kafka ConfigurableProducerWorker 源码
kafka ConfigurableProducerWorker 代码
文件路径:/trogdor/src/main/java/org/apache/kafka/trogdor/workload/ConfigurableProducerWorker.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.node.TextNode;
import org.apache.kafka.clients.admin.NewTopic;
import org.apache.kafka.clients.producer.Callback;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.ProducerConfig;
import org.apache.kafka.clients.producer.ProducerRecord;
import org.apache.kafka.clients.producer.RecordMetadata;
import org.apache.kafka.common.TopicPartition;
import org.apache.kafka.common.internals.KafkaFutureImpl;
import org.apache.kafka.common.serialization.ByteArraySerializer;
import org.apache.kafka.common.utils.ThreadUtils;
import org.apache.kafka.common.utils.Time;
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.TaskWorker;
import org.apache.kafka.trogdor.task.WorkerStatusTracker;
import org.slf4j.Logger;
import org.slf4j.LoggerFactory;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;
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;
/**
* This workload allows for customized and even variable configurations in terms of messages per second, message size,
* batch size, key size, and even the ability to target a specific partition out of a topic.
*
* See `ConfigurableProducerSpec` for a more detailed description.
*/
public class ConfigurableProducerWorker implements TaskWorker {
private static final Logger log = LoggerFactory.getLogger(ConfigurableProducerWorker.class);
private final String id;
private final ConfigurableProducerSpec spec;
private final AtomicBoolean running = new AtomicBoolean(false);
private ScheduledExecutorService executor;
private WorkerStatusTracker status;
private KafkaFutureImpl<String> doneFuture;
public ConfigurableProducerWorker(String id, ConfigurableProducerSpec spec) {
this.id = id;
this.spec = spec;
}
@Override
public void start(Platform platform, WorkerStatusTracker status,
KafkaFutureImpl<String> doneFuture) {
if (!running.compareAndSet(false, true)) {
throw new IllegalStateException("ConfigurableProducerWorker is already running.");
}
log.info("{}: Activating ConfigurableProducerWorker with {}", id, spec);
// Create an executor with 2 threads. We need the second thread so
// that the StatusUpdater can run in parallel with SendRecords.
this.executor = Executors.newScheduledThreadPool(2,
ThreadUtils.createThreadFactory("ConfigurableProducerWorkerThread%d", false));
this.status = status;
this.doneFuture = doneFuture;
executor.submit(new Prepare());
}
public class Prepare implements Runnable {
@Override
public void run() {
try {
Map<String, NewTopic> newTopics = new HashMap<>();
if (spec.activeTopic().materialize().size() != 1) {
throw new RuntimeException("Can only run against 1 topic.");
}
List<TopicPartition> active = new ArrayList<>();
for (Map.Entry<String, PartitionsSpec> entry :
spec.activeTopic().materialize().entrySet()) {
String topicName = entry.getKey();
PartitionsSpec partSpec = entry.getValue();
newTopics.put(topicName, partSpec.newTopic(topicName));
for (Integer partitionNumber : partSpec.partitionNumbers()) {
active.add(new TopicPartition(topicName, partitionNumber));
}
}
status.update(new TextNode("Creating " + newTopics.keySet().size() + " topic(s)"));
WorkerUtils.createTopics(log, spec.bootstrapServers(), spec.commonClientConf(),
spec.adminClientConf(), newTopics, false);
status.update(new TextNode("Created " + newTopics.keySet().size() + " topic(s)"));
executor.submit(new SendRecords(active.get(0).topic(), spec.activePartition()));
} catch (Throwable e) {
WorkerUtils.abort(log, "Prepare", e, doneFuture);
}
}
}
private static class SendRecordsCallback implements Callback {
private final SendRecords sendRecords;
private final long startMs;
SendRecordsCallback(SendRecords sendRecords, long startMs) {
this.sendRecords = sendRecords;
this.startMs = startMs;
}
@Override
public void onCompletion(RecordMetadata metadata, Exception exception) {
long now = Time.SYSTEM.milliseconds();
long durationMs = now - startMs;
sendRecords.recordDuration(durationMs);
if (exception != null) {
log.error("SendRecordsCallback: error", exception);
}
}
}
public class SendRecords implements Callable<Void> {
private final String activeTopic;
private final int activePartition;
private final Histogram histogram;
