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Xiao Li commented on SPARK-12030: --------------------------------- What is the data type of id1? > Incorrect results when aggregate joined data > -------------------------------------------- > > Key: SPARK-12030 > URL: https://issues.apache.org/jira/browse/SPARK-12030 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 1.6.0 > Reporter: Maciej BryĆski > Priority: Critical > > I have following issue. > I created 2 dataframes from JDBC (MySQL) and joined them (t1 has fk1 to t2) > {code} > t1 = sqlCtx.read.jdbc("jdbc:mysql://XXX", t1, id1, 0, size1, 200).cache() > t2 = sqlCtx.read.jdbc("jdbc:mysql://XXX", t2, id2, 0, size1, 200).cache() > joined = t1.join(t2, t1.fk1 == t2.id2, "left_outer") > {code} > Important: both table are cached, so results should be the same on every > query. > Then I did come counts: > {code} > t1.count() -> 5900729 > t1.registerTempTable("t1") > sqlCtx.sql("select distinct(id1) from t1").count() -> 5900729 > t2.count() -> 54298 > joined.count() -> 5900729 > {code} > And here magic begins - I counted distinct id1 from joined table > {code} > joined.registerTempTable("joined") > sqlCtx.sql("select distinct(id1) from joined").count() > {code} > Results varies *(are different on every run)* between 5899000 and > 5900000 but never are equal to 5900729. > In addition. I did more queries: > {code} > sqlCtx.sql("select id1, count(*) from joined group by id1 having count(*) > > 1").collect() > {code} > This gives some results but this query return *1* > {code} > len(sqlCtx.sql("select * from joined where id1 = result").collect()) > {code} > What's wrong ? -- This message was sent by Atlassian JIRA (v6.3.4#6332) --------------------------------------------------------------------- To unsubscribe, e-mail: issues-unsubscr...@spark.apache.org For additional commands, e-mail: issues-h...@spark.apache.org