cloud-fan commented on code in PR #48407:
URL: https://github.com/apache/spark/pull/48407#discussion_r1914519467
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sql/core/src/main/scala/org/apache/spark/sql/execution/SparkStrategies.scala:
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@@ -82,27 +82,47 @@ abstract class SparkStrategies extends
QueryPlanner[SparkPlan] {
*/
object SpecialLimits extends Strategy {
override def apply(plan: LogicalPlan): Seq[SparkPlan] = plan match {
+ // Match the serialization pattern for case of Dataset.toJSON
// Call `planTakeOrdered` first which matches a larger plan.
- case ReturnAnswer(rootPlan) =>
planTakeOrdered(rootPlan).getOrElse(rootPlan match {
- // We should match the combination of limit and offset first, to get
the optimal physical
- // plan, instead of planning limit and offset separately.
- case LimitAndOffset(limit, offset, child) =>
- CollectLimitExec(limit = limit, child = planLater(child), offset =
offset)
- case OffsetAndLimit(offset, limit, child) =>
- // 'Offset a' then 'Limit b' is the same as 'Limit a + b' then
'Offset a'.
- CollectLimitExec(limit = offset + limit, child = planLater(child),
offset = offset)
- case Limit(IntegerLiteral(limit), child) =>
- CollectLimitExec(limit = limit, child = planLater(child))
- case logical.Offset(IntegerLiteral(offset), child) =>
- CollectLimitExec(child = planLater(child), offset = offset)
- case Tail(IntegerLiteral(limit), child) =>
- CollectTailExec(limit, planLater(child))
- case other => planLater(other)
- }) :: Nil
+ case ReturnAnswer(
+ SerializeFromObject(
+ serializer,
+ MapPartitions(
+ f,
Review Comment:
I'm not sure if it's safe to apply this special limit optimization for
`MapPartitions` with an arbitrary lambda function.
Are we able to implement `df.toJSON` with `Project` and the `to_json`
function?
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