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[SPARK-2875] [PySpark] [SQL] handle null in schemaRDD() #1802

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[SPARK-2875] [PySpark] [SQL] handle null in schemaRDD() #1802

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7 changes: 7 additions & 0 deletions python/pyspark/sql.py
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Original file line number Diff line number Diff line change
Expand Up @@ -1231,6 +1231,13 @@ def jsonRDD(self, rdd, schema=None):
... "field3.field5[0] as f3 from table3")
>>> srdd6.collect()
[Row(f1=u'row1', f2=None,...Row(f1=u'row3', f2=[], f3=None)]

>>> sqlCtx.jsonRDD(sc.parallelize(['{}',
... '{"key0": {"key1": "value1"}}'])).collect()
[Row(key0=None), Row(key0=Row(key1=u'value1'))]
>>> sqlCtx.jsonRDD(sc.parallelize(['{"key0": null}',
... '{"key0": {"key1": "value1"}}'])).collect()
[Row(key0=None), Row(key0=Row(key1=u'value1'))]
"""

def func(iterator):
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27 changes: 16 additions & 11 deletions sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala
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Expand Up @@ -382,21 +382,26 @@ class SchemaRDD(
private[sql] def javaToPython: JavaRDD[Array[Byte]] = {
import scala.collection.Map

def toJava(obj: Any, dataType: DataType): Any = dataType match {
case struct: StructType => rowToArray(obj.asInstanceOf[Row], struct)
case array: ArrayType => obj match {
case seq: Seq[Any] => seq.map(x => toJava(x, array.elementType)).asJava
case list: JList[_] => list.map(x => toJava(x, array.elementType)).asJava
case arr if arr != null && arr.getClass.isArray =>
arr.asInstanceOf[Array[Any]].map(x => toJava(x, array.elementType))
case other => other
}
case mt: MapType => obj.asInstanceOf[Map[_, _]].map {
def toJava(obj: Any, dataType: DataType): Any = (obj, dataType) match {
case (null, _) => null

case (obj: Row, struct: StructType) => rowToArray(obj, struct)

case (seq: Seq[Any], array: ArrayType) =>
seq.map(x => toJava(x, array.elementType)).asJava
case (list: JList[_], array: ArrayType) =>
list.map(x => toJava(x, array.elementType)).asJava
case (arr, array: ArrayType) if arr.getClass.isArray =>
arr.asInstanceOf[Array[Any]].map(x => toJava(x, array.elementType))

case (obj: Map[_, _], mt: MapType) => obj.map {
case (k, v) => (k, toJava(v, mt.valueType)) // key should be primitive type
}.asJava

// Pyrolite can handle Timestamp
case other => obj
case (other, _) => other
}

def rowToArray(row: Row, structType: StructType): Array[Any] = {
val fields = structType.fields.map(field => field.dataType)
row.zip(fields).map {
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