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https://issues.apache.org/jira/browse/SPARK-10914?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
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Reynold Xin updated SPARK-10914:
--------------------------------
Description:
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}
was:
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}
> 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}
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