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https://issues.apache.org/jira/browse/PIG-1846?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=13047476#comment-13047476
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Thejas M Nair commented on PIG-1846:
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bq. yeah I was just using short-hand with the distinct thing, and assumed you
would know what I meant
I didn't realize the mistake when I wrote the example. But short hand is more
readable, i have created a PIG-2117 to discuss supporting that syntax.
bq. Regarding two distincts – we can run the initial group-bys twice, and join?
Yes, that will work.
If the udf FUNC is algebraic and FUNC.Initial() returns something that is
smaller than its argument (eg, COUNT), a further optimization would be -
{code}
in = FOREACH in GENERATE *, ALGFUNC$Initial(c4) as init;
gby_dist = GROUP in BY (c1, c2, c3) PARALLEL 100;
res_dist = FOREACH gby_dist GENERATE
group.c1, group.c2, FUNC.Initial(c3),
ALGFUNC$Intermed(in.init) as intermed;
gby = GROUP res_dist BY (c1, c2) PARALLEL 100;
res = FOREACH gby GENERATE
FLATTEN(group) as (c1, c2),
FUNC2(res_dist.c3),
ALGFUNC2(res_dist.intermed);
{code}
Where FUNC2 is like ALGFUNC2 described earlier, having FUNC2.Initial same as
FUNC.Intermed .
> 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.
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