最近網關和業務的日誌線上都是4萬/秒，然後需要用flink算一下每個業務的異常數，週期性輸出分析結果
既然是4萬/秒，那麼我起碼得壓個10萬/秒才能安心上線，那麼問題來了，怎麼構造10萬/秒的壓力（單條消息1K）
---這裏選擇官方的Kafka-producer-perf-test腳本
顯然，它的內部也是啓動了一個java程序，那麼我把它的java代碼摳出來，該替換的替換成我自己的需求，進行定製所以下面是分析步驟
1）cat kafka-producer-perf-test.sh
#!/bin/bash
# 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.
if [ "x$KAFKA_HEAP_OPTS" = "x" ]; then
export KAFKA_HEAP_OPTS="-Xmx512M"
fi
exec $(dirname $0)/kafka-run-class.sh org.apache.kafka.tools.ProducerPerformance "$@"可以看到，執行的是
kafka-run-class.sh org.apache.kafka.tools.ProducerPerformance "$@"2)kafka-run-class.sh
最關鍵的是最後一段
# Launch mode
if [ "x$DAEMON_MODE" = "xtrue" ]; then
nohup $JAVA $KAFKA_HEAP_OPTS $KAFKA_JVM_PERFORMANCE_OPTS $KAFKA_GC_LOG_OPTS $KAFKA_JMX_OPTS $KAFKA_LOG4J_OPTS -cp $CLASSPATH $KAFKA_OPTS "$@" > "$CONSOLE_OUTPUT_FILE" 2>&1 < /dev/null &
else
exec $JAVA $KAFKA_HEAP_OPTS $KAFKA_JVM_PERFORMANCE_OPTS $KAFKA_GC_LOG_OPTS $KAFKA_JMX_OPTS $KAFKA_LOG4J_OPTS -cp $CLASSPATH $KAFKA_OPTS "$@"
fi這裏採用非daemon模式，那麼命令行其實就是
/home/ymmapp/java/jdk1.8.0_131//bin/java -Xmx512M -server -XX:+UseG1GC -XX:MaxGCPauseMillis=20 -XX:InitiatingHeapOccupancyPercent=35 -XX:+DisableExplicitGC -Djava.awt.headless=true -Xloggc:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../logs/-gc.log -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCDateStamps -XX:+PrintGCTimeStamps -Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.authenticate=false -Dcom.sun.management.jmxremote.ssl=false -Dkafka.logs.dir=/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../logs -Dlog4j.configuration=file:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../config/tools-log4j.properties -cp /data/java/lib::/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/aopalliance-repackaged-2.5.0-b05.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/argparse4j-0.7.0.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/connect-api-0.10.2.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/connect-file-0.10.2.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/connect-json-0.10.2.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/connect-runtime-0.10.2.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/connect-transforms-0.10.2.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/guava-18.0.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/hk2-api-2.5.0-b05.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/hk2-locator-2.5.0-b05.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/hk2-utils-2.5.0-b05.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jackson-annotations-2.8.0.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jackson-annotations-2.8.5.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jackson-core-2.8.5.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jackson-databind-2.8.5.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jackson-jaxrs-base-2.8.5.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jackson-jaxrs-json-provider-2.8.5.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jackson-module-jaxb-annotations-2.8.5.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/javassist-3.20.0-GA.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/javax.annotation-api-1.2.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/javax.inject-1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/javax.inject-2.5.0-b05.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/javax.servlet-api-3.1.0.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/javax.ws.rs-api-2.0.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jersey-client-2.24.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jersey-common-2.24.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jersey-container-servlet-2.24.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jersey-container-servlet-core-2.24.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jersey-guava-2.24.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jersey-media-jaxb-2.24.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jersey-server-2.24.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jetty-continuation-9.2.15.v20160210.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jetty-http-9.2.15.v20160210.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jetty-io-9.2.15.v20160210.