct values of the group-by key, only 2 reducers > will actually get used in current implementation. ie, you can't get better > performance by adding more reducers. > Similar problem is there when the data is skewed on the group key. With > current implementation, another problem is that pig and MR has to deal with > records with extremely large bags that have the large number of distinct user > names, which results in high memory utilization and having to spill the bags > to disk. > The query plan should be modified to handle the skew in such cases and make > use of more reducers. -- This message is automatically generated by JIRA. For more information on JIRA, see: http://www.atlassian.com/software/jira