AngersZhuuuu commented on a change in pull request #30957:
URL: https://github.com/apache/spark/pull/30957#discussion_r550230592
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File path:
sql/core/src/main/scala/org/apache/spark/sql/execution/BaseScriptTransformationExec.scala
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@@ -329,14 +332,45 @@ case class ScriptTransformationIOSchema(
schemaLess: Boolean) extends Serializable {
import ScriptTransformationIOSchema._
- val inputRowFormatMap = inputRowFormat.toMap.withDefault((k) =>
defaultFormat(k))
- val outputRowFormatMap = outputRowFormat.toMap.withDefault((k) =>
defaultFormat(k))
+ val inputRowFormatMap = inputRowFormat.toMap.withDefault(k =>
defaultFormat(k))
+ val outputRowFormatMap = outputRowFormat.toMap.withDefault(k =>
defaultFormat(k))
+
+ val separators = (getByte(inputRowFormatMap("TOK_TABLEROWFORMATFIELD"),
0.toByte) ::
+ getByte(inputRowFormatMap("TOK_TABLEROWFORMATCOLLITEMS"), 1.toByte) ::
+ getByte(inputRowFormatMap("TOK_TABLEROWFORMATMAPKEYS"), 2.toByte) :: Nil)
++
+ (4 to 8).map(_.toByte)
Review comment:
> we cannot write a custom parser for nested arrays just like a json
parser?
you mean similar like `DelimitedJSONSerDe` ? I think default way should like
`LazySimpleSerde` and keep same with hive.
Construct Json string should be done in spark sql transform(no-serde)'s own
serde. @Alfozan have done this and he will raise pr.
https://github.com/apache/spark/pull/29085#issuecomment-658131729
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