[jira] [Assigned] (SPARK-17957) Calling outer join and na.fill(0) and then inner join will miss rows

2016-10-17 Thread Apache Spark (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-17957?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-17957:


Assignee: Apache Spark  (was: Xiao Li)

> Calling outer join and na.fill(0) and then inner join will miss rows
> 
>
> Key: SPARK-17957
> URL: https://issues.apache.org/jira/browse/SPARK-17957
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 2.0.1
> Environment: Spark 2.0.1, Mac, Local
>Reporter: Linbo
>Assignee: Apache Spark
>Priority: Critical
>  Labels: correctness
>
> I reported a similar bug two months ago and it's fixed in Spark 2.0.1: 
> https://issues.apache.org/jira/browse/SPARK-17060 But I find a new bug: when 
> I insert a na.fill(0) call between outer join and inner join in the same 
> workflow in SPARK-17060 I get wrong result.
> {code:title=spark-shell|borderStyle=solid}
> scala> val a = Seq((1, 2), (2, 3)).toDF("a", "b")
> a: org.apache.spark.sql.DataFrame = [a: int, b: int]
> scala> val b = Seq((2, 5), (3, 4)).toDF("a", "c")
> b: org.apache.spark.sql.DataFrame = [a: int, c: int]
> scala> val ab = a.join(b, Seq("a"), "fullouter").na.fill(0)
> ab: org.apache.spark.sql.DataFrame = [a: int, b: int ... 1 more field]
> scala> ab.show
> +---+---+---+
> |  a|  b|  c|
> +---+---+---+
> |  1|  2|  0|
> |  3|  0|  4|
> |  2|  3|  5|
> +---+---+---+
> scala> val c = Seq((3, 1)).toDF("a", "d")
> c: org.apache.spark.sql.DataFrame = [a: int, d: int]
> scala> c.show
> +---+---+
> |  a|  d|
> +---+---+
> |  3|  1|
> +---+---+
> scala> ab.join(c, "a").show
> +---+---+---+---+
> |  a|  b|  c|  d|
> +---+---+---+---+
> +---+---+---+---+
> {code}
> And again if i use persist, the result is correct. I think the problem is 
> join optimizer similar to this pr: https://github.com/apache/spark/pull/14661
> {code:title=spark-shell|borderStyle=solid}
> scala> val ab = a.join(b, Seq("a"), "outer").na.fill(0).persist
> ab: org.apache.spark.sql.Dataset[org.apache.spark.sql.Row] = [a: int, b: int 
> ... 1 more field]
> scala> ab.show
> +---+---+---+
> |  a|  b|  c|
> +---+---+---+
> |  1|  2|  0|
> |  3|  0|  4|
> |  2|  3|  5|
> +---+---+---+
> scala> ab.join(c, "a").show
> +---+---+---+---+
> |  a|  b|  c|  d|
> +---+---+---+---+
> |  3|  0|  4|  1|
> +---+---+---+---+
> {code}
>   



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[jira] [Assigned] (SPARK-17957) Calling outer join and na.fill(0) and then inner join will miss rows

2016-10-17 Thread Apache Spark (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-17957?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Apache Spark reassigned SPARK-17957:


Assignee: Xiao Li  (was: Apache Spark)