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jetty-security-9.2.15.v20160210.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jetty-server-9.2.15.v20160210.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jetty-servlet-9.2.15.v20160210.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jetty-servlets-9.2.15.v20160210.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jetty-util-9.2.15.v20160210.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/jopt-simple-5.0.3.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/kafka_2.10-0.10.2.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/kafka_2.10-0.10.2.1-sources.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/kafka_2.10-0.10.2.1-test-sources.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/kafka-clients-0.10.2.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/kafka-log4j-appender-0.10.2.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/kafka-streams-0.10.2.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/kafka-streams-examples-0.10.2.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/kafka-tools-0.10.2.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/log4j-1.2.17.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/lz4-1.3.0.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/metrics-core-2.2.0.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/osgi-resource-locator-1.0.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/reflections-0.9.10.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/rocksdbjni-5.0.1.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/scala-library-2.10.6.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/slf4j-api-1.7.21.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/slf4j-log4j12-1.7.21.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/snappy-java-1.1.2.6.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/validation-api-1.1.0.Final.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/zkclient-0.10.jar:/usr/local/hadoop/kafka_2.10-0.10.2.1/bin/../libs/zookeeper-3.4.9.jar org.apache.kafka.tools.ProducerPerformance
3)尋找org.apache.kafka.tools.ProducerPerformance類
這個類在
<!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka-tools -->
<dependency>
<groupId>org.apache.kafka</groupId>
<artifactId>kafka-tools</artifactId>
<version>0.10.2.1</version>
</dependency>
4）ProducerPerformance做定製
/**
* 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.
*/
import static net.sourceforge.argparse4j.impl.Arguments.store;
import java.nio.charset.StandardCharsets;
import java.nio.file.Files;
import java.nio.file.Path;
import java.nio.file.Paths;
import java.util.ArrayList;
import java.util.Arrays;
import java.util.List;
import java.util.Properties;
import java.util.Random;
import net.sourceforge.argparse4j.inf.MutuallyExclusiveGroup;
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 net.sourceforge.argparse4j.ArgumentParsers;
import net.sourceforge.argparse4j.inf.ArgumentParser;
import net.sourceforge.argparse4j.inf.ArgumentParserException;
import net.sourceforge.argparse4j.inf.Namespace;
import org.apache.kafka.common.utils.Utils;
import org.apache.kafka.tools.ThroughputThrottler;
import log_exception_test.MyKafkaProducer;
public class MyProducerPerformance {
public static void main(String[] args) throws Exception {
//構造參數解析器
ArgumentParser parser = argParser();
//
try {
//解析
Namespace res = parser.parseArgs(args);
//提取參數
String topicName = res.getString("topic");
System.out.println("topicName --- " + topicName);
//
long numRecords = res.getLong("numRecords");
System.out.println("numRecords --- " + numRecords);
//
Integer recordSize = res.getInt("recordSize");
System.out.println("recordSize --- " + recordSize);
//
int throughput = res.getInt("throughput");
System.out.println("throughput --- " + throughput);
//
List<String> producerProps = res.getList("producerConfig");
System.out.println("producerProps --- " + producerProps);
//
String producerConfig = res.getString("producerConfigFile");
System.out.println("producerConfig --- " + producerConfig);
//
//payload自己通過程序生成
// since default value gets printed with the help text, we are escaping \n there and replacing it with correct value here.