private final Future<?> statusUpdaterFuture;
private final KafkaProducer<byte[], byte[]> producer;
private final PayloadIterator keys;
private final PayloadIterator values;
private Future<RecordMetadata> sendFuture;
SendRecords(String topic, int partition) {
this.activeTopic = topic;
this.activePartition = partition;
this.histogram = new Histogram(10000);
this.statusUpdaterFuture = executor.scheduleWithFixedDelay(
new StatusUpdater(histogram), 30, 30, TimeUnit.SECONDS);
Properties props = new Properties();
props.put(ProducerConfig.BOOTSTRAP_SERVERS_CONFIG, spec.bootstrapServers());
WorkerUtils.addConfigsToProperties(props, spec.commonClientConf(), spec.producerConf());
this.producer = new KafkaProducer<>(props, new ByteArraySerializer(), new ByteArraySerializer());
this.keys = new PayloadIterator(spec.keyGenerator());
this.values = new PayloadIterator(spec.valueGenerator());
}
@Override
public Void call() throws Exception {
long startTimeMs = Time.SYSTEM.milliseconds();
try {
try {
long sentMessages = 0;
while (true) {
sendMessage();
sentMessages++;
}
} catch (Exception e) {
throw e;
} finally {
if (sendFuture != null) {
try {
sendFuture.get();
} catch (Exception e) {
log.error("Exception on final future", e);
}
}
producer.close();
}
} catch (Exception e) {
WorkerUtils.abort(log, "SendRecords", e, doneFuture);
} finally {
statusUpdaterFuture.cancel(false);
StatusData statusData = new StatusUpdater(histogram).update();
long curTimeMs = Time.SYSTEM.milliseconds();
log.info("Sent {} total record(s) in {} ms. status: {}",
histogram.summarize().numSamples(), curTimeMs - startTimeMs, statusData);
}
doneFuture.complete("");
return null;
}
private void sendMessage() throws InterruptedException {
ProducerRecord<byte[], byte[]> record;
if (activePartition != -1) {
record = new ProducerRecord<>(activeTopic, activePartition, keys.next(), values.next());
} else {
record = new ProducerRecord<>(activeTopic, keys.next(), values.next());
}
sendFuture = producer.send(record, new SendRecordsCallback(this, Time.SYSTEM.milliseconds()));
spec.flushGenerator().ifPresent(flushGenerator -> flushGenerator.increment(producer));
spec.throughputGenerator().throttle();
}
void recordDuration(long durationMs) {
histogram.add(durationMs);
}
}
public class StatusUpdater implements Runnable {
private final Histogram histogram;
StatusUpdater(Histogram histogram) {
this.histogram = histogram;
}
@Override
public void run() {
try {
update();
} catch (Exception e) {
WorkerUtils.abort(log, "StatusUpdater", e, doneFuture);
}
}
StatusData update() {
Histogram.Summary summary = histogram.summarize(StatusData.PERCENTILES);
StatusData statusData = new StatusData(summary.numSamples(), summary.average(),
summary.percentiles().get(0).value(),
summary.percentiles().get(1).value(),
summary.percentiles().get(2).value());
status.update(JsonUtil.JSON_SERDE.valueToTree(statusData));
return statusData;
}
}
public static class StatusData {
private final long totalSent;
private final float averageLatencyMs;
private final int p50LatencyMs;
private final int p95LatencyMs;
private final int p99LatencyMs;
/**
* 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("totalSent") long totalSent,
@JsonProperty("averageLatencyMs") float averageLatencyMs,
@JsonProperty("p50LatencyMs") int p50latencyMs,
@JsonProperty("p95LatencyMs") int p95latencyMs,
@JsonProperty("p99LatencyMs") int p99latencyMs) {
this.totalSent = totalSent;
this.averageLatencyMs = averageLatencyMs;
this.p50LatencyMs = p50latencyMs;
this.p95LatencyMs = p95latencyMs;
this.p99LatencyMs = p99latencyMs;
}
@JsonProperty
public long totalSent() {
return totalSent;
}
@JsonProperty
public float averageLatencyMs() {
return averageLatencyMs;
}
@JsonProperty
public int p50LatencyMs() {
return p50LatencyMs;
}
@JsonProperty
public int p95LatencyMs() {
return p95LatencyMs;
}
@JsonProperty
public int p99LatencyMs() {
return p99LatencyMs;
}
}
@Override
public void stop(Platform platform) throws Exception {
if (!running.compareAndSet(true, false)) {
throw new IllegalStateException("ConfigurableProducerWorker is not running.");
}
log.info("{}: Deactivating ConfigurableProducerWorker.", id);
doneFuture.complete("");
executor.shutdownNow();
executor.awaitTermination(1, TimeUnit.DAYS);
this.executor = null;
this.status = null;
this.doneFuture = null;
}
}
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