> Calling outer join and na.fill(0) and then inner join will miss rows
> 
>
> Key: SPARK-17957
> URL: https://issues.apache.org/jira/browse/SPARK-17957
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 2.0.1
> Environment: Spark 2.0.1, Mac, Local
>Reporter: Linbo
>Assignee: Xiao Li
>Priority: Critical
>  Labels: correctness
>
> I reported a similar bug two months ago and it's fixed in Spark 2.0.1: 
> https://issues.apache.org/jira/browse/SPARK-17060 But I find a new bug: when 
> I insert a na.fill(0) call between outer join and inner join in the same 
> workflow in SPARK-17060 I get wrong result.
> {code:title=spark-shell|borderStyle=solid}
> scala> val a = Seq((1, 2), (2, 3)).toDF("a", "b")
> a: org.apache.spark.sql.DataFrame = [a: int, b: int]
> scala> val b = Seq((2, 5), (3, 4)).toDF("a", "c")
> b: org.apache.spark.sql.DataFrame = [a: int, c: int]
> scala> val ab = a.join(b, Seq("a"), "fullouter").na.fill(0)
> ab: org.apache.spark.sql.DataFrame = [a: int, b: int ... 1 more field]
> scala> ab.show
> +---+---+---+
> |  a|  b|  c|
> +---+---+---+
> |  1|  2|  0|
> |  3|  0|  4|
> |  2|  3|  5|
> +---+---+---+
> scala> val c = Seq((3, 1)).toDF("a", "d")
> c: org.apache.spark.sql.DataFrame = [a: int, d: int]
> scala> c.show
> +---+---+
> |  a|  d|
> +---+---+
> |  3|  1|
> +---+---+
> scala> ab.join(c, "a").show
> +---+---+---+---+
> |  a|  b|  c|  d|
> +---+---+---+---+
> +---+---+---+---+
> {code}
> And again if i use persist, the result is correct. I think the problem is 
> join optimizer similar to this pr: https://github.com/apache/spark/pull/14661
> {code:title=spark-shell|borderStyle=solid}
> scala> val ab = a.join(b, Seq("a"), "outer").na.fill(0).persist
> ab: org.apache.spark.sql.Dataset[org.apache.spark.sql.Row] = [a: int, b: int 
> ... 1 more field]
> scala> ab.show
> +---+---+---+
> |  a|  b|  c|
> +---+---+---+
> |  1|  2|  0|
> |  3|  0|  4|
> |  2|  3|  5|
> +---+---+---+
> scala> ab.join(c, "a").show
> +---+---+---+---+
> |  a|  b|  c|  d|
> +---+---+---+---+
> |  3|  0|  4|  1|
> +---+---+---+---+
> {code}
>   



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[jira] [Assigned] (SPARK-17957) Calling outer join and na.fill(0) and then inner join will miss rows

2016-10-17 Thread Xiao Li (JIRA) 

 [ 
https://issues.apache.org/jira/browse/SPARK-17957?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
 ]

Xiao Li reassigned SPARK-17957:
---

Assignee: Xiao Li

> Calling outer join and na.fill(0) and then inner join will miss rows
> 
>
> Key: SPARK-17957
> URL: https://issues.apache.org/jira/browse/SPARK-17957
> Project: Spark
>  Issue Type: Bug
>  Components: SQL
>Affects Versions: 2.0.1
> Environment: Spark 2.0.1, Mac, Local
>Reporter: Linbo
>Assignee: Xiao Li
>Priority: Critical
>  Labels: correctness
>
> I reported a similar bug two months ago and it's fixed in Spark 2.0.1: 
> https://issues.apache.org/jira/browse/SPARK-17060 But I find a new bug: when 
> I insert a na.fill(0) call between outer join and inner join in the same 
> workflow in SPARK-17060 I get wrong result.
> {code:title=spark-shell|borderStyle=solid}
> scala> val a = Seq((1, 2), (2, 3)).toDF("a", "b")
> a: org.apache.spark.sql.DataFrame = [a: int, b: int]
> scala> val b = Seq((2, 5), (3, 4)).toDF("a", "c")
> b: org.apache.spark.sql.DataFrame = [a: int, c: int]
> scala> val ab = a.join(b, Seq("a"), "fullouter").na.fill(0)
> ab: org.apache.spark.sql.DataFrame = [a: int, b: int ... 1 more field]
> scala> ab.show
> +---+---+---+
> |  a|  b|  c|
> +---+---+---+
> |  1|  2|  0|
> |  3|  0|  4|
> |  2|  3|  5|
> +---+---+---+
> scala> val c = Seq((3, 1)).toDF("a", "d")
> c: org.apache.spark.sql.DataFrame = [a: int, d: int]
> scala> c.show
> +---+---+
> |  a|  d|
> +---+---+
> |  3|  1|
> +---+---+
> scala> ab.join(c, "a").show
> +---+---+---+---+
> |  a|  b|  c|  d|
> +---+---+---+---+
> +---+---+---+---+
> {code}
> And again if i use persist, the result is correct. I think the problem is 
> join optimizer similar to this pr: https://github.com/apache/spark/pull/14661
> {code:title=spark-shell|borderStyle=solid}
> scala> val ab = a.join(b, Seq("a"), "outer").na.fill(0).persist
> ab: org.apache.spark.sql.Dataset[org.apache.spark.sql.Row] = [a: int, b: int 
> ... 1 more field]
> scala> ab.show
> +---+---+---+
> |  a|  b|  c|
> +---+---+---+
> |  1|  2|  0|
> |  3|  0|  4|
> |  2|  3|  5|
> +---+---+---+
> scala> ab.join(c, "a").show
> +---+---+---+---+
> |  a|  b|  c|  d|
> +---+---+---+---+
> |  3|  0|  4|  1|
> +---+---+---+---+
> {code}
>   



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