kafka ConsumeBenchWorker 源码
kafka ConsumeBenchWorker 代码
文件路径：/trogdor/src/main/java/org/apache/kafka/trogdor/workload/ConsumeBenchWorker.java
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* 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.kafka.trogdor.workload;
import com.fasterxml.jackson.annotation.JsonCreator;
import com.fasterxml.jackson.annotation.JsonProperty;
import com.fasterxml.jackson.databind.JsonNode;
import org.apache.kafka.clients.consumer.ConsumerConfig;
import org.apache.kafka.clients.consumer.ConsumerRecord;
import org.apache.kafka.clients.consumer.ConsumerRecords;
import org.apache.kafka.clients.consumer.KafkaConsumer;
import org.apache.kafka.common.TopicPartition;
import org.apache.kafka.common.config.ConfigException;
import org.apache.kafka.common.internals.KafkaFutureImpl;
import org.apache.kafka.common.serialization.ByteArrayDeserializer;
import org.apache.kafka.common.utils.ThreadUtils;
import org.apache.kafka.common.utils.Time;
import org.apache.kafka.common.utils.Utils;
import org.apache.kafka.trogdor.common.JsonUtil;
import org.apache.kafka.trogdor.common.Platform;
import org.apache.kafka.trogdor.common.WorkerUtils;
import org.apache.kafka.trogdor.task.WorkerStatusTracker;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import org.apache.kafka.trogdor.task.TaskWorker;
import java.time.Duration;
import java.util.ArrayList;
import java.util.Collection;
import java.util.List;
import java.util.Map;
import java.util.Set;
import java.util.UUID;
import java.util.Optional;
import java.util.Properties;
import java.util.HashMap;
import java.util.concurrent.Callable;
import java.util.concurrent.Executors;
import java.util.concurrent.Future;
import java.util.concurrent.ScheduledExecutorService;
import java.util.concurrent.TimeUnit;
import java.util.concurrent.atomic.AtomicBoolean;
import java.util.concurrent.locks.ReentrantLock;
import java.util.stream.Collectors;
public class ConsumeBenchWorker implements TaskWorker {
private static final Logger log = LoggerFactory.getLogger(ConsumeBenchWorker.class);
private static final int THROTTLE_PERIOD_MS = 100;
private final String id;
private final ConsumeBenchSpec spec;
private final AtomicBoolean running = new AtomicBoolean(false);
private ScheduledExecutorService executor;
private WorkerStatusTracker workerStatus;
private StatusUpdater statusUpdater;
private Future<?> statusUpdaterFuture;
private KafkaFutureImpl<String> doneFuture;
private ThreadSafeConsumer consumer;
public ConsumeBenchWorker(String id, ConsumeBenchSpec spec) {
this.id = id;
this.spec = spec;
}
@Override
public void start(Platform platform, WorkerStatusTracker status,
KafkaFutureImpl<String> doneFuture) throws Exception {
if (!running.compareAndSet(false, true)) {
throw new IllegalStateException("ConsumeBenchWorker is already running.");
}
log.info("{}: Activating ConsumeBenchWorker with {}", id, spec);
this.statusUpdater = new StatusUpdater();
this.executor = Executors.newScheduledThreadPool(
spec.threadsPerWorker() + 2, // 1 thread for all the ConsumeStatusUpdater and 1 for the StatusUpdater
ThreadUtils.createThreadFactory("ConsumeBenchWorkerThread%d", false));
this.statusUpdaterFuture = executor.scheduleAtFixedRate(this.statusUpdater, 1, 1, TimeUnit.MINUTES);
this.workerStatus = status;
this.doneFuture = doneFuture;
executor.submit(new Prepare());
}
public class Prepare implements Runnable {
@Override
public void run() {
try {
List<Future<Void>> consumeTasks = new ArrayList<>();
for (ConsumeMessages task : consumeTasks()) {
consumeTasks.add(executor.submit(task));
}
executor.submit(new CloseStatusUpdater(consumeTasks));
} catch (Throwable e) {
WorkerUtils.abort(log, "Prepare", e, doneFuture);
}
}
private List<ConsumeMessages> consumeTasks() {
List<ConsumeMessages> tasks = new ArrayList<>();
String consumerGroup = consumerGroup();
int consumerCount = spec.threadsPerWorker();
Map<String, List<TopicPartition>> partitionsByTopic = spec.materializeTopics();
boolean toUseGroupPartitionAssignment = partitionsByTopic.values().stream().allMatch(List::isEmpty);
if (!toUseGroupPartitionAssignment && !toUseRandomConsumeGroup() && consumerCount > 1)
throw new ConfigException("You may not specify an explicit partition assignment when using multiple consumers in the same group."
