Uploaded image for project: 'Spark'
  1. Spark
  2. SPARK-12030

Incorrect results when aggregate joined data

    XMLWordPrintableJSON

    Details

    • Type: Bug
    • Status: Resolved
    • Priority: Blocker
    • Resolution: Fixed
    • Affects Version/s: 1.6.0
    • Fix Version/s: 1.5.3, 1.6.0
    • Component/s: SQL
    • Labels:
    • Target Version/s:

      Description

      I have following issue.
      I created 2 dataframes from JDBC (MySQL) and joined them (t1 has fk1 to t2)

      t1 = sqlCtx.read.jdbc("jdbc:mysql://XXX", t1, id1, 0, size1, 200).cache()
      t2 = sqlCtx.read.jdbc("jdbc:mysql://XXX", t2).cache()
      joined = t1.join(t2, t1.fk1 == t2.id2, "left_outer")
      

      Important: both table are cached, so results should be the same on every query.
      Then I did come counts:

      t1.count() -> 5900729
      t1.registerTempTable("t1")
      sqlCtx.sql("select distinct(id1) from t1").count() -> 5900729
      t2.count() -> 54298
      joined.count() -> 5900729
      

      And here magic begins - I counted distinct id1 from joined table

      joined.registerTempTable("joined")
      sqlCtx.sql("select distinct(id1) from joined").count()
      

      Results varies (are different on every run) between 5899000 and
      5900000 but never are equal to 5900729.

      In addition. I did more queries:

      sqlCtx.sql("select id1, count(*) from joined group by id1 having count(*) > 1").collect() 
      

      This gives some results but this query return 1

      len(sqlCtx.sql("select * from joined where id1 = result").collect())
      

      What's wrong ?

        Attachments

          Issue Links

            Activity

              People

              • Assignee:
                nongli Nong Li
                Reporter:
                maver1ck Maciej BryƄski
              • Votes:
                0 Vote for this issue
                Watchers:
                10 Start watching this issue

                Dates

                • Created:
                  Updated:
                  Resolved: