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

    https://github.com/apache/spark/pull/21560#discussion_r196999745
  
    --- 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 --
    
    We are addressing only the specific case that number of partitions is 1, 
but we could have some assertion for that and try to write complete code so 
that we don't modify it again.


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