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From "Apache Spark (JIRA)" <j...@apache.org>
Subject [jira] [Assigned] (SPARK-23835) When Dataset.as converts column from nullable to non-nullable type, null Doubles are converted silently to -1
Date Wed, 04 Apr 2018 15:21:00 GMT

     [ https://issues.apache.org/jira/browse/SPARK-23835?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel
]

Apache Spark reassigned SPARK-23835:
------------------------------------

    Assignee: Apache Spark

> When Dataset.as converts column from nullable to non-nullable type, null Doubles are
converted silently to -1
> -------------------------------------------------------------------------------------------------------------
>
>                 Key: SPARK-23835
>                 URL: https://issues.apache.org/jira/browse/SPARK-23835
>             Project: Spark
>          Issue Type: Bug
>          Components: SQL
>    Affects Versions: 2.3.0
>            Reporter: Joseph K. Bradley
>            Assignee: Apache Spark
>            Priority: Major
>
> I constructed a DataFrame with a nullable java.lang.Double column (and an extra Double
column).  I then converted it to a Dataset using ```as[(Double, Double)]```.  When the Dataset
is shown, it has a null.  When it is collected and printed, the null is silently converted
to a -1.
> Code snippet to reproduce this:
> {code}
> val localSpark = spark
> import localSpark.implicits._
> val df = Seq[(java.lang.Double, Double)](
>   (1.0, 2.0),
>   (3.0, 4.0),
>   (Double.NaN, 5.0),
>   (null, 6.0)
> ).toDF("a", "b")
> df.show()  // OUTPUT 1: has null
> df.printSchema()
> val data = df.as[(Double, Double)]
> data.show()  // OUTPUT 2: has null
> data.collect().foreach(println)  // OUTPUT 3: has -1
> {code}
> OUTPUT 1 and 2:
> {code}
> +----+---+
> |   a|  b|
> +----+---+
> | 1.0|2.0|
> | 3.0|4.0|
> | NaN|5.0|
> |null|6.0|
> +----+---+
> {code}
> OUTPUT 3:
> {code}
> (1.0,2.0)
> (3.0,4.0)
> (NaN,5.0)
> (-1.0,6.0)
> {code}



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