Github user gatorsmile commented on a diff in the pull request:

    https://github.com/apache/spark/pull/10942#discussion_r51531853
  
    --- 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 =>
    +        DataSourceStrategy.getBucketId(
    +          bucketColumn, numBuckets, row.get(bucketColumnIndex, 
bucketColumn.dataType)))})
    +    // Check if all the returned rows are from the non-pruned buckets
    +    assert(checkBucketId.collect().forall(matchedBuckets.get))
    +
    +    checkAnswer(
    +      expectedAnswer
    +        .orderBy(expectedAnswer.logicalPlan.output.map(attr => 
Column(attr)) : _*),
    --- End diff --
    
    There is a test case which is using a different Dataframe `nullStrings`. 
Thus, the schema is different. If you want, I can create a dataFrame with the 
same schema for this test case. Let me know if you want me to do the change. 
Thanks! 


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