+ "Please leave the consumer group unset, specify topics instead of partitions or use a single consumer.");
consumer = consumer(consumerGroup, clientId(0));
if (toUseGroupPartitionAssignment) {
Set<String> topics = partitionsByTopic.keySet();
tasks.add(new ConsumeMessages(consumer, spec.recordProcessor(), topics));
for (int i = 0; i < consumerCount - 1; i++) {
tasks.add(new ConsumeMessages(consumer(consumerGroup(), clientId(i + 1)), spec.recordProcessor(), topics));
}
} else {
List<TopicPartition> partitions = populatePartitionsByTopic(consumer.consumer(), partitionsByTopic)
.values().stream().flatMap(List::stream).collect(Collectors.toList());
tasks.add(new ConsumeMessages(consumer, spec.recordProcessor(), partitions));
for (int i = 0; i < consumerCount - 1; i++) {
tasks.add(new ConsumeMessages(consumer(consumerGroup(), clientId(i + 1)), spec.recordProcessor(), partitions));
}
}
return tasks;
}
private String clientId(int idx) {
return String.format("consumer.%s-%d", id, idx);
}
/**
* Creates a new KafkaConsumer instance
*/
private ThreadSafeConsumer consumer(String consumerGroup, String clientId) {
Properties props = new Properties();
props.put(ConsumerConfig.BOOTSTRAP_SERVERS_CONFIG, spec.bootstrapServers());
props.put(ConsumerConfig.CLIENT_ID_CONFIG, clientId);
props.put(ConsumerConfig.GROUP_ID_CONFIG, consumerGroup);
props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
props.put(ConsumerConfig.MAX_POLL_INTERVAL_MS_CONFIG, 100000);
// these defaults maybe over-written by the user-specified commonClientConf or consumerConf
WorkerUtils.addConfigsToProperties(props, spec.commonClientConf(), spec.consumerConf());
return new ThreadSafeConsumer(new KafkaConsumer<>(props, new ByteArrayDeserializer(), new ByteArrayDeserializer()), clientId);
}
private String consumerGroup() {
return toUseRandomConsumeGroup()
? "consume-bench-" + UUID.randomUUID().toString()
: spec.consumerGroup();
}
private boolean toUseRandomConsumeGroup() {
return spec.consumerGroup().isEmpty();
}
private Map<String, List<TopicPartition>> populatePartitionsByTopic(KafkaConsumer<byte[], byte[]> consumer,
Map<String, List<TopicPartition>> materializedTopics) {
// fetch partitions for topics who do not have any listed
for (Map.Entry<String, List<TopicPartition>> entry : materializedTopics.entrySet()) {
String topicName = entry.getKey();
List<TopicPartition> partitions = entry.getValue();
if (partitions.isEmpty()) {
List<TopicPartition> fetchedPartitions = consumer.partitionsFor(topicName).stream()
.map(partitionInfo -> new TopicPartition(partitionInfo.topic(), partitionInfo.partition()))
.collect(Collectors.toList());
partitions.addAll(fetchedPartitions);
}
materializedTopics.put(topicName, partitions);
}
return materializedTopics;
}
}
public class ConsumeMessages implements Callable<Void> {
private final Histogram latencyHistogram;
private final Histogram messageSizeHistogram;
private final Future<?> statusUpdaterFuture;
private final Throttle throttle;
private final String clientId;
private final ThreadSafeConsumer consumer;
