Github user cloud-fan commented on a diff in the pull request:
https://github.com/apache/spark/pull/10942#discussion_r51392868
--- Diff:
sql/hive/src/test/scala/org/apache/spark/sql/sources/BucketedReadSuite.scala ---
@@ -59,6 +61,159 @@ class BucketedReadSuite extends QueryTest with
SQLTestUtils with TestHiveSinglet
}
}
+ // To verify if the bucket pruning works, this function checks two
conditions:
+ // 1) Check if the pruned buckets (before filtering) are empty.
+ // 2) Verify the final result is the same as the expected one
+ private def checkPrunedAnswers(
+ bucketSpec: BucketSpec,
+ bucketValues: Seq[Integer],
+ bucketedDataFrame: DataFrame,
+ expectedAnswer: DataFrame): Unit = {
+
+ val BucketSpec(numBuckets, bucketColumnNames, _) = bucketSpec
+ // Limit: bucket pruning only works when the bucket column has one and
only one column
+ assert(bucketColumnNames.length == 1)
+ val bucketColumnIndex =
bucketedDataFrame.schema.fieldIndex(bucketColumnNames.head)
+ val bucketColumn = bucketedDataFrame.schema.toAttributes.head
+ val matchedBuckets = new BitSet(numBuckets)
+ bucketValues.foreach { value =>
+ matchedBuckets.set(DataSourceStrategy.getBucketId(bucketColumn,
numBuckets, value))
+ }
+
+ // Filter could hide the bug in bucket pruning. Thus, skipping all the
filters
+ val rdd =
bucketedDataFrame.queryExecution.executedPlan.find(_.isInstanceOf[PhysicalRDD])
+ assert(rdd.isDefined)
+
+ val checkBucketId = rdd.get.execute().map(_.copy()).mapPartitions(iter
=> {
+ iter.map(row =>
--- End diff --
I think we don't need to check every row here, but only partition id:
```
val checkedResult = rdd.get.execute().mapPartitionsWithIndex {
case (index, iter) => if (index == should be prunned bucket id)
Iterator(iter.isEmpty) else Iterator(true)
}
assert(checkedResult.collect().forall(_ == true))
```
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