Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/7301#discussion_r34230631
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/pythonUDFs.scala ---
@@ -220,6 +214,89 @@ object EvaluatePython {
// TODO(davies): we could improve this by try to cast the object to
expected type
case (c, _) => null
}
+
+
+ private val module = "pyspark.sql.types"
+
+ /**
+ * Pickler for StructType
+ */
+ private class StructTypePickler extends IObjectPickler {
+
+ private val cls = classOf[StructType]
+
+ def register(): Unit = {
+ Pickler.registerCustomPickler(cls, this)
+ }
+
+ def pickle(obj: Object, out: OutputStream, pickler: Pickler): Unit = {
+ out.write(Opcodes.GLOBAL)
+ out.write((module + "\n" + "_parse_datatype_json_string" +
"\n").getBytes)
+ val schema = obj.asInstanceOf[StructType]
+ pickler.save(schema.json)
+ out.write(Opcodes.TUPLE1)
+ out.write(Opcodes.REDUCE)
+ }
+ }
+
+ /**
+ * Pickler for InternalRow
+ */
+ private class RowPickler extends IObjectPickler {
+
+ private val cls = classOf[GenericInternalRowWithSchema]
+
+ // register this to Pickler and Unpickler
+ def register(): Unit = {
+ Pickler.registerCustomPickler(this.getClass, this)
+ Pickler.registerCustomPickler(cls, this)
+ }
+
+ def pickle(obj: Object, out: OutputStream, pickler: Pickler): Unit = {
+ if (obj == this) {
+ out.write(Opcodes.GLOBAL)
+ out.write((module + "\n" + "_create_row_inbound_converter" +
"\n").getBytes)
+ } else {
+ // it will be memorized by Pickler
+ pickler.save(this)
+ val row = obj.asInstanceOf[GenericInternalRowWithSchema]
+ // schema should always be same object for memorization
+ pickler.save(row.schema)
+ out.write(Opcodes.TUPLE1)
+ out.write(Opcodes.REDUCE)
+
+ out.write(Opcodes.MARK)
+ row.values.foreach(pickler.save)
--- End diff --
For performance, should we use a `while` loop here instead of `foreach`?
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