private final Optional<RecordProcessor> recordProcessor;
private ConsumeMessages(ThreadSafeConsumer consumer,
Optional<RecordProcessor> recordProcessor) {
this.latencyHistogram = new Histogram(10000);
this.messageSizeHistogram = new Histogram(2 * 1024 * 1024);
this.clientId = consumer.clientId();
this.statusUpdaterFuture = executor.scheduleAtFixedRate(
new ConsumeStatusUpdater(latencyHistogram, messageSizeHistogram, consumer, recordProcessor), 1, 1, TimeUnit.MINUTES);
int perPeriod;
if (spec.targetMessagesPerSec() <= 0)
perPeriod = Integer.MAX_VALUE;
else
perPeriod = WorkerUtils.perSecToPerPeriod(spec.targetMessagesPerSec(), THROTTLE_PERIOD_MS);
this.throttle = new Throttle(perPeriod, THROTTLE_PERIOD_MS);
this.consumer = consumer;
this.recordProcessor = recordProcessor;
}
ConsumeMessages(ThreadSafeConsumer consumer,
Optional<RecordProcessor> recordProcessor,
Set<String> topics) {
this(consumer, recordProcessor);
log.info("Will consume from topics {} via dynamic group assignment.", topics);
this.consumer.subscribe(topics);
}
ConsumeMessages(ThreadSafeConsumer consumer,
Optional<RecordProcessor> recordProcessor,
List<TopicPartition> partitions) {
this(consumer, recordProcessor);
log.info("Will consume from topic partitions {} via manual assignment.", partitions);
this.consumer.assign(partitions);
}
@Override
public Void call() throws Exception {
long messagesConsumed = 0;
long bytesConsumed = 0;
long startTimeMs = Time.SYSTEM.milliseconds();
long startBatchMs = startTimeMs;
long maxMessages = spec.maxMessages();
try {
while (messagesConsumed < maxMessages) {
ConsumerRecords<byte[], byte[]> records = consumer.poll();
if (records.isEmpty()) {
continue;
}
long endBatchMs = Time.SYSTEM.milliseconds();
long elapsedBatchMs = endBatchMs - startBatchMs;
// Do the record batch processing immediately to avoid latency skew.
recordProcessor.ifPresent(processor -> processor.processRecords(records));
for (ConsumerRecord<byte[], byte[]> record : records) {
messagesConsumed++;
long messageBytes = 0;
if (record.key() != null) {
messageBytes += record.serializedKeySize();
}
if (record.value() != null) {
messageBytes += record.serializedValueSize();
}
latencyHistogram.add(elapsedBatchMs);
messageSizeHistogram.add(messageBytes);
bytesConsumed += messageBytes;
if (messagesConsumed >= maxMessages)
break;
throttle.increment();
}
startBatchMs = Time.SYSTEM.milliseconds();
}
} catch (Exception e) {
WorkerUtils.abort(log, "ConsumeRecords", e, doneFuture);
} finally {
statusUpdaterFuture.cancel(false);
StatusData statusData =
new ConsumeStatusUpdater(latencyHistogram, messageSizeHistogram, consumer, spec.recordProcessor()).update();
long curTimeMs = Time.SYSTEM.milliseconds();
log.info("{} Consumed total number of messages={}, bytes={} in {} ms. status: {}",
clientId, messagesConsumed, bytesConsumed, curTimeMs - startTimeMs, statusData);
}
consumer.close();
return null;
}
}
public class CloseStatusUpdater implements Runnable {
private final List<Future<Void>> consumeTasks;
CloseStatusUpdater(List<Future<Void>> consumeTasks) {
this.consumeTasks = consumeTasks;
}
