[jira] [Updated] (SPARK-17957) Calling outer join and na.fill(0) and then inner join will miss rows
[ https://issues.apache.org/jira/browse/SPARK-17957?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiao Li updated SPARK-17957: Priority: Critical (was: Major) > 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 >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} > -- 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
[jira] [Updated] (SPARK-17957) Calling outer join and na.fill(0) and then inner join will miss rows
[ https://issues.apache.org/jira/browse/SPARK-17957?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiao Li updated SPARK-17957: Target Version/s: 2.0.2, 2.1.0 (was: 2.0.2) > 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 > 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} > -- 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
[jira] [Updated] (SPARK-17957) Calling outer join and na.fill(0) and then inner join will miss rows
[ https://issues.apache.org/jira/browse/SPARK-17957?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Xiao Li updated SPARK-17957: Labels: correctness (was: joins na.fill) > 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 > 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} > -- 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
[jira] [Updated] (SPARK-17957) Calling outer join and na.fill(0) and then inner join will miss rows
[ https://issues.apache.org/jira/browse/SPARK-17957?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ] Linbo updated SPARK-17957: -- Description: 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} was: 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| +---+---+---+---+ +---+---+---+---+ scala> val ab = a.join(b, Seq("a"), "outer").na.fill(0) ab: org.apache.spark.sql.DataFrame = [a: int, b: int ... 1 more field] 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} > 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 > Labels: joins, na.fill > > 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>