String payloadDelimiter = res.getString("payloadDelimiter").equals("\\n") ? "\n"
: res.getString("payloadDelimiter");
System.out.println("payloadDelimiter --- " + payloadDelimiter);
if (producerProps == null && producerConfig == null) {
throw new ArgumentParserException(
"Either --producer-props or --producer.config must be specified.", parser);
}
//payload自己通過程序生成
List<byte[]> payloadByteList = new ArrayList<>();
String payloadFilePath = null;
if (payloadFilePath != null) {
Path path = Paths.get(payloadFilePath);
System.out.println("Reading payloads from: " + path.toAbsolutePath());
if (Files.notExists(path) || Files.size(path) == 0) {
throw new IllegalArgumentException(
"File does not exist or empty file provided.");
}
String[] payloadList = new String(Files.readAllBytes(path), "UTF-8")
.split(payloadDelimiter);
System.out.println("Number of messages read: " + payloadList.length);
for (String payload : payloadList) {
payloadByteList.add(payload.getBytes(StandardCharsets.UTF_8));
}
}
System.out.println("payload 自己通過程序生成");
//構造Properties屬性
Properties props = new Properties();
if (producerConfig != null) {
props.putAll(Utils.loadProps(producerConfig));
}
if (producerProps != null)
for (String prop : producerProps) {
String[] pieces = prop.split("=");
if (pieces.length != 2)
throw new IllegalArgumentException("Invalid property: " + prop);
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");
//開始構造Producer
KafkaProducer<byte[], byte[]> producer = new KafkaProducer<byte[], byte[]>(props);
/* setup perf test */
//payload需要自己構造
byte[] payload = null;
Random random = new Random(0);
//
ProducerRecord<byte[], byte[]> record;
Stats stats = new Stats(numRecords, 1000);
long startMs = System.currentTimeMillis();
//numRecords是總數
//throughput是每秒的吞吐量
ThroughputThrottler throttler = new ThroughputThrottler(throughput, startMs);
for (int i = 0; i < numRecords; i++) {
//這裏的payload從生產者隊列裏面取
//long begin = System.currentTimeMillis();
payload = MyQueue.getObject();
//long end = System.currentTimeMillis();
//System.out.println(end-begin);
record = new ProducerRecord<>(topicName, payload);
long sendStartMs = System.currentTimeMillis();
Callback cb = stats.nextCompletion(sendStartMs, payload.length, stats);
producer.send(record, cb);
if (throttler.shouldThrottle(i, sendStartMs)) {
throttler.throttle();
}
}
/* print final results */
producer.close();
stats.printTotal();
} catch (ArgumentParserException e) {
if (args.length == 0) {
parser.printHelp();
System.exit(0);
} else {
parser.handleError(e);
System.exit(1);
}
}
}
/** Get the command-line argument parser. */
private static ArgumentParser argParser() {
ArgumentParser parser = ArgumentParsers.newArgumentParser("producer-performance")
.defaultHelp(true).description("This tool is used to verify the producer performance.");
MutuallyExclusiveGroup payloadOptions = parser.addMutuallyExclusiveGroup().required(false)
.description("either --record-size or --payload-file must be specified but not both.");
parser.addArgument("--topic").action(store()).required(false).type(String.class)
.metavar("TOPIC").help("produce messages to this topic");
parser.addArgument("--num-records").action(store()).required(false).type(Long.class)
.metavar("NUM-RECORDS").dest("numRecords").help("number of messages to produce");
payloadOptions.addArgument("--record-size").action(store()).required(false)
.type(Integer.class).metavar("RECORD-SIZE").dest("recordSize").help(
"message size in bytes. Note that you must provide exactly one of --record-size or --payload-file.");
payloadOptions.addArgument("--payload-file").action(store()).required(false)
.type(String.class).metavar("PAYLOAD-FILE").dest("payloadFile")
