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Wenchen Fan commented on SPARK-10914: ------------------------------------- hi [~benm], I can't reproduce this bug on spark 1.5.1(downloaded binary version) on my mac locally, can you provide more details(local or cluster? jvm options?)? you can use `df.explain(true)` to print the plan tree so that we can see what's going on there. > Incorrect empty join sets > ------------------------- > > Key: SPARK-10914 > URL: https://issues.apache.org/jira/browse/SPARK-10914 > Project: Spark > Issue Type: Bug > Components: SQL > Affects Versions: 1.5.0, 1.5.1 > Environment: Ubuntu 14.04 (spark-slave), 12.04 (master) > Reporter: Ben Moran > > Using an inner join, to match together two integer columns, I generally get > no results when there should be matches. But the results vary and depend on > whether the dataframes are coming from SQL, JSON, or cached, as well as the > order in which I cache things and query them. > This minimal example reproduces it consistently for me in the spark-shell, on > new installs of both 1.5.0 and 1.5.1 (pre-built against Hadoop 2.6 from > http://spark.apache.org/downloads.html.) > /* x is {"xx":1}{"xx":2} and y is just {"yy":1}{"yy:2} */ > val x = sql("select 1 xx union all select 2") > val y = sql("select 1 yy union all select 2") > x.join(y, $"xx" === $"yy").count() /* expect 2, get 0 */ > /* If I cache both tables it works: */ > x.cache() > y.cache() > x.join(y, $"xx" === $"yy").count() /* expect 2, get 2 */ > /* but this still doesn't work: */ > x.join(y, $"xx" === $"yy").filter("yy=1").count() /* expect 1, get 0 */ -- 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