背景
上一篇我们介绍了Kafka Streams中的消息转换操作map，今天我们给出另一个经典的转换操作filter的用法。依然是结合一个具体的实例展开介绍。
演示功能说明
本篇演示filter用法，即根据给定的过滤条件或逻辑实时对每条消息进行过滤处理。今天使用的输入topic消息格式如下：
{"name": "George R. R. Martin", "title": "A Song of Ice and Fire"}
{"name": "C.S. Lewis", "title": "The Silver Chair"}
我们打算过滤出name是“George R. R. Martin”的所有消息并发送到输出topic上。
初始化项目
创建项目目录：
mkdir filter-streams
cd filter-streams/
配置项目
在filter-streams目录下创建build.gradle文件，内容如下：
buildscript {
repositories {
jcenter()
}
dependencies {
classpath 'com.github.jengelman.gradle.plugins:shadow:4.0.2'
}
}
plugins {
id 'java'
id "com.google.protob" version "0.8.10"
}
apply plugin: 'com.github.johnrengelman.shadow'
repositories {
mavenCentral()
jcenter()
maven {
url 'http://packages.confluent.io/maven'
}
}
group 'huxihx.kafkastreams'
sourceCompatibility = 1.8
targetCompatibility = '1.8'
version = '0.0.1'
dependencies {
implementation 'com.google.protobuf:protobuf-java:3.0.0'
implementation 'org.slf4j:slf4j-simple:1.7.26'
implementation 'org.apache.kafka:kafka-streams:2.3.0'
implementation 'com.google.protobuf:protobuf-java:3.9.1'
testCompile group: 'junit', name: 'junit', version: '4.12'
}
protobuf {
generatedFilesBaseDir = "$projectDir/src/"
protoc {
artifact = 'com.google.protobuf:protoc:3.0.0'
}
}
jar {
manifest {
attributes(
'Class-Path': configurations.compile.collect { it.getName() }.join(' '),
'Main-Class': 'huxihx.kafkastreams.FilteredStreamsApp'
)
}
}
shadowJar {
archiveName = "kstreams-transform-standalone-${version}.${extension}"
}
然后执行下列命令下载Gradle的wrapper套件：
gradle wrapper
之后在filter-streams目录下创建一个名为configuration的文件夹用于保存我们的参数配置文件：
mkdir configuration
创建一个名为dev.properties的文件：
application.id=filtering-app
bootstrap.servers=localhost:9092input.topic.name=publications
input.topic.partitions=1
input.topic.replication.factor=1output.topic.name=filtered-publications
output.topic.partitions=1output.topic.replication.factor=1
创建消息Schema
下一步是创建输入消息和输出消息的schema。由于我们今天只是做filter，所以输入和输出的格式一样的，只需要创建一份schema即可。首先，在filter-streams下执行命令创建保存schema的文件夹：
mkdir -p src/main/proto
之后创建publication.proto文件，内容如下：
syntax = "proto3";
package huxihx.kafkastreams.proto;
message Publication {
string name = 1;
string title = 2;
}
保存文件之后运行下列命令去编译对应的Java类：
./gradlew build
此时，你应该可以在src/main/java/huxihx/kafkastreams/proto下看到生成的Java类：PublicationOuterClass。
创建Serdes
这一步的Serdes和上一篇中的一样，因此不再赘述，直接上代码：
mkdir -p src/main/java/huxihx/kafkastreams/serdes
在新创建的serdes文件夹下创建ProtobufSerializer.java：
package huxihx.kafkastreams.serdes;
import com.google.protobuf.MessageLite;
import org.apache.kafka.common.serialization.Serializer;
public class ProtobufSerializer<T extends MessageLite> implements Serializer<T> {
@Override
public byte[] serialize(String topic, T data) {
return data == null ? new byte[0] : data.toByteArray();
}
}
然后创建ProtobufDeserializer.java：
package huxihx.kafkastreams.serdes;
import com.google.protobuf.InvalidProtocolBufferException;
import com.google.protobuf.MessageLite;
import com.google.protobuf.Parser;
import org.apache.kafka.common.errors.SerializationException;
import org.apache.kafka.common.serialization.Deserializer;
import java.util.Map;
public class ProtobufDeserializer<T extends MessageLite> implements Deserializer<T> {
private Parser<T> parser;
@Override
public void configure(Map<String, ?> configs, boolean isKey) {
parser = (Parser<T>) configs.get("parser");
}
@Override
public T deserialize(String topic, byte[] data) {
try {
return parser.parseFrom(data);
} catch (InvalidProtocolBufferException e) {
throw new SerializationException("Failed to deserialize from a protobuf byte array.", e);
}
}
}
最后创建ProtobufSerdes.java：
package huxihx.kafkastreams.serdes;
import com.google.protobuf.MessageLite;
import com.google.protobuf.Parser;
import org.apache.kafka.common.serialization.Deserializer;
import org.apache.kafka.common.serialization.Serde;
import org.apache.kafka.common.serialization.Serializer;
import java.util.HashMap;
import java.util.Map;
public class ProtobufSerdes<T extends MessageLite> implements Serde<T> {
private final Serializer<T> serializer;
private final Deserializer<T> deserializer;
public ProtobufSerdes(Parser<T> parser) {
serializer = new ProtobufSerializer<>();
deserializer = new ProtobufDeserializer<>();
Map<String, Parser<T>> config = new HashMap<>();
config.put("parser", parser);
deserializer.configure(config, false);
}
@Override
public Serializer<T> serializer() {
return serializer;
}
@Override
