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Sean Owen commented on SPARK-10914: ----------------------------------- Still kind of guessing here... but what if the problem is that the computation spans machines that have a different oops configuration (driver vs executor) and that breaks some assumption in the low-level byte munging? > Incorrect empty join sets when executor-memory >= 32g > ----------------------------------------------------- > > 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.) > {code} > /* 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 */ > {code} -- 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