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KAFKA-9335: Fix StreamPartitionAssignor regression in repartition top…
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…ics counts (apache#7904)

This PR fixes the regression introduced in 2.4 from 2 refactoring PRs:
apache#7249
apache#7419

The bug was introduced by having a logical path leading numPartitionsCandidate to be 0, which is assigned to numPartitions and later being checked by setNumPartitions. In the subsequent check we will throw illegal argument if the numPartitions is 0.

This bug is both impacting new 2.4 application and upgrades to 2.4 in certain types of topology. The example in original JIRA was imported as a new integration test to guard against such regression. We also verify that without the bug fix application will still fail by running this integration test.

Reviewers: Guozhang Wang <wangguoz@gmail.com>
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Boyang Chen authored and qq619618919 committed May 12, 2020
1 parent a654e8b commit 841f5f3
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Expand Up @@ -439,7 +439,7 @@ public GroupAssignment assign(final Cluster metadata, final GroupSubscription gr
// if this topic is one of the sink topics of this topology,
// use the maximum of all its source topic partitions as the number of partitions
for (final String sourceTopicName : otherTopicsInfo.sourceTopics) {
int numPartitionsCandidate = 0;
Integer numPartitionsCandidate = null;
// It is possible the sourceTopic is another internal topic, i.e,
// map().join().join(map())
if (repartitionTopicMetadata.containsKey(sourceTopicName)) {
Expand All @@ -459,13 +459,16 @@ public GroupAssignment assign(final Cluster metadata, final GroupSubscription gr
numPartitionsCandidate = count;
}

if (numPartitions == null || numPartitionsCandidate > numPartitions) {
numPartitions = numPartitionsCandidate;
if (numPartitionsCandidate != null) {
if (numPartitions == null || numPartitionsCandidate > numPartitions) {
numPartitions = numPartitionsCandidate;
}
}
}
}
}
// if we still have not find the right number of partitions,

// if we still have not found the right number of partitions,
// another iteration is needed
if (numPartitions == null) {
numPartitionsNeeded = true;
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@@ -0,0 +1,151 @@
/*
* 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
* limitations under the License.
*/
package org.apache.kafka.streams.integration;

import kafka.utils.MockTime;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.common.serialization.ByteArraySerializer;
import org.apache.kafka.common.serialization.Serdes;
import org.apache.kafka.streams.KafkaStreams;
import org.apache.kafka.streams.KeyValue;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.StreamsConfig;
import org.apache.kafka.streams.Topology;
import org.apache.kafka.streams.integration.utils.EmbeddedKafkaCluster;
import org.apache.kafka.streams.integration.utils.IntegrationTestUtils;
import org.apache.kafka.streams.kstream.KStream;
import org.apache.kafka.streams.kstream.KTable;
import org.apache.kafka.streams.kstream.Materialized;
import org.apache.kafka.test.IntegrationTest;
import org.apache.kafka.test.StreamsTestUtils;
import org.apache.kafka.test.TestUtils;
import org.junit.Before;
import org.junit.ClassRule;
import org.junit.Test;
import org.junit.experimental.categories.Category;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;

import java.util.Collections;
import java.util.List;
import java.util.Properties;
import java.util.concurrent.ExecutionException;

/**
* Test out a topology with 3 level of sub-topology as:
* 0
* / \
* 1 3
* \ /
* 2
* where each pair of the sub topology is connected by repartition topic.
* The purpose of this test is to verify the robustness of the stream partition assignor algorithm,
* especially whether it could build the repartition topic counts (step zero) with a complex topology.
* The traversal path 0 -> 1 -> 2 -> 3 hits the case where sub-topology 2 will be initialized while its
* parent 3 hasn't been initialized yet.
*/
@Category({IntegrationTest.class})
public class BranchedMultiLevelRepartitionConnectedTopologyTest {

private static final Logger log = LoggerFactory.getLogger(BranchedMultiLevelRepartitionConnectedTopologyTest.class);

private static String inputStream;

private KafkaStreams kafkaStreams;

private Properties streamsConfiguration;

@ClassRule
public static final EmbeddedKafkaCluster CLUSTER = new EmbeddedKafkaCluster(1);
private final MockTime mockTime = CLUSTER.time;

@Before
public void setUp() throws Exception {
final Properties props = new Properties();
props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
props.put(StreamsConfig.TOPOLOGY_OPTIMIZATION, StreamsConfig.NO_OPTIMIZATION);
streamsConfiguration = StreamsTestUtils.getStreamsConfig(
"branched-repartition-topic-test",
CLUSTER.bootstrapServers(),
Serdes.ByteArray().getClass().getName(),
Serdes.ByteArray().getClass().getName(),
props);

inputStream = "input-stream";
CLUSTER.createTopic(inputStream, 3, 1);

IntegrationTestUtils.purgeLocalStreamsState(streamsConfiguration);
}

@Test
@SuppressWarnings("unchecked")
public void testTopologyBuild() throws InterruptedException, ExecutionException {

final StreamsBuilder builder = new StreamsBuilder();

final KStream<byte[], byte[]> input = builder.stream(inputStream);

final KStream<byte[], byte[]>[] branches = input
.flatMapValues(value -> Collections.singletonList(new byte[0]))
.branch((k, v) -> true, (k, v) -> false);

final KTable<byte[], byte[]> b1 = branches[0]
.map(KeyValue::new)
.groupByKey()
.reduce((k, v) -> v, Materialized.as("odd_store"))
.toStream()
.peek((k, v) -> { })
.map(KeyValue::new)
.groupByKey()
.reduce((k, v) -> v, Materialized.as("odd_store_2"));

final KTable<byte[], byte[]> b2 = branches[1]
.map(KeyValue::new)
.groupByKey()
.reduce((k, v) -> v, Materialized.as("even_store"))
.toStream()
.peek((k, v) -> { })
.map(KeyValue::new)
.groupByKey()
.reduce((k, v) -> v, Materialized.as("even_store_2"));

b1.join(b2, (v1, v2) -> v1, Materialized.as("joined_store"))
.toStream();

final Topology topology = builder.build(streamsConfiguration);
log.info("Built topology: {}", topology.describe());

final Properties producerConfig = TestUtils.producerConfig(
CLUSTER.bootstrapServers(), ByteArraySerializer.class, ByteArraySerializer.class);

final List<KeyValue<byte[], byte[]>> initialKeyValues = Collections.singletonList(
KeyValue.pair(new byte[1], new byte[1]));

IntegrationTestUtils.produceKeyValuesSynchronously(
inputStream, initialKeyValues, producerConfig, mockTime);

kafkaStreams = new KafkaStreams(topology, streamsConfiguration);

kafkaStreams.cleanUp();
kafkaStreams.start();

TestUtils.waitForCondition(() -> kafkaStreams.state() == KafkaStreams.State.RUNNING,
"Failed to observe stream transits to RUNNING");

kafkaStreams.close();
}
}

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