@Override
public void run() {
while (!consumeTasks.stream().allMatch(Future::isDone)) {
try {
Thread.sleep(60000);
} catch (InterruptedException e) {
log.debug("{} was interrupted. Closing...", this.getClass().getName());
break; // close the thread
}
}
statusUpdaterFuture.cancel(false);
statusUpdater.update();
doneFuture.complete("");
}
}
class StatusUpdater implements Runnable {
final Map<String, JsonNode> statuses;
StatusUpdater() {
statuses = new HashMap<>();
}
@Override
public void run() {
try {
update();
} catch (Exception e) {
WorkerUtils.abort(log, "ConsumeStatusUpdater", e, doneFuture);
}
}
synchronized void update() {
workerStatus.update(JsonUtil.JSON_SERDE.valueToTree(statuses));
}
synchronized void updateConsumeStatus(String clientId, StatusData status) {
statuses.put(clientId, JsonUtil.JSON_SERDE.valueToTree(status));
}
}
/**
* Runnable class that updates the status of a single consumer
*/
public class ConsumeStatusUpdater implements Runnable {
private final Histogram latencyHistogram;
private final Histogram messageSizeHistogram;
private final ThreadSafeConsumer consumer;
private final Optional<RecordProcessor> recordProcessor;
ConsumeStatusUpdater(Histogram latencyHistogram,
Histogram messageSizeHistogram,
ThreadSafeConsumer consumer,
Optional<RecordProcessor> recordProcessor) {
this.latencyHistogram = latencyHistogram;
this.messageSizeHistogram = messageSizeHistogram;
this.consumer = consumer;
this.recordProcessor = recordProcessor;
}
@Override
public void run() {
try {
update();
} catch (Exception e) {
WorkerUtils.abort(log, "ConsumeStatusUpdater", e, doneFuture);
}
}
StatusData update() {
Histogram.Summary latSummary = latencyHistogram.summarize(StatusData.PERCENTILES);
Histogram.Summary msgSummary = messageSizeHistogram.summarize(StatusData.PERCENTILES);
// Parse out the RecordProcessor's status, id specified.
Optional<JsonNode> recordProcessorStatus = Optional.empty();
if (recordProcessor.isPresent()) {
recordProcessorStatus = Optional.of(recordProcessor.get().processorStatus());
}
StatusData statusData = new StatusData(
consumer.assignedPartitions(),
latSummary.numSamples(),
(long) (msgSummary.numSamples() * msgSummary.average()),
(long) msgSummary.average(),
latSummary.average(),
latSummary.percentiles().get(0).value(),
latSummary.percentiles().get(1).value(),
latSummary.percentiles().get(2).value(),
recordProcessorStatus);
statusUpdater.updateConsumeStatus(consumer.clientId(), statusData);
log.info("Status={}", JsonUtil.toJsonString(statusData));
return statusData;
}
}
public static class StatusData {
private final long totalMessagesReceived;
private final List<String> assignedPartitions;
private final long totalBytesReceived;
private final long averageMessageSizeBytes;
private final float averageLatencyMs;
private final int p50LatencyMs;
private final int p95LatencyMs;
private final int p99LatencyMs;
private final Optional<JsonNode> recordProcessorStatus;
/**
* The percentiles to use when calculating the histogram data.
* These should match up with the p50LatencyMs, p95LatencyMs, etc. fields.
