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From "Hyukjin Kwon (JIRA)" <j...@apache.org>
Subject [jira] [Commented] (SPARK-24051) Incorrect results for certain queries using Java and Python APIs on Spark 2.3.0
Date Tue, 24 Apr 2018 00:51:00 GMT

    [ https://issues.apache.org/jira/browse/SPARK-24051?page=com.atlassian.jira.plugin.system.issuetabpanels:comment-tabpanel&focusedCommentId=16449122#comment-16449122
] 

Hyukjin Kwon commented on SPARK-24051:
--------------------------------------

Thanks for elaborating it. The details look very helpful. Will try to have some time to take
a look as well.

> Incorrect results for certain queries using Java and Python APIs on Spark 2.3.0
> -------------------------------------------------------------------------------
>
>                 Key: SPARK-24051
>                 URL: https://issues.apache.org/jira/browse/SPARK-24051
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.3.0
>            Reporter: Emlyn Corrin
>            Priority: Major
>
> I'm seeing Spark 2.3.0 return incorrect results for a certain (very specific) query,
demonstrated by the Java program below. It was simplified from a much more complex query,
but I'm having trouble simplifying it further without removing the erroneous behaviour.
> {code:java}
> package sparktest;
> import org.apache.spark.SparkConf;
> import org.apache.spark.sql.*;
> import org.apache.spark.sql.expressions.Window;
> import org.apache.spark.sql.types.DataTypes;
> import org.apache.spark.sql.types.Metadata;
> import org.apache.spark.sql.types.StructField;
> import org.apache.spark.sql.types.StructType;
> import java.util.Arrays;
> public class Main {
>     public static void main(String[] args) {
>         SparkConf conf = new SparkConf()
>                 .setAppName("SparkTest")
>                 .setMaster("local[*]");
>         SparkSession session = SparkSession.builder().config(conf).getOrCreate();
>         Row[] arr1 = new Row[]{
>                 RowFactory.create(1, 42),
>                 RowFactory.create(2, 99)};
>         StructType sch1 = new StructType(new StructField[]{
>                 new StructField("a", DataTypes.IntegerType, true, Metadata.empty()),
>                 new StructField("b", DataTypes.IntegerType, true, Metadata.empty())});
>         Dataset<Row> ds1 = session.createDataFrame(Arrays.asList(arr1), sch1);
>         ds1.show();
>         Row[] arr2 = new Row[]{
>                 RowFactory.create(3)};
>         StructType sch2 = new StructType(new StructField[]{
>                 new StructField("a", DataTypes.IntegerType, true, Metadata.empty())});
>         Dataset<Row> ds2 = session.createDataFrame(Arrays.asList(arr2), sch2)
>                 .withColumn("b", functions.lit(0));
>         ds2.show();
>         Column[] cols = new Column[]{
>                 new Column("a"),
>                 new Column("b").as("b"),
>                 functions.count(functions.lit(1))
>                         .over(Window.partitionBy())
>                         .as("n")};
>         Dataset<Row> ds = ds1
>                 .select(cols)
>                 .union(ds2.select(cols))
>                 .where(new Column("n").geq(1))
>                 .drop("n");
>         ds.show();
>         //ds.explain(true);
>     }
> }
> {code}
> It just calculates the union of 2 datasets,
> {code:java}
> +---+---+
> |  a|  b|
> +---+---+
> |  1| 42|
> |  2| 99|
> +---+---+
> {code}
> with
> {code:java}
> +---+---+
> |  a|  b|
> +---+---+
> |  3|  0|
> +---+---+
> {code}
> The expected result is:
> {code:java}
> +---+---+
> |  a|  b|
> +---+---+
> |  1| 42|
> |  2| 99|
> |  3|  0|
> +---+---+
> {code}
> but instead it prints:
> {code:java}
> +---+---+
> |  a|  b|
> +---+---+
> |  1|  0|
> |  2|  0|
> |  3|  0|
> +---+---+
> {code}
> notice how the value in column c is always zero, overriding the original values in rows
1 and 2.
>  Making seemingly trivial changes, such as replacing {{new Column("b").as("b"),}} with
just {{new Column("b"),}} or removing the {{where}} clause after the union, make it behave
correctly again.



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