.help(
"file to read the message payloads from. This works only for UTF-8 encoded text files. "
+ "Payloads will be read from this file and a payload will be randomly selected when sending messages. "
+ "Note that you must provide exactly one of --record-size or --payload-file.");
parser.addArgument("--payload-delimiter").action(store()).required(false).type(String.class)
.metavar("PAYLOAD-DELIMITER").dest("payloadDelimiter").setDefault("\\n")
.help("provides delimiter to be used when --payload-file is provided. "
+ "Defaults to new line. "
+ "Note that this parameter will be ignored if --payload-file is not provided.");
parser.addArgument("--throughput").action(store()).required(false).type(Integer.class)
.metavar("THROUGHPUT")
.help("throttle maximum message throughput to *approximately* THROUGHPUT messages/sec");
parser.addArgument("--producer-props").nargs("+").required(false)
.metavar("PROP-NAME=PROP-VALUE").type(String.class).dest("producerConfig")
.help(
"kafka producer related configuration properties like bootstrap.servers,client.id etc. "
+ "These configs take precedence over those passed via --producer.config.");
parser.addArgument("--producer.config").action(store()).required(false).type(String.class)
.metavar("CONFIG-FILE").dest("producerConfigFile")
.help("producer config properties file.");
return parser;
}
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 elapsed = System.currentTimeMillis() - start;
double recsPerSec = 1000.0 * count / (double) elapsed;
double mbPerSec = 1000.0 * this.bytes / (double) elapsed / (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();
}
}
}
import java.util.ArrayList;
import java.util.List;
import java.util.concurrent.BlockingQueue;
import java.util.concurrent.LinkedBlockingQueue;
import log_exception_test.MyKafkaProducer;
public class MyQueue {
// poll: 若隊列爲空，返回null。
// remove:若隊列爲空，拋出NoSuchElementException異常。
// take:若隊列爲空，發生阻塞，等待有元素。
// put---無空間會等待
// add--- 滿時,立即返回,會拋出異常
// offer---滿時,立即返回,不拋異常
// private static final Logger logger =
// LoggerFactory.getLogger(MonitorQueue.class);
public static BlockingQueue<byte[]> objectQueue = new LinkedBlockingQueue<byte[]>(50 * 10000);
public static void addObject(byte[] obj) {
objectQueue.offer(obj);
}
public static byte[] getObject() throws InterruptedException {
//System.out.println(objectQueue.size());
return objectQueue.take();
}
private static List list = new ArrayList();
static {
//啓動時,開啓線程
int total = 3;
for (int index = 0; index < total; index++) {
Thread thread = new Thread(new Runnable() {
@Override
public void run() {
while (true) {
byte[] data = MyKafkaProducer.getData();
addObject(data);
}
}
});
thread.start();
list.add(thread);
}
}
}
package log_exception_test;
import java.nio.charset.StandardCharsets;
import java.sql.Timestamp;
import java.util.Properties;
import java.util.Random;
import java.util.concurrent.Future;
import java.util.concurrent.atomic.AtomicLong;
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 com.alibaba.fastjson.JSON;
public class MyKafkaProducer {
// private static List<String> data = new ArrayList<String>();
// static {
// // for (int i = 0; i <= 6; i++)
// // data.add("1.0");
// // //
// // for (int i = 0; i <= 6; i++)
// // data.add("2.0");
// // //
// // for (int i = 0; i <= 1; i++)
// // data.add("3.0");
// data.add("1");
// data.add("1");
// data.add("1");
// data.add("1");
// data.add("1");
// data.add("1");
// data.add("1");
// data.add("2");
// data.add("2");
// data.add("2");
// data.add("11");
// data.add("11");
// data.add("11");
// data.add("11");
// data.add("11");
// data.add("11");
//
// }
private static AtomicLong totalSendSucceed = new AtomicLong(0);
