Details
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Bug
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Status: Resolved
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Minor
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Resolution: Not A Problem
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2.4.0
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None
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Linux CentOS, Databricks.
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Patch
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Why does Some(null) throw NullPointerException in Spark 2.4 (but worked in 2.2)?
Description
Please refer to https://stackoverflow.com/questions/54851205/why-does-somenull-throw-nullpointerexception-in-spark-2-4-but-worked-in-2-2/54861152#54861152.
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 ensues.
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$1(TraversableLike.scala:233) at scala.collection.immutable.List.foreach(List.scala:388) at scala.collection.TraversableLike.map(TraversableLike.scala:233) at scala.collection.TraversableLike.map$(TraversableLike.scala:226) at scala.collection.immutable.List.map(List.scala:294) 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(UnsafeWriter.java:109) 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.