Github user MaxGekk commented on a diff in the pull request:
https://github.com/apache/spark/pull/22938#discussion_r231783277
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/jsonExpressions.scala
---
@@ -550,15 +550,33 @@ case class JsonToStructs(
s"Input schema ${nullableSchema.catalogString} must be a struct, an
array or a map.")
}
- // This converts parsed rows to the desired output by the given schema.
@transient
- lazy val converter = nullableSchema match {
- case _: StructType =>
- (rows: Iterator[InternalRow]) => if (rows.hasNext) rows.next() else
null
- case _: ArrayType =>
- (rows: Iterator[InternalRow]) => if (rows.hasNext)
rows.next().getArray(0) else null
- case _: MapType =>
- (rows: Iterator[InternalRow]) => if (rows.hasNext)
rows.next().getMap(0) else null
+ private lazy val castRow = nullableSchema match {
+ case _: StructType => (row: InternalRow) => row
+ case _: ArrayType => (row: InternalRow) =>
+ if (row.isNullAt(0)) {
+ new GenericArrayData(Array())
--- End diff --
I also thought what is better to return here - `null` or empty
`Array`/`MapData`. In the case of `StructType` we return `Row` in the
`PERMISSIVE` mode. For consistency should we return empty array/map in this
mode too?
Maybe we can consider special mode when we can return `null` for the bad
record? For now it is easy to do since we use `FailureSafeParser`.
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