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

    https://github.com/apache/spark/pull/21560#discussion_r197526872
  
    --- Diff: 
sql/core/src/main/scala/org/apache/spark/sql/execution/streaming/continuous/ContinuousCoalesceRDD.scala
 ---
    @@ -0,0 +1,108 @@
    +/*
    + * 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,
    + * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
    + * See the License for the specific language governing permissions and
    + * limitations under the License.
    + */
    +
    +package org.apache.spark.sql.execution.streaming.continuous
    +
    +import org.apache.spark._
    +import org.apache.spark.rdd.{CoalescedRDDPartition, RDD}
    +import org.apache.spark.sql.catalyst.InternalRow
    +import org.apache.spark.sql.catalyst.expressions.UnsafeRow
    +import org.apache.spark.sql.execution.streaming.continuous.shuffle._
    +import org.apache.spark.util.ThreadUtils
    +
    +case class ContinuousCoalesceRDDPartition(index: Int) extends Partition {
    +  // This flag will be flipped on the executors to indicate that the 
threads processing
    +  // partitions of the write-side RDD have been started. These will run 
indefinitely
    +  // asynchronously as epochs of the coalesce RDD complete on the read 
side.
    +  private[continuous] var writersInitialized: Boolean = false
    +}
    +
    +/**
    + * RDD for continuous coalescing. Asynchronously writes all partitions of 
`prev` into a local
    + * continuous shuffle, and then reads them in the task thread using 
`reader`.
    + */
    +class ContinuousCoalesceRDD(
    +    context: SparkContext,
    +    numPartitions: Int,
    +    readerQueueSize: Int,
    +    epochIntervalMs: Long,
    +    readerEndpointName: String,
    +    prev: RDD[InternalRow])
    +  extends RDD[InternalRow](context, Nil) {
    +
    +  override def getPartitions: Array[Partition] = 
Array(ContinuousCoalesceRDDPartition(0))
    --- End diff --
    
    Agree. And since theres an `assert (numpartitions == 1)` in 
`ContinuousCoalesceExec`, we can probably create any array of `numPartitions` 
here.


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