public Deserializer<T> deserializer() {
return deserializer;
}
}
开发主流程
在src/main/java/huxihx/kafkastreams下创建FilteredStreamsApp.java文件：
package huxihx.kafkastreams;
import huxihx.kafkastreams.proto.PublicationOuterClass;
import huxihx.kafkastreams.serdes.ProtobufSerdes;
import org.apache.kafka.clients.admin.AdminClient;
import org.apache.kafka.clients.admin.NewTopic;
import org.apache.kafka.common.serialization.Serde;
import org.apache.kafka.common.serialization.Serdes;
import org.apache.kafka.streams.KafkaStreams;
import org.apache.kafka.streams.StreamsBuilder;
import org.apache.kafka.streams.StreamsConfig;
import org.apache.kafka.streams.Topology;
import org.apache.kafka.streams.kstream.Consumed;
import org.apache.kafka.streams.kstream.Produced;
import java.io.FileInputStream;
import java.io.IOException;
import java.util.ArrayList;
import java.util.HashMap;
import java.util.List;
import java.util.Map;
import java.util.Properties;
import java.util.Set;
import java.util.concurrent.CountDownLatch;
public class FilteredStreamsApp {
private Properties buildStreamsProperties(Properties envProps) {
Properties props = new Properties();
props.put(StreamsConfig.APPLICATION_ID_CONFIG, envProps.getProperty("application.id"));
props.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, envProps.getProperty("bootstrap.servers"));
props.put(StreamsConfig.DEFAULT_KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass());
props.put(StreamsConfig.DEFAULT_VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass());
return props;
}
private void preCreateTopics(Properties envProps) throws Exception {
Map<String, Object> config = new HashMap<>();
config.put("bootstrap.servers", envProps.getProperty("bootstrap.servers"));
try (AdminClient client = AdminClient.create(config)) {
Set<String> existingTopics = client.listTopics().names().get();
List<NewTopic> topics = new ArrayList<>();
String inputTopic = envProps.getProperty("input.topic.name");
if (!existingTopics.contains(inputTopic)) {
topics.add(new NewTopic(inputTopic,
Integer.parseInt(envProps.getProperty("input.topic.partitions")),
Short.parseShort(envProps.getProperty("input.topic.replication.factor"))));
}
String outputTopic = envProps.getProperty("output.topic.name");
if (!existingTopics.contains(outputTopic)) {
topics.add(new NewTopic(outputTopic,
Integer.parseInt(envProps.getProperty("output.topic.partitions")),
Short.parseShort(envProps.getProperty("output.topic.replication.factor"))));
}
client.createTopics(topics);
}
}
private Properties loadEnvProperties(String filePath) throws IOException {
Properties envProps = new Properties();
try (FileInputStream input = new FileInputStream(filePath)) {
envProps.load(input);
}
return envProps;
}
private Topology buildTopology(Properties envProps, final Serde<PublicationOuterClass.Publication> publicationSerde) {
final StreamsBuilder builder = new StreamsBuilder();
final String inputTopic = envProps.getProperty("input.topic.name");
final String outputTopic = envProps.getProperty("output.topic.name");
builder.stream(inputTopic, Consumed.with(Serdes.String(), publicationSerde))
.filter((key, publication) -> "George R. R. Martin".equals(publication.getName()))
.to(outputTopic, Produced.with(Serdes.String(), publicationSerde));
return builder.build();
}
public static void main(String[] args) throws Exception {
if (args.length < 1) {
throw new IllegalArgumentException("Environment configuration file must be specified.");
}
FilteredStreamsApp app = new FilteredStreamsApp();
Properties envProps = app.loadEnvProperties(args[0]);
Properties streamProps = app.buildStreamsProperties(envProps);
app.preCreateTopics(envProps);
Topology topology = app.buildTopology(envProps, new ProtobufSerdes<>(PublicationOuterClass.Publication.parser()));
final KafkaStreams streams = new KafkaStreams(topology, streamProps);
final CountDownLatch latch = new CountDownLatch(1);
Runtime.getRuntime().addShutdownHook(new Thread("streams-jvm-shutdown-hook") {
@Override
public void run() {
streams.close();
latch.countDown();
}
});
try {
streams.start();
latch.await();
} catch (Exception e) {
System.exit(1);
}
System.exit(0);
}
}
编写测试Producer和Consumer
在src/main/java/huxihx/kafkastreams/tests/TestProducer.java和TestConsumer.java，内容分别如下：
package huxihx.kafkastreams.tests;
import huxihx.kafkastreams.proto.PublicationOuterClass;
import huxihx.kafkastreams.serdes.ProtobufSerializer;
