Github user HyukjinKwon commented on a diff in the pull request:
https://github.com/apache/spark/pull/15354#discussion_r85630778
--- Diff:
sql/catalyst/src/main/scala/org/apache/spark/sql/catalyst/expressions/jsonExpressions.scala
---
@@ -494,3 +495,46 @@ case class JsonToStruct(schema: StructType, options:
Map[String, String], child:
override def inputTypes: Seq[AbstractDataType] = StringType :: Nil
}
+
+/**
+ * Converts a [[StructType]] to a json output string.
+ */
+case class StructToJson(options: Map[String, String], child: Expression)
+ extends Expression with CodegenFallback with ExpectsInputTypes {
+ override def nullable: Boolean = true
+
+ @transient
+ lazy val writer = new CharArrayWriter()
+
+ @transient
+ lazy val gen =
+ new JacksonGenerator(child.dataType.asInstanceOf[StructType], writer)
+
+ override def dataType: DataType = StringType
+ override def children: Seq[Expression] = child :: Nil
+
+ override def checkInputDataTypes(): TypeCheckResult = {
+ if (StructType.acceptsType(child.dataType)) {
+ try {
--- End diff --
Ah, yes, makes sense but if `verifySchema` returns a boolean, we could not
find which field and type are problematic.
Maybe, I can make do one of the below:
- this logic in `verifySchema` into `checkInputDataTypes`
- `verifySchema` returns the unsupported fields. and types.
- Just fix the exception message without the information of unsupported
fields and types.
If you pick one, I will follow (or please let me know if there is a better
way)!
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