Github user HeartSaVioR commented on a diff in the pull request:
https://github.com/apache/spark/pull/21337#discussion_r188638980
--- 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 --
May be better to add test(s) for multiple partitions. I guess we don't need
to reiterate all of tests, but just simple one with multiple partitions to
ensure all RPC endpoints are working properly.
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