private static AtomicLong totalSendFail = new AtomicLong(0);
private static long begin = System.currentTimeMillis();
private static String topic = "ymm-appmetric-dev-self1";
// private static long VALVE = 1;//30 * 10000 + 367;
private static String[] levels = new String[] { "DEBUG", "INFO", "WARN", "ERROR" };
public static byte[] getData() {
//構造send對象
Send send = new Send();
Random random = new Random();
//msg
send.setMsg(new Random().nextInt()
+ "Session 0x0 for server null, unexpected error, closing socket connection and attempting reconnect"
+ System.currentTimeMillis());
// send.setLoc(new Random().nextInt() + "org.apache.zookeeper.ClientCnxn"
// + System.currentTimeMillis());
send.setStack(new Random().nextInt()
+ "java.net.ConnectException: Connection timed out\\r\\nsun.nio.ch.SocketChannelImpl.checkConnect(Native Method)\\r\\nsun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:739)\\r\\norg.apache.zookeeper.ClientCnxnSocketNIO.doTransport(ClientCnxnSocketNIO.java:361)\\r\\norg.apache.zookeeper.ClientCnxn$SendThread.run(ClientCnxn.java:1141)\\r\\n"
+ System.currentTimeMillis());
send.setTimestamp(
new Random().nextInt() + "2018-11-20T01:45:52.160Z+" + System.currentTimeMillis());
send.setLevel(levels[random.nextInt(4)]);
send.setIp(//
random.nextInt(256)//
+ "."//
+ random.nextInt(256)////
+ "."//
+ random.nextInt(256)//
+ "."//
+ random.nextInt(256)//
);
send.setThrowable(
"java.net.ConnectException" + System.currentTimeMillis() + random.nextInt());
send.setTimeInSec(
"2018-11-20T09:45:51.000+0800" + System.currentTimeMillis() + random.nextInt());
send.setThread("localhost-startStop-1-SendThread(10.80.58.128:2181)"
+ System.currentTimeMillis() + new Random().nextInt());
send.setTime("" + random.nextInt(100000) + new Timestamp(System.currentTimeMillis()));
send.setPro("ymm-sms-web" + random.nextInt(256));
send.setType("log");
//
String value = JSON.toJSONString(send);
return value.getBytes(StandardCharsets.UTF_8);
}
@SuppressWarnings("unchecked")
private static void sendSingle(KafkaProducer producer, int index) {
long recordTime = System.currentTimeMillis();
//構造send對象
Send send = new Send();
Random random = new Random();
//msg
send.setMsg(random.nextInt()
+ "Session 0x0 for server null, unexpected error, closing socket connection and attempting reconnect"
+ System.currentTimeMillis());
// send.setLoc(new Random().nextInt() + "org.apache.zookeeper.ClientCnxn"
// + System.currentTimeMillis());
send.setStack(random.nextInt()
+ "java.net.ConnectException: Connection timed out\\r\\nsun.nio.ch.SocketChannelImpl.checkConnect(Native Method)\\r\\nsun.nio.ch.SocketChannelImpl.finishConnect(SocketChannelImpl.java:739)\\r\\norg.apache.zookeeper.ClientCnxnSocketNIO.doTransport(ClientCnxnSocketNIO.java:361)\\r\\norg.apache.zookeeper.ClientCnxn$SendThread.run(ClientCnxn.java:1141)\\r\\n"
+ System.currentTimeMillis());
send.setTimestamp(
new Random().nextInt() + "2018-11-20T01:45:52.160Z+" + System.currentTimeMillis());
send.setLevel(levels[random.nextInt(4)]);
send.setIp(//
random.nextInt(256)//
+ "."//
+ random.nextInt(256)////
+ "."//
+ random.nextInt(256)//
+ "."//
+ random.nextInt(256)//
);
send.setThrowable(
"java.net.ConnectException" + System.currentTimeMillis() + random.nextInt());
send.setTimeInSec(
"2018-11-20T09:45:51.000+0800" + System.currentTimeMillis() + random.nextInt());
send.setThread("localhost-startStop-1-SendThread(10.80.58.128:2181)"
+ System.currentTimeMillis() + new Random().nextInt());
send.setTime("" + random.nextInt() + new Timestamp(recordTime));
send.setPro("ymm-sms-web" + random.nextInt(256));
send.setType("log");
//
String value = JSON.toJSONString(send);
//System.out.println(value);
