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Kafka client whose producer requires explicit encoders.
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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.clients.tools;
import java.util.Arrays;
import java.util.Properties;
import org.apache.kafka.clients.producer.*;
public class ProducerPerformance {
private static final long NS_PER_MS = 1000000L;
private static final long NS_PER_SEC = 1000 * NS_PER_MS;
private static final long MIN_SLEEP_NS = 2 * NS_PER_MS;
public static void main(String[] args) throws Exception {
if (args.length < 4) {
System.err.println("USAGE: java " + ProducerPerformance.class.getName() +
" topic_name num_records record_size target_records_sec [prop_name=prop_value]*");
System.exit(1);
}
/* parse args */
String topicName = args[0];
long numRecords = Long.parseLong(args[1]);
int recordSize = Integer.parseInt(args[2]);
int throughput = Integer.parseInt(args[3]);
Properties props = new Properties();
for (int i = 4; i < args.length; i++) {
String[] pieces = args[i].split("=");
if (pieces.length != 2)
throw new IllegalArgumentException("Invalid property: " + args[i]);
props.put(pieces[0], pieces[1]);
}
props.put(ProducerConfig.KEY_SERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.ByteArraySerializer");
props.put(ProducerConfig.VALUE_SERIALIZER_CLASS_CONFIG, "org.apache.kafka.common.serialization.ByteArraySerializer");
KafkaProducer producer = new KafkaProducer(props);
/* setup perf test */
byte[] payload = new byte[recordSize];
Arrays.fill(payload, (byte) 1);
ProducerRecord record = new ProducerRecord(topicName, payload);
long sleepTime = NS_PER_SEC / throughput;
long sleepDeficitNs = 0;
Stats stats = new Stats(numRecords, 5000);
for (int i = 0; i < numRecords; i++) {
long sendStart = System.currentTimeMillis();
Callback cb = stats.nextCompletion(sendStart, payload.length, stats);
producer.send(record, cb);
/*
* Maybe sleep a little to control throughput. Sleep time can be a bit inaccurate for times < 1 ms so
* instead of sleeping each time instead wait until a minimum sleep time accumulates (the "sleep deficit")
* and then make up the whole deficit in one longer sleep.
*/
if (throughput > 0) {
sleepDeficitNs += sleepTime;
if (sleepDeficitNs >= MIN_SLEEP_NS) {
long sleepMs = sleepDeficitNs / 1000000;
long sleepNs = sleepDeficitNs - sleepMs * 1000000;
Thread.sleep(sleepMs, (int) sleepNs);
sleepDeficitNs = 0;
}
}
}
/* print final results */
producer.close();
stats.printTotal();
}
private static class Stats {
private long start;
private long windowStart;
private int[] latencies;
private int sampling;
private int iteration;
private int index;
private long count;
private long bytes;
private int maxLatency;
private long totalLatency;
private long windowCount;
private int windowMaxLatency;
private long windowTotalLatency;
private long windowBytes;
private long reportingInterval;
public Stats(long numRecords, int reportingInterval) {
this.start = System.currentTimeMillis();
this.windowStart = System.currentTimeMillis();
this.index = 0;
this.iteration = 0;
this.sampling = (int) (numRecords / Math.min(numRecords, 500000));
this.latencies = new int[(int) (numRecords / this.sampling) + 1];
this.index = 0;
this.maxLatency = 0;
this.totalLatency = 0;
this.windowCount = 0;
this.windowMaxLatency = 0;
this.windowTotalLatency = 0;
this.windowBytes = 0;
this.totalLatency = 0;
this.reportingInterval = reportingInterval;
}
public void record(int iter, int latency, int bytes, long time) {
this.count++;
this.bytes += bytes;
this.totalLatency += latency;
this.maxLatency = Math.max(this.maxLatency, latency);
this.windowCount++;
this.windowBytes += bytes;
this.windowTotalLatency += latency;
this.windowMaxLatency = Math.max(windowMaxLatency, latency);
if (iter % this.sampling == 0) {
this.latencies[index] = latency;
this.index++;
}
/* maybe report the recent perf */
if (time - windowStart >= reportingInterval) {
printWindow();
newWindow();
}
}
public Callback nextCompletion(long start, int bytes, Stats stats) {
Callback cb = new PerfCallback(this.iteration, start, bytes, stats);
this.iteration++;
return cb;
}
public void printWindow() {
long ellapsed = System.currentTimeMillis() - windowStart;
double recsPerSec = 1000.0 * windowCount / (double) ellapsed;
double mbPerSec = 1000.0 * this.windowBytes / (double) ellapsed / (1024.0 * 1024.0);
System.out.printf("%d records sent, %.1f records/sec (%.2f MB/sec), %.1f ms avg latency, %.1f max latency.\n",
windowCount,
recsPerSec,
mbPerSec,
windowTotalLatency / (double) windowCount,
(double) windowMaxLatency);
}
public void newWindow() {
this.windowStart = System.currentTimeMillis();
this.windowCount = 0;
this.windowMaxLatency = 0;
this.windowTotalLatency = 0;
this.windowBytes = 0;
}
public void printTotal() {
long ellapsed = System.currentTimeMillis() - start;
double recsPerSec = 1000.0 * count / (double) ellapsed;
double mbPerSec = 1000.0 * this.bytes / (double) ellapsed / (1024.0 * 1024.0);
int[] percs = percentiles(this.latencies, index, 0.5, 0.95, 0.99, 0.999);
System.out.printf("%d records sent, %f records/sec (%.2f MB/sec), %.2f ms avg latency, %.2f ms max latency, %d ms 50th, %d ms 95th, %d ms 99th, %d ms 99.9th.\n",
count,
recsPerSec,
mbPerSec,
totalLatency / (double) count,
(double) maxLatency,
percs[0],
percs[1],
percs[2],
percs[3]);
}
private static int[] percentiles(int[] latencies, int count, double... percentiles) {
int size = Math.min(count, latencies.length);
Arrays.sort(latencies, 0, size);
int[] values = new int[percentiles.length];
for (int i = 0; i < percentiles.length; i++) {
int index = (int) (percentiles[i] * size);
values[i] = latencies[index];
}
return values;
}
}
private static final class PerfCallback implements Callback {
private final long start;
private final int iteration;
private final int bytes;
private final Stats stats;
public PerfCallback(int iter, long start, int bytes, Stats stats) {
this.start = start;
this.stats = stats;
this.iteration = iter;
this.bytes = bytes;
}
public void onCompletion(RecordMetadata metadata, Exception exception) {
long now = System.currentTimeMillis();
int latency = (int) (now - start);
this.stats.record(iteration, latency, bytes, now);
if (exception != null)
exception.printStackTrace();
}
}
}