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From "Gerard Alexander (JIRA)" <>
Subject [jira] [Created] (SPARK-26984) Incompatibility between Spark releases - Some(null)
Date Mon, 25 Feb 2019 08:51:00 GMT
Gerard Alexander created SPARK-26984:

             Summary: Incompatibility between Spark releases - Some(null) 
                 Key: SPARK-26984
             Project: Spark
          Issue Type: Bug
          Components: Spark Core
    Affects Versions: 2.4.0
         Environment: Linux CentOS, Databricks.
            Reporter: Gerard Alexander
             Fix For: 2.4.1, 2.4.2

Please refer to []

NB: Not sure of priority being correct - no doubt one will evaluate.

It is noted that the following:

{{val df = Seq( }}

{{  (1, Some("a"), Some(1)), }}

{{  (2, Some(null), Some(2)), }}

{{  (3, Some("c"), Some(3)), }}

{{  (4, None, None) ).toDF("c1", "c2", "c3")}}

In Spark 2.2.1 (on mapr) the Some(null) works fine, in Spark 2.4.0 on Databricks an error

{{java.lang.RuntimeException: Error while encoding: java.lang.NullPointerException assertnotnull(assertnotnull(input[0,
scala.Tuple3, true]))._1 AS _1#6 staticinvoke(class org.apache.spark.unsafe.types.UTF8String,
StringType, fromString, unwrapoption(ObjectType(class java.lang.String), assertnotnull(assertnotnull(input[0,
scala.Tuple3, true]))._2), true, false) AS _2#7 unwrapoption(IntegerType, assertnotnull(assertnotnull(input[0,
scala.Tuple3, true]))._3) AS _3#8 at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.toRow(ExpressionEncoder.scala:293)
at org.apache.spark.sql.SparkSession.$anonfun$createDataset$1(SparkSession.scala:472) at scala.collection.TraversableLike.$anonfun$map$1(TraversableLike.scala:233)
at scala.collection.immutable.List.foreach(List.scala:388) at
at$(TraversableLike.scala:226) at
at org.apache.spark.sql.SparkSession.createDataset(SparkSession.scala:472) at org.apache.spark.sql.SQLContext.createDataset(SQLContext.scala:377)
at org.apache.spark.sql.SQLImplicits.localSeqToDatasetHolder(SQLImplicits.scala:228) ... 57
elided Caused by: java.lang.NullPointerException at org.apache.spark.sql.catalyst.expressions.codegen.UnsafeWriter.write(
at org.apache.spark.sql.catalyst.expressions.GeneratedClass$SpecificUnsafeProjection.apply(Unknown
Source) at org.apache.spark.sql.catalyst.encoders.ExpressionEncoder.toRow(ExpressionEncoder.scala:289)
... 66 more}}


You can argue it is solvable otherwise, but there may well be an existing code base that could
be affected.



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