import org.apache.kafka.clients.producer.KafkaProducer;
import org.apache.kafka.clients.producer.Producer;
import org.apache.kafka.clients.producer.ProducerRecord;
import java.util.Arrays;
import java.util.List;
import java.util.Properties;
public class TestProducer {
// 测试输入事件
private static final List<PublicationOuterClass.Publication> TEST_PUBLICATIONS = Arrays.asList(
PublicationOuterClass.Publication.newBuilder()
.setName("George R. R. Martin").setTitle("A Song of Ice and Fire").build(),
PublicationOuterClass.Publication.newBuilder()
.setName("C.S. Lewis").setTitle("The Silver Chair").build(),
PublicationOuterClass.Publication.newBuilder()
.setName("C.S. Lewis").setTitle("Perelandra").build(),
PublicationOuterClass.Publication.newBuilder()
.setName("George R. R. Martin").setTitle("Fire & Blood").build(),
PublicationOuterClass.Publication.newBuilder()
.setName("J. R. R. Tolkien").setTitle("The Hobbit").build(),
PublicationOuterClass.Publication.newBuilder()
.setName("J. R. R. Tolkien").setTitle("The Lord of the Rings").build(),
PublicationOuterClass.Publication.newBuilder()
.setName("George R. R. Martin").setTitle("A Dream of Spring").build(),
PublicationOuterClass.Publication.newBuilder()
.setName("J. R. R. Tolkien").setTitle("The Fellowship of the Ring").build(),
PublicationOuterClass.Publication.newBuilder()
.setName("George R. R. Martin").setTitle("The Ice Dragon").build());
public static void main(String[] args) {
Properties props = new Properties();
props.put("bootstrap.servers", "localhost:9092");
props.put("acks", "all");
props.put("key.serializer", "org.apache.kafka.common.serialization.StringSerializer");
props.put("value.serializer", new ProtobufSerializer<PublicationOuterClass.Publication>().getClass());
try (final Producer<String, PublicationOuterClass.Publication> producer = new KafkaProducer<>(props)) {
TEST_PUBLICATIONS.stream()
.map(publication -> new ProducerRecord<String, PublicationOuterClass.Publication>("publications", publication))
.forEach(producer::send);
}
}
}
package huxihx.kafkastreams.tests;
import com.google.protobuf.Parser;
import huxihx.kafkastreams.proto.PublicationOuterClass;
import huxihx.kafkastreams.serdes.ProtobufDeserializer;
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.serialization.Deserializer;
import org.apache.kafka.common.serialization.StringDeserializer;
import java.time.Duration;
import java.util.Arrays;
import java.util.HashMap;
import java.util.Map;
import java.util.Properties;
public class TestConsumer {
public static void main(String[] args) {
// 为输出事件构造protobuf deserializer
Deserializer<PublicationOuterClass.Publication> deserializer = new ProtobufDeserializer<>();
Map<String, Parser<PublicationOuterClass.Publication>> config = new HashMap<>();
config.put("parser", PublicationOuterClass.Publication.parser());
deserializer.configure(config, false);
Properties props = new Properties();
props.put("bootstrap.servers", "localhost:9092");
props.put("group.id", "test-group");
props.put("enable.auto.commit", "true");
props.put("auto.commit.interval.ms", "1000");
props.put("auto.offset.reset", "earliest");
KafkaConsumer<String, PublicationOuterClass.Publication> consumer = new KafkaConsumer<>(props, new StringDeserializer(), deserializer);
consumer.subscribe(Arrays.asList("filtered-publications"));
while (true) {
ConsumerRecords<String, PublicationOuterClass.Publication> records = consumer.poll(Duration.ofSeconds(1));
for (ConsumerRecord<String, PublicationOuterClass.Publication> record : records)
System.out.printf("offset = %d, key = %s, value = %s%n", record.offset(), record.key(), record.value());
}
}
}
测试
首先我们运行下列命令构建项目：
./gradlew shadowJar
然后启动Kafka集群，之后运行Kafka Streams应用：
java -jar build/libs/kstreams-transform-standalone-0.0.1.jar configuration/dev.properties
然后启动TestProducer发送测试事件：
java -cp build/libs/kstreams-transform-standalone-0.0.1.jar huxihx.kafkastreams.tests.TestProducer
最后启动TestConsumer验证Kafka Streams过滤出了指定的Publication消息：
java -cp build/libs/kstreams-transform-standalone-0.0.1.jar huxihx.kafkastreams.tests.TestConsumer
.......
offset = 0, key = null, value = name: "George R. R. Martin"
title: "A Song of Ice and Fire"offset = 1, key = null, value = name: "George R. R. Martin"
title: "Fire & Blood"offset = 2, key = null, value = name: "George R. R. Martin"
title: "A Dream of Spring"offset = 3, key = null, value = name: "George R. R. Martin"
title: "The Ice Dragon"
总结
下一篇介绍rekey的用法，即实时修改消息的Key值~~