*/
final static float[] PERCENTILES = {0.5f, 0.95f, 0.99f};
@JsonCreator
StatusData(@JsonProperty("assignedPartitions") List<String> assignedPartitions,
@JsonProperty("totalMessagesReceived") long totalMessagesReceived,
@JsonProperty("totalBytesReceived") long totalBytesReceived,
@JsonProperty("averageMessageSizeBytes") long averageMessageSizeBytes,
@JsonProperty("averageLatencyMs") float averageLatencyMs,
@JsonProperty("p50LatencyMs") int p50latencyMs,
@JsonProperty("p95LatencyMs") int p95latencyMs,
@JsonProperty("p99LatencyMs") int p99latencyMs,
@JsonProperty("recordProcessorStatus") Optional<JsonNode> recordProcessorStatus) {
this.assignedPartitions = assignedPartitions;
this.totalMessagesReceived = totalMessagesReceived;
this.totalBytesReceived = totalBytesReceived;
this.averageMessageSizeBytes = averageMessageSizeBytes;
this.averageLatencyMs = averageLatencyMs;
this.p50LatencyMs = p50latencyMs;
this.p95LatencyMs = p95latencyMs;
this.p99LatencyMs = p99latencyMs;
this.recordProcessorStatus = recordProcessorStatus;
}
@JsonProperty
public List<String> assignedPartitions() {
return assignedPartitions;
}
@JsonProperty
public long totalMessagesReceived() {
return totalMessagesReceived;
}
@JsonProperty
public long totalBytesReceived() {
return totalBytesReceived;
}
@JsonProperty
public long averageMessageSizeBytes() {
return averageMessageSizeBytes;
}
@JsonProperty
public float averageLatencyMs() {
return averageLatencyMs;
}
@JsonProperty
public int p50LatencyMs() {
return p50LatencyMs;
}
@JsonProperty
public int p95LatencyMs() {
return p95LatencyMs;
}
@JsonProperty
public int p99LatencyMs() {
return p99LatencyMs;
}
@JsonProperty
public JsonNode recordProcessorStatus() {
return recordProcessorStatus.orElse(null);
}
}
@Override
public void stop(Platform platform) throws Exception {
if (!running.compareAndSet(true, false)) {
throw new IllegalStateException("ConsumeBenchWorker is not running.");
}
log.info("{}: Deactivating ConsumeBenchWorker.", id);
doneFuture.complete("");
executor.shutdownNow();
executor.awaitTermination(1, TimeUnit.DAYS);
consumer.close();
this.consumer = null;
this.executor = null;
this.statusUpdater = null;
this.statusUpdaterFuture = null;
this.workerStatus = null;
this.doneFuture = null;
}
/**
* A thread-safe KafkaConsumer wrapper
*/
private static class ThreadSafeConsumer {
private final KafkaConsumer<byte[], byte[]> consumer;
private final String clientId;
private final ReentrantLock consumerLock;
private boolean closed = false;
ThreadSafeConsumer(KafkaConsumer<byte[], byte[]> consumer, String clientId) {
this.consumer = consumer;
this.clientId = clientId;
this.consumerLock = new ReentrantLock();
}
ConsumerRecords<byte[], byte[]> poll() {
this.consumerLock.lock();
try {
return consumer.poll(Duration.ofMillis(50));
} finally {
this.consumerLock.unlock();
}
}
void close() {
if (closed)
return;
this.consumerLock.lock();
try {
consumer.unsubscribe();
Utils.closeQuietly(consumer, "consumer");
closed = true;
} finally {
this.consumerLock.unlock();
}
}
void subscribe(Set<String> topics) {
this.consumerLock.lock();
try {
consumer.subscribe(topics);
} finally {
this.consumerLock.unlock();
}
}
void assign(Collection<TopicPartition> partitions) {
this.consumerLock.lock();
try {
consumer.assign(partitions);
} finally {
this.consumerLock.unlock();
}
}
List<String> assignedPartitions() {
this.consumerLock.lock();
try {
return consumer.assignment().stream()
.map(TopicPartition::toString).collect(Collectors.toList());
} finally {
this.consumerLock.unlock();
}
}
String clientId() {
return clientId;
}
KafkaConsumer<byte[], byte[]> consumer() {
return consumer;
}
}
}
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