Github user JoshRosen commented on a diff in the pull request:
https://github.com/apache/spark/pull/6397#discussion_r31006414
--- Diff:
core/src/main/scala/org/apache/spark/util/collection/ExternalSorter.scala ---
@@ -123,43 +130,28 @@ private[spark] class ExternalSorter[K, V, C](
// grow internal data structures by growing + copying every time the
number of objects doubles.
private val serializerBatchSize =
conf.getLong("spark.shuffle.spill.batchSize", 10000)
- private def getPartition(key: K): Int = {
- if (shouldPartition) partitioner.get.getPartition(key) else 0
- }
-
- private val metaInitialRecords = 256
- private val kvChunkSize = conf.getInt("spark.shuffle.sort.kvChunkSize",
1 << 22) // 4 MB
- private val useSerializedPairBuffer =
- !ordering.isDefined &&
conf.getBoolean("spark.shuffle.sort.serializeMapOutputs", true) &&
- ser.supportsRelocationOfSerializedObjects
-
// Data structures to store in-memory objects before we spill. Depending
on whether we have an
// Aggregator set, we either put objects into an AppendOnlyMap where we
combine them, or we
// store them in an array buffer.
- private var map = new PartitionedAppendOnlyMap[K, C]
- private var buffer = if (useSerializedPairBuffer) {
- new PartitionedSerializedPairBuffer[K, C](metaInitialRecords,
kvChunkSize, serInstance)
- } else {
- new PartitionedPairBuffer[K, C]
+ private def newBuffer: () => WritablePartitionedPairCollection[K, C]
with SizeTracker = {
--- End diff --
Ah, I got a bit too clever here. My idea was to reduce the visibility of
variables like `useSerializedPairBuffer` without having to recompute them on
each call to `newBuffer(0)`, so I had this block of code effectively return a
factory for creating buffers based on a configuration which is read once.
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