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KAFKA-4402: make the KafkaProducer true round robin per topic #2128

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KAFKA-4402: make the KafkaProducer true round robin per topic #2128

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d74b0bd
KAFKA-4402: make the KafkaProducer true round robin per topic
yaojuncn Nov 13, 2016
fdd946a
KAFKA-4402: fix some style issues
yaojuncn Nov 13, 2016
f978b50
[KAFKA-4402] add performance test for round-robin default partitioner,
yaojuncn Nov 14, 2016
f9ca411
Merge branch 'trunk' into KAFKA-4402-client-producer-round-robin-fix
yaojuncn Nov 19, 2016
82421e4
KAFKA-4402: fix some style issues in DefaultPartitionerTest.java
yaojuncn Jan 1, 2017
59a5298
KAFKA-4402 fix DefaultPartitionerTest.testPartitionPerf time calculat…
yaojuncn Jan 2, 2017
6b99f6e
KAFKA-4402 fix test code checkstyle error
yaojuncn Jan 2, 2017
c5d0bb0
KAFKA-4402, fix a bug in DefaultPartitionerTest.testPartitionPerf
yaojuncn Jan 2, 2017
51eed89
KAFKA-4402: fix a race condition in DefaultPartitioner
yaojuncn Jan 2, 2017
b560d1b
KAFKA-4402 rename "getNextValue" to "nextValue", as this is kafka sytle
yaojuncn Jan 2, 2017
eb8d1bd
KAFKA-4402 remove perf test codes from unit test
yaojuncn Jan 8, 2017
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18 changes: 16 additions & 2 deletions clients/src/main/java/org/apache/kafka/clients/producer/internals/DefaultPartitioner.java
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,8 @@
import java.util.List;
import java.util.Map;
import java.util.Random;
import java.util.concurrent.ConcurrentHashMap;
import java.util.concurrent.ConcurrentMap;
import java.util.concurrent.atomic.AtomicInteger;

import org.apache.kafka.clients.producer.Partitioner;
Expand All @@ -35,7 +37,7 @@
*/
public class DefaultPartitioner implements Partitioner {

private final AtomicInteger counter = new AtomicInteger(new Random().nextInt());
private final ConcurrentMap<String, AtomicInteger> topicCounterMap = new ConcurrentHashMap<>();

public void configure(Map<String, ?> configs) {}

Expand All @@ -53,7 +55,7 @@ public int partition(String topic, Object key, byte[] keyBytes, Object value, by
List<PartitionInfo> partitions = cluster.partitionsForTopic(topic);
int numPartitions = partitions.size();
if (keyBytes == null) {
int nextValue = counter.getAndIncrement();
int nextValue = nextValue(topic);
List<PartitionInfo> availablePartitions = cluster.availablePartitionsForTopic(topic);
if (availablePartitions.size() > 0) {
int part = Utils.toPositive(nextValue) % availablePartitions.size();
Expand All @@ -68,6 +70,18 @@ public int partition(String topic, Object key, byte[] keyBytes, Object value, by
}
}

private int nextValue(String topic) {
AtomicInteger counter = topicCounterMap.get(topic);
if (null == counter) {
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This isn't strictly thread safe since you might overwrite values in the map. It won't cause a crash, but not perfectly consistent behavior. Was this intentional since it only matters for concurrent access the first time a topic is accessed? Or should this entire method be synchronized to guarantee the behavior you're expecting (in which case the Map itself doesn't need to be a concurrent implementation)?

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yeah, I was aware of it and chose to do it in this way.
As this method is a hot method which may be called by every producer.send() if no key is provided, put it as 'synchronized' may potentially impact the performance among the threads.

while the null check may be both true for the initial concurrent threads, as you said, it only impact that very first few calls. further calls are not impacted.

counter = new AtomicInteger(new Random().nextInt());
AtomicInteger currentCounter = topicCounterMap.putIfAbsent(topic, counter);
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looks like, there is a race condition putting the counter to the map

if (currentCounter != null) {
counter = currentCounter;
}
}
return counter.getAndIncrement();
}

public void close() {}

}
35 changes: 34 additions & 1 deletion ...nts/src/test/java/org/apache/kafka/clients/producer/internals/DefaultPartitionerTest.java
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Expand Up @@ -16,11 +16,13 @@
import org.apache.kafka.common.Cluster;
import org.apache.kafka.common.Node;
import org.apache.kafka.common.PartitionInfo;
import org.junit.Assert;
import org.junit.Test;

import java.util.Collections;
import java.util.HashMap;
import java.util.List;

import java.util.Map;
import static java.util.Arrays.asList;
import static org.junit.Assert.assertEquals;
import static org.junit.Assert.assertTrue;
Expand Down Expand Up @@ -62,4 +64,35 @@ public void testRoundRobinWithUnavailablePartitions() {
}
assertEquals("The distribution between two available partitions should be even", countForPart0, countForPart2);
}

@Test
public void testRoundRobin() throws InterruptedException {
final String topicA = "topicA";
final String topicB = "topicB";

List<PartitionInfo> allPartitions = asList(new PartitionInfo(topicA, 0, node0, nodes, nodes),
new PartitionInfo(topicA, 1, node1, nodes, nodes),
new PartitionInfo(topicA, 2, node2, nodes, nodes),
new PartitionInfo(topicB, 0, node0, nodes, nodes)
);
Cluster testCluster = new Cluster("clusterId", asList(node0, node1, node2), allPartitions,
Collections.<String>emptySet(), Collections.<String>emptySet());

final Map<Integer, Integer> partitionCount = new HashMap<>();

for (int i = 0; i < 30; ++i) {
int partition = partitioner.partition(topicA, null, null, null, null, testCluster);
Integer count = partitionCount.get(partition);
if (null == count) count = 0;
partitionCount.put(partition, count + 1);

if (i % 5 == 0) {
partitioner.partition(topicB, null, null, null, null, testCluster);
}
}

Assert.assertEquals(10, (int) partitionCount.get(0));
Assert.assertEquals(10, (int) partitionCount.get(1));
Assert.assertEquals(10, (int) partitionCount.get(2));
}
}