ProducerRecord<String, String> record = new ProducerRecord<String, String>(topic, value);
try {
Future future = producer.send(record,
new DemoCallback(recordTime, topic, "value_" + recordTime));
//future.get();
totalSendSucceed.incrementAndGet();
// System.out.println("本條發送完畢");
} catch (Exception e) {
totalSendFail.incrementAndGet();
System.out.println(e.toString());
} finally {
//System.exit(-1);
}
}
private static Send[] sendArray = new Send[] { new Send(//
"msg", //
"loc", //
"stack", //
"timestamp", //
"level", //
"ip", //
"throwable", //
"timeInSec", //
"thread", //
"time", //
"type", //
"pro"), //
new Send(//
"msg", //
"loc", //
"stack", //
"timestamp", //
"level", //
"ip", //
"throwable", //
"timeInSec", //
"thread", //
"time", //
"type", //
"pro")//
};
private static void unitTest() {
KafkaProducer<String, String> producer = getKafkaProducer();
//
int total = 100;
int mod = 1;
for (int index = 0; index < total; index++) {
Send send = new Send();
send.setPro("pro" + Math.abs(new Random().nextInt()) % mod);
send.setThrowable("throwable" + Math.abs(new Random().nextInt()) % mod);
send.setLevel("level" + Math.abs(new Random().nextInt()) % mod);
send.setIp("ip" + Math.abs(new Random().nextInt()) % mod);
long recordTime = System.currentTimeMillis();
String value = JSON.toJSONString(send);
//System.out.println(value);
ProducerRecord<String, String> record = new ProducerRecord<String, String>(topic,
value);
try {
Future future = producer.send(record,
new DemoCallback(recordTime, topic, "value_" + recordTime));
//future.get();
totalSendSucceed.incrementAndGet();
// System.out.println("本條發送完畢");
} catch (Exception e) {
totalSendFail.incrementAndGet();
System.out.println(e.toString());
} finally {
}
}
}
public static void main(String[] args) {
// unitTest();
// try {
// Thread.sleep(1000);
// } catch (InterruptedException e) {
// //logger.error("", e);
// }
// unitTest();
// try {
// Thread.sleep(1000);
// } catch (InterruptedException e) {
// //logger.error("", e);
// }
// unitTest();
int tag = 30;
Thread thread = null;
//負責發送1
if (tag >= 1) {
thread = new Thread(new Runnable() {
@Override
public void run() {
main0(args, 1, 90000001L);//
}
});
thread.start();
}
//負責發送2
if (tag >= 2) {
thread = new Thread(new Runnable() {
@Override
public void run() {
main0(args, 2, 90000002L);//
}
});
thread.start();
}
//負責發送3
if (tag >= 3) {
thread = new Thread(new Runnable() {
@Override
public void run() {
main0(args, 3, 90000003L);//
}
});
thread.start();
}
//負責發送4
if (tag >= 4) {
thread = new Thread(new Runnable() {
@Override
public void run() {
main0(args, 4, 90000004L);//
}
});
thread.start();
}
//負責發送5
if (tag >= 5) {
thread = new Thread(new Runnable() {
@Override
public void run() {
main0(args, 5, 90000005L);//
}
});
thread.start();
}
//負責發送6
if (tag >= 6) {
thread = new Thread(new Runnable() {
@Override
public void run() {
main0(args, 6, 90000006L);//
}
});
thread.start();
}
//負責發送7
if (tag >= 7) {
thread = new Thread(new Runnable() {
@Override
public void run() {
main0(args, 7, 90000007L);//
}
});
thread.start();
}
//統計線程
Thread statsThread = new Thread(new Runnable() {
@Override
public void run() {
long last = System.currentTimeMillis();
long lastsuc = 0;
long lastfail = 0;
//
while (true) {
long now = System.currentTimeMillis();
long elapsed = now - last;
if (elapsed >= 1000) {
long currentSuc = totalSendSucceed.get();
long currentFail = totalSendFail.get();
System.out
.println("elapsed " + elapsed + " - suc " + (currentSuc - lastsuc)
+ " total " + currentSuc + " fail " + (currentFail - lastfail)
+ " " + System.currentTimeMillis());
//
last = now;
lastsuc = currentSuc;
lastfail = currentFail;
}
}
//end
