Github user rxin commented on a diff in the pull request:
https://github.com/apache/spark/pull/1023#discussion_r13782641
--- Diff: sql/core/src/main/scala/org/apache/spark/sql/SchemaRDD.scala ---
@@ -343,16 +343,11 @@ class SchemaRDD(
val pickle = new Pickler
iter.map { row =>
val map: JMap[String, Any] = new java.util.HashMap
- // TODO: We place the map in an ArrayList so that the object is
pickled to a List[Dict].
- // Ideally we should be able to pickle an object directly into a
Python collection so we
- // don't have to create an ArrayList every time.
- val arr: java.util.ArrayList[Any] = new java.util.ArrayList
row.zip(fieldNames).foreach { case (obj, name) =>
map.put(name, obj)
}
- arr.add(map)
- pickle.dumps(arr)
- }
+ map
+ }.grouped(10).map(batched => pickle.dumps(batched.toArray))
--- End diff --
Do you know if grouped is stream based or does it materialize the whole
thing in memory? If it is the latter, we should rewrite it to to be stream
based.
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