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[SPARK-3447][SQL] Remove explicit conversion with JListWrapper to avoid NPE #2323

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[SPARK-3447][SQL] Remove explicit conversion with JListWrapper to avoid NPE #2323

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59065bc
Remove explicit conversion to avoid NPE
marmbrus Sep 8, 2014
646976b
Fix JSON RDD Conversion too
marmbrus Sep 10, 2014
4d4d93c
Merge remote-tracking branch 'origin/master' into kryoJListNPE
marmbrus Sep 11, 2014
9634f11
Rollback JSON RDD changes
marmbrus Sep 11, 2014
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4 changes: 1 addition & 3 deletions sql/core/src/main/scala/org/apache/spark/sql/SQLContext.scala
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Original file line number Diff line number Diff line change
Expand Up @@ -460,7 +460,6 @@ class SQLContext(@transient val sparkContext: SparkContext)
rdd: RDD[Array[Any]],
schema: StructType): SchemaRDD = {
import scala.collection.JavaConversions._
import scala.collection.convert.Wrappers.{JListWrapper, JMapWrapper}

def needsConversion(dataType: DataType): Boolean = dataType match {
case ByteType => true
Expand All @@ -482,8 +481,7 @@ class SQLContext(@transient val sparkContext: SparkContext)
case (null, _) => null

case (c: java.util.List[_], ArrayType(elementType, _)) =>
val converted = c.map { e => convert(e, elementType)}
JListWrapper(converted)
c.map { e => convert(e, elementType)}: Seq[Any]

case (c, ArrayType(elementType, _)) if c.getClass.isArray =>
c.asInstanceOf[Array[_]].map(e => convert(e, elementType)): Seq[Any]
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5 changes: 3 additions & 2 deletions sql/core/src/main/scala/org/apache/spark/sql/json/JsonRDD.scala
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Expand Up @@ -18,7 +18,8 @@
package org.apache.spark.sql.json

import scala.collection.Map
import scala.collection.convert.Wrappers.{JMapWrapper, JListWrapper}
import scala.collection.JavaConversions._
import scala.collection.convert.Wrappers.JMapWrapper
import scala.math.BigDecimal

import com.fasterxml.jackson.databind.ObjectMapper
Expand Down Expand Up @@ -253,7 +254,7 @@ private[sql] object JsonRDD extends Logging {
// This issue is documented at https://issues.scala-lang.org/browse/SI-7005
JMapWrapper(map).mapValues(scalafy).map(identity)
case list: java.util.List[_] =>
JListWrapper(list).map(scalafy)
(list: Seq[_]).map(scalafy)
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Oh, after checking the code again, I think .map(scalafy) will convert the JListWrapper at here to an ArrayBuffer (JListWrapper is a Buffer and Buffer's newBuilder returns ArrayBuffer) and we will not have the Kryo issue. I tried from pyspark.sql import SQLContext;SQLContext(sc).jsonRDD(sc.parallelize(['{"a":[3]}']))._jschema_rdd.collect() and it's fine.

case atom => atom
}

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