}
});
statsThread.start();
//
}
private static KafkaProducer<String, String> getKafkaProducer() {
Properties kafkaProps = new Properties();
//kafkaProps.put("bootstrap.servers", " 192.168.199.188:9092,192.168.198.109:9092,192.168.198.110:9092");
kafkaProps.put("bootstrap.servers", "192.168.199.188:9092");
kafkaProps.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
kafkaProps.put("value.serializer",
"org.apache.kafka.common.serialization.StringSerializer");
//網絡調優
//1)發送
kafkaProps.put("compression.type", "lz4");
kafkaProps.put("batch.size", "8196");
//2)
//kafkaProps.put(ProducerConfig.MAX_REQUEST_SIZE_CONFIG, "1024000");
// kafkaProps.put(ProducerConfig.MAX_IN_FLIGHT_REQUESTS_PER_CONNECTION,"1000");
//2)等待響應
kafkaProps.put(ProducerConfig.ACKS_CONFIG, "1");
kafkaProps.put(ProducerConfig.REQUEST_TIMEOUT_MS_CONFIG, "120000");
//3)超時重試
kafkaProps.put(ProducerConfig.RETRIES_CONFIG, 30);
//
// kafkaProps.put("batch.size", "10240");
// kafkaProps.put("linger.ms", "0");
KafkaProducer<String, String> producer = new KafkaProducer<String, String>(kafkaProps);
return producer;
}
public static void main0(String[] args, int index, Long valve) {
//
KafkaProducer<String, String> producer = getKafkaProducer();
System.out.println("發送開始 ");
long sendCount = 0;
while (true) {
try {
sendSingle(producer, index);
} catch (Exception e) {
System.out.println(e.toString());
} finally {
sendCount++;
if (sendCount >= valve) {
//線程結束
System.out.println("send " + index + " for " + valve + " 條 完畢!");
producer.close();
return;
}
}
}
}
static class DemoCallback implements Callback {
private long startTime;
@SuppressWarnings("unused")
private String key;
@SuppressWarnings("unused")
private String message;
public DemoCallback(long startTime, String key, String message) {
this.startTime = startTime;
this.key = key;
this.message = message;
}
@Override
public void onCompletion(RecordMetadata metadata, Exception exception) {
long elapsedTime = System.currentTimeMillis() - startTime;
if (null != exception) {
System.out.println(exception.toString());
return;
}
// if (null != metadata && elapsedTime >= 1000) {
// System.out.println("message(" + key + ", " + message + ") sent to partition("
// + metadata.partition()
// + "), " + "offset(" + metadata.offset() + " ) in " + elapsedTime + " ms");
//
// }
}
}
}
5）打包後執行
java -Xms1024M -Xmx1024M -server -XX:+UseG1GC -XX:MaxGCPauseMillis=20 -XX:InitiatingHeapOccupancyPercent=35 -XX:+DisableExplicitGC -Djava.awt.headless=true -Xloggc:./gc.log -verbose:gc -XX:+PrintGCDetails -XX:+PrintGCDateStamps -XX:+PrintGCTimeStamps -Dcom.sun.management.jmxremote -Dcom.sun.management.jmxremote.authenticate=false -Dcom.sun.management.jmxremote.ssl=false -jar kafkadriver-0.0.1-SNAPSHOT-shaded.jar --topic ymm-appmetric-dev-self1 --throughput 100000 --num-records 20000000 --producer-props bootstrap.servers=192.168.199.188:9092 client.id=myclientid batch.size=8196 compression.type=lz46）效果
.kafka.common.utils.AppInfoParser$AppInfo.<init>(AppInfoParser.java:84)
23804 records sent, 23638.5 records/sec (20.40 MB/sec), 16.6 ms avg latency, 304.0 max latency.
97041 records sent, 96944.1 records/sec (83.67 MB/sec), 14.1 ms avg latency, 84.0 max latency.
60257 records sent, 60257.0 records/sec (52.01 MB/sec), 9.4 ms avg latency, 108.0 max latency.
[2018-11-22 17:56:09,697] INFO Closing the Kafka producer with timeoutMillis = 9223372036854775807 ms. (org.apache.kafka.clients.producer.KafkaProducer) org.apache.kafka.clients.producer.KafkaProducer.close(KafkaProducer.java:689)
200000 records sent, 59790.732436 records/sec (51.61 MB/sec), 12.35 ms avg latency, 304.00 ms max latency, 7 ms 50th, 39 ms 95th, 64 ms 99th, 79 ms 99.9th.