Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/14864#discussion_r77122392
--- Diff:
sql/core/src/main/scala/org/apache/spark/sql/execution/DataSourceScanExec.scala
---
@@ -156,24 +156,56 @@ case class FileSourceScanExec(
false
}
- override val outputPartitioning: Partitioning = {
+ override val (outputPartitioning, outputOrdering): (Partitioning,
Seq[SortOrder]) = {
val bucketSpec = if
(relation.sparkSession.sessionState.conf.bucketingEnabled) {
relation.bucketSpec
} else {
None
}
- bucketSpec.map { spec =>
- val numBuckets = spec.numBuckets
- val bucketColumns = spec.bucketColumnNames.flatMap { n =>
- output.find(_.name == n)
- }
- if (bucketColumns.size == spec.bucketColumnNames.size) {
- HashPartitioning(bucketColumns, numBuckets)
- } else {
- UnknownPartitioning(0)
- }
- }.getOrElse {
- UnknownPartitioning(0)
+ bucketSpec match {
+ case Some(spec) =>
+ val numBuckets = spec.numBuckets
+ val bucketColumns = spec.bucketColumnNames.flatMap { n =>
+ output.find(_.name == n)
+ }
+ if (bucketColumns.size == spec.bucketColumnNames.size) {
+ val partitioning = HashPartitioning(bucketColumns, numBuckets)
+
+ val sortOrder = if (spec.sortColumnNames.nonEmpty) {
+ // In case of bucketing, its possible to have multiple files
belonging to the
+ // same bucket in a given relation. Each of these files are
locally sorted
+ // but those files combined together are not globally sorted.
Given that,
+ // the RDD partition will not be sorted even if the relation
has sort columns set
+ // Current solution is to check if all the buckets have a
single file in it
+
+ val files =
+
relation.location.listFiles(partitionFilters).flatMap(partition =>
partition.files)
+ val bucketToFilesGrouping =
+ files.map(_.getPath.getName).groupBy(file =>
BucketingUtils.getBucketId(file))
+ val singleFilePartitions = bucketToFilesGrouping.forall(p =>
p._2.length <= 1)
--- End diff --
yea that's a good question, single file per bucket looks more reasonable,
it's more important to read bucketed table fast than writing it fast. But how
about data insertion? Does hive support inserting into bucketed table?
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