Uploaded image for project: 'Pig'
  1. Pig
  2. PIG-1846

optimize queries like - count distinct users for each gender


    • Type: Improvement
    • Status: Open
    • Priority: Major
    • Resolution: Unresolved
    • Affects Version/s: 0.9.0
    • Fix Version/s: None
    • Component/s: None
    • Labels:


      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 -

      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;

      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.




            • Assignee:
              thejas Thejas M Nair
            • Votes:
              0 Vote for this issue
              7 Start watching this issue


              • Created: