Github user pwoody commented on a diff in the pull request:
https://github.com/apache/spark/pull/14733#discussion_r76775733
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/columnar/InMemoryTableScanExec.scala
---
@@ -125,12 +129,37 @@ case class InMemoryTableScanExec(
val schema = relation.partitionStatistics.schema
val schemaIndex = schema.zipWithIndex
val relOutput: AttributeSeq = relation.output
- val buffers = relation.cachedColumnBuffers
+ val partitionFilter = newPredicate(
+ partitionFilters.reduceOption(And).getOrElse(Literal(true)),
+ schema)
+
+ val buffers = if (inMemoryPartitionPruningEnabled &&
!relation.batchStats.value.isEmpty) {
+ val validPartitions = relation.batchStats.value.asScala
+ .filter(batchStat => partitionFilter(batchStat._2))
+ .map(_._1)
+ .distinct
+ if (validPartitions.isEmpty) {
+ sparkContext.emptyRDD[CachedBatch]
+ } else {
+
PartitionPruningRDD.create[CachedBatch](relation.cachedColumnBuffers,
+ index => {
+ if (validPartitions.contains(index)) {
+ true
+ } else {
+ logInfo(s"Skipping partition $index because all cached
batches will be pruned")
--- End diff --
Current executor-side pruning logging is done at INFO. I have no strong
opinion either way, but this can get noisy with many partitions getting pruned.
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