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From "Joseph K. Bradley (JIRA)" <j...@apache.org>
Subject [jira] [Created] (SPARK-23835) When Dataset.as converts column from nullable to non-nullable type, null Doubles are converted silently to -1
Date Fri, 30 Mar 2018 18:23:00 GMT
Joseph K. Bradley created SPARK-23835:
-----------------------------------------

             Summary: 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


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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