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Posted to issues@spark.apache.org by "Xiao Li (JIRA)" <ji...@apache.org> on 2017/08/17 23:38:00 UTC
[jira] [Resolved] (SPARK-21677) json_tuple throws
NullPointException when column is null as string type.
[ https://issues.apache.org/jira/browse/SPARK-21677?page=com.atlassian.jira.plugin.system.issuetabpanels:all-tabpanel ]
Xiao Li resolved SPARK-21677.
-----------------------------
Resolution: Fixed
Fix Version/s: 2.3.0
> json_tuple throws NullPointException when column is null as string type.
> ------------------------------------------------------------------------
>
> Key: SPARK-21677
> URL: https://issues.apache.org/jira/browse/SPARK-21677
> Project: Spark
> Issue Type: Bug
> Components: SQL
> Affects Versions: 2.3.0
> Reporter: Hyukjin Kwon
> Assignee: Jen-Ming Chung
> Priority: Minor
> Labels: Starter
> Fix For: 2.3.0
>
>
> I was testing {{json_tuple}} before using this to extract values from JSONs in my testing cluster but I found it could actually throw {{NullPointException}} as below sometimes:
> {code}
> scala> Seq(("""{"Hyukjin": 224, "John": 1225}""")).toDS.selectExpr("json_tuple(value, trim(' Hyukjin '))").show()
> +---+
> | c0|
> +---+
> |224|
> +---+
> scala> Seq(("""{"Hyukjin": 224, "John": 1225}""")).toDS.selectExpr("json_tuple(value, trim(' Jackson '))").show()
> +----+
> | c0|
> +----+
> |null|
> +----+
> scala> Seq(("""{"Hyukjin": 224, "John": 1225}""")).toDS.selectExpr("json_tuple(value, trim(null))").show()
> ...
> java.lang.NullPointerException
> at org.apache.spark.sql.catalyst.expressions.JsonTuple$$anonfun$foldableFieldNames$1.apply(jsonExpressions.scala:367)
> at org.apache.spark.sql.catalyst.expressions.JsonTuple$$anonfun$foldableFieldNames$1.apply(jsonExpressions.scala:366)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.TraversableLike$$anonfun$map$1.apply(TraversableLike.scala:234)
> at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
> at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:48)
> at scala.collection.TraversableLike$class.map(TraversableLike.scala:234)
> at scala.collection.AbstractTraversable.map(Traversable.scala:104)
> at org.apache.spark.sql.catalyst.expressions.JsonTuple.foldableFieldNames$lzycompute(jsonExpressions.scala:366)
> at org.apache.spark.sql.catalyst.expressions.JsonTuple.foldableFieldNames(jsonExpressions.scala:365)
> at org.apache.spark.sql.catalyst.expressions.JsonTuple.constantFields$lzycompute(jsonExpressions.scala:373)
> at org.apache.spark.sql.catalyst.expressions.JsonTuple.constantFields(jsonExpressions.scala:373)
> at org.apache.spark.sql.catalyst.expressions.JsonTuple.org$apache$spark$sql$catalyst$expressions$JsonTuple$$parseRow(jsonExpressions.scala:417)
> at org.apache.spark.sql.catalyst.expressions.JsonTuple$$anonfun$eval$4.apply(jsonExpressions.scala:401)
> at org.apache.spark.sql.catalyst.expressions.JsonTuple$$anonfun$eval$4.apply(jsonExpressions.scala:400)
> at org.apache.spark.util.Utils$.tryWithResource(Utils.scala:2559)
> at org.apache.spark.sql.catalyst.expressions.JsonTuple.eval(jsonExpressions.scala:400)
> {code}
> It sounds we should show explicit error messages or return {{NULL}}.
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