Github user jose-torres commented on a diff in the pull request: https://github.com/apache/spark/pull/21337#discussion_r188831887 --- Diff: sql/core/src/test/scala/org/apache/spark/sql/streaming/continuous/shuffle/ContinuousShuffleReadSuite.scala --- @@ -0,0 +1,122 @@ +/* + * 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.shuffle + +import org.apache.spark.{TaskContext, TaskContextImpl} +import org.apache.spark.sql.catalyst.expressions.{GenericInternalRow, UnsafeProjection} +import org.apache.spark.sql.streaming.StreamTest +import org.apache.spark.sql.types.{DataType, IntegerType} + +class ContinuousShuffleReadSuite extends StreamTest { + + private def unsafeRow(value: Int) = { + UnsafeProjection.create(Array(IntegerType : DataType))( + new GenericInternalRow(Array(value: Any))) + } + + var ctx: TaskContextImpl = _ + + override def beforeEach(): Unit = { + super.beforeEach() + ctx = TaskContext.empty() + TaskContext.setTaskContext(ctx) + } + + override def afterEach(): Unit = { + ctx.markTaskCompleted(None) + ctx = null + super.afterEach() + } + + test("receiver stopped with row last") { + val rdd = new ContinuousShuffleReadRDD(sparkContext, numPartitions = 1) + val endpoint = rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].endpoint + endpoint.askSync[Unit](ReceiverEpochMarker()) + endpoint.askSync[Unit](ReceiverRow(unsafeRow(111))) + + ctx.markTaskCompleted(None) + val receiver = rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].receiver + eventually(timeout(streamingTimeout)) { + assert(receiver.stopped.get()) + } + } + + test("receiver stopped with marker last") { + val rdd = new ContinuousShuffleReadRDD(sparkContext, numPartitions = 1) + val endpoint = rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].endpoint + endpoint.askSync[Unit](ReceiverRow(unsafeRow(111))) + endpoint.askSync[Unit](ReceiverEpochMarker()) + + ctx.markTaskCompleted(None) + val receiver = rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].receiver + eventually(timeout(streamingTimeout)) { + assert(receiver.stopped.get()) + } + } + + test("one epoch") { + val rdd = new ContinuousShuffleReadRDD(sparkContext, numPartitions = 1) + val endpoint = rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].endpoint + endpoint.askSync[Unit](ReceiverRow(unsafeRow(111))) + endpoint.askSync[Unit](ReceiverRow(unsafeRow(222))) + endpoint.askSync[Unit](ReceiverRow(unsafeRow(333))) + endpoint.askSync[Unit](ReceiverEpochMarker()) + + val iter = rdd.compute(rdd.partitions(0), ctx) + assert(iter.next().getInt(0) == 111) + assert(iter.next().getInt(0) == 222) + assert(iter.next().getInt(0) == 333) + assert(!iter.hasNext) + } + + test("multiple epochs") { + val rdd = new ContinuousShuffleReadRDD(sparkContext, numPartitions = 1) + val endpoint = rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].endpoint + endpoint.askSync[Unit](ReceiverRow(unsafeRow(111))) + endpoint.askSync[Unit](ReceiverEpochMarker()) + endpoint.askSync[Unit](ReceiverRow(unsafeRow(222))) + endpoint.askSync[Unit](ReceiverRow(unsafeRow(333))) + endpoint.askSync[Unit](ReceiverEpochMarker()) + + val firstEpoch = rdd.compute(rdd.partitions(0), ctx) + assert(firstEpoch.next().getInt(0) == 111) + assert(!firstEpoch.hasNext) + + val secondEpoch = rdd.compute(rdd.partitions(0), ctx) + assert(secondEpoch.next().getInt(0) == 222) + assert(secondEpoch.next().getInt(0) == 333) + assert(!secondEpoch.hasNext) + } + + test("empty epochs") { + val rdd = new ContinuousShuffleReadRDD(sparkContext, numPartitions = 1) + val endpoint = rdd.partitions(0).asInstanceOf[ContinuousShuffleReadPartition].endpoint + endpoint.askSync[Unit](ReceiverEpochMarker()) + endpoint.askSync[Unit](ReceiverEpochMarker()) + endpoint.askSync[Unit](ReceiverRow(unsafeRow(111))) + endpoint.askSync[Unit](ReceiverEpochMarker()) + endpoint.askSync[Unit](ReceiverEpochMarker()) + + assert(rdd.compute(rdd.partitions(0), ctx).isEmpty) + assert(rdd.compute(rdd.partitions(0), ctx).isEmpty) + val thirdEpoch = rdd.compute(rdd.partitions(0), ctx) + assert(thirdEpoch.next().getInt(0) == 111) + assert(rdd.compute(rdd.partitions(0), ctx).isEmpty) + assert(rdd.compute(rdd.partitions(0), ctx).isEmpty) + } --- End diff -- Added the simple one. I agree we don't need to reiterate all of them; RDD partitions being independent is pretty well enforced by the framework.
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