JkSelf commented on a change in pull request #25295: [SPARK-28560][SQL] 
Optimize shuffle reader to local shuffle reader when smj converted to bhj in 
adaptive execution
URL: https://github.com/apache/spark/pull/25295#discussion_r323548060

 File path: 
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+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements.  See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License.  You may obtain a copy of the License at
+ *
+ *    http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
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+ * See the License for the specific language governing permissions and
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+ */
+package org.apache.spark.sql.execution.adaptive
+import org.apache.spark._
+import org.apache.spark.rdd.{RDD, ShuffledRDDPartition}
+import org.apache.spark.sql.catalyst.InternalRow
+import org.apache.spark.sql.execution.metric.{SQLMetric, 
+ * This is a specialized version of 
[[org.apache.spark.sql.execution.ShuffledRowRDD]]. This is used
+ * in Spark SQL adaptive execution when a shuffle join is converted to 
broadcast join at runtime
+ * because the map output of one input table is small enough for broadcast. 
This RDD represents the
+ * data of another input table of the join that reads from shuffle. Each 
partition of the RDD reads
+ * the whole data from just one mapper output locally. So actually there is no 
data transferred
+ * from the network.
+ * This RDD takes a [[ShuffleDependency]] (`dependency`).
+ *
+ * The `dependency` has the parent RDD of this RDD, which represents the 
dataset before shuffle
+ * (i.e. map output). Elements of this RDD are (partitionId, Row) pairs.
+ * Partition ids should be in the range [0, numPartitions - 1].
+ * `dependency.partitioner.numPartitions` is the number of pre-shuffle 
partitions. (i.e. the number
+ * of partitions of the map output). The post-shuffle partition number is the 
same to the parent
+ * RDD's partition number.
+ */
+class LocalShuffledRowRDD(
+     var dependency: ShuffleDependency[Int, InternalRow, InternalRow],
+     metrics: Map[String, SQLMetric],
+     specifiedPartitionStartIndices: Option[Array[Int]] = None,
+     specifiedPartitionEndIndices: Option[Array[Int]] = None)
 Review comment:
   Currently not. We may need the `specifiedPartitionEndIndices `variable to 
skip the partitions with 0 size in the following optimization. And I will 
retain and use it when create `LocalShuffledRowRDD `later.

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