#基本操作
参考:http://kafka.apache.org/quickstart#quickstart_multibroker

kakfa安装配置启动

http://kafka.apache.org/quickstart

• 启动zookerper
  root:~/kafka$ ./bin/zookeeper-server-start.sh config/zookeeper.properties
• 启动kafka
  root:~/kafka_2.12-0.10.2.1$ ./bin/kafka-server-start.sh config/server.properties

server.properties中的cluster_id要求唯一

• 创建主题:
  root:~/kafka_2.12-0.10.2.1$ bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic test
  Created topic "test".
• 启动producer
  root:~/kafka_2.12-0.10.2.1$ ./bin/kafka-console-producer.sh --broker-list localhost:9092 --topic test
• 启动consumer
  root:~/kafka_2.12-0.10.2.1$ ./bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic test --from-beginning

在Producer终端输入字符串,在Consumer终端将会接收到Producer端收到的信息

查看主题相关信息

root:~/kafka_2.12-0.10.2.1$ ./bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 3 --partitions 1 --topic my-replicated-topic

查看:

root:~/kafka_2.12-0.10.2.1$ ./bin/kafka-topics.sh --describe --zookeeper localhost:2181 --topic my-replicated-topic
Topic:my-replicated-topic PartitionCount:1 ReplicationFactor:3 Configs:
Topic: my-replicated-topic Partition: 0 Leader: 2 Replicas: 2,0,1 Isr: 2,0,1
每一行代表一个分区
leader:负责指定分区的所有读写操作的节点(cluster_id=2的节点)
replicas:对指定分区做日志复制的节点列表(cluster_id =2,0,1的节点)
isr:当前可用的或可成为leader的复制列表的子集(cluster_id =2,0,1的节点)

kafka设置多个集群

1. 设置新集群的配置文件
   cp config/server.properties config/server-1.properties
   修改以下配置:
   broker.id=1
   listeners=PLAINTEXT://:9093
   log.dir=/tmp/kafka-logs-1
2. 启动
   bin/kafka-server-start.sh config/server-1.properties

数据的导入

1. 设置连接
   root:~/kafka_2.12-0.10.2.1$ bin/connect-standalone.sh config/connect-standalone.properties config/connect-file-source.properties config/connect-file-sink.properties
2. 启动consumer监听指定主题
   root:~/kafka_2.12-0.10.2.1$ bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic connect-test --from-beginning
3. 文件输入
   root:~/kafka_2.12-0.10.2.1$ echo "line">>test.txt
   connect-file-source.properties文件中设置了数据导入来源,connect-file-sink.properties 设置了数据保存地址

数据处理

1. 新建主题
   root:~/kafka_2.12-0.10.2.1$ bin/kafka-topics.sh --create --zookeeper localhost:2181 --replication-factor 1 --partitions 1 --topic streams-file-input
2. 设置从文件中获取producer输入
   root:~/kafka_2.12-0.10.2.1$ bin/kafka-console-producer.sh --broker-list localhost:9092 --topic streams-file-input < file-input.txt
3. 新建应用
   root:~/kafka_2.12-0.10.2.1$ vi org.apache.kafka.streams.examples.wordcount.WordCountDemo
4. 运行应用
   root:~/kafka_2.12-0.10.2.1$ bin/kafka-run-class.sh org.apache.kafka.streams.examples.wordcount.WordCountDemo
5. 消费
   root:~/kafka_2.12-0.10.2.1$ bin/kafka-console-consumer.sh --bootstrap-server localhost:9092 --topic streams-wordcount-output --from-beginning --formatter kafka.tools.DefaultMessageFormatter --property key.deserializer=org.apache.kafka.common.serialization.StringDeserializer --property value.deserializer=org.apache.kafka.common.serialization.LongDeserializer --property print.key=true
   all 1
   lead 1
   to 1
   hello 1
   streams 2
   join 1
   kafka 3
   summit 1
   流处理是对发送的消息进行再次处理

java开发

参考:http://kafka.apache.org/documentation
kafka源代码中包含了java示例程序

1. 添加依赖

<!--kafka-->
<!-- https://mvnrepository.com/artifact/org.apache.kafka/kafka_2.10 -->
<dependency>
   <groupId>org.apache.kafka</groupId>
   <artifactId>kafka_2.10</artifactId>
   <version>0.10.2.1</version>
</dependency>
<dependency>
   <groupId>org.apache.kafka</groupId>
   <artifactId>kafka-clients</artifactId>
   <version>0.10.2.1</version>
</dependency>
<dependency>
   <groupId>org.apache.kafka</groupId>
   <artifactId>kafka-streams</artifactId>
   <version>0.10.2.1</version>
</dependency>
<!--kafka-->

stream

• 添加Producer和Consumer,并新建Stream要处理的消息主题
• 新建KafkaStreams对象
• 在Producer端发送消息,启动KafkaStreams运行

KStream的相关用法

• 针对每条消息记录进行处理:

//KStream示例
public static void main(String[] args) throws Exception {

   Properties props = new Properties();
   props.put(StreamsConfig.APPLICATION_ID_CONFIG, "streams-wordcount1");//一个stream应用指定一个topic
   props.put(StreamsConfig.BOOTSTRAP_SERVERS_CONFIG, "localhost:9092");
   props.put(StreamsConfig.KEY_SERDE_CLASS_CONFIG, Serdes.String().getClass().getName());
   props.put(StreamsConfig.VALUE_SERDE_CLASS_CONFIG, Serdes.String().getClass().getName());

   // setting offset reset to earliest so that we can re-run the demo code with the same pre-loaded data
   // Note: To re-run the demo, you need to use the offset reset tool:
   // https://cwiki.apache.org/confluence/display/KAFKA/Kafka+Streams+Application+Reset+Tool
   props.put(ConsumerConfig.AUTO_OFFSET_RESET_CONFIG, "earliest");
   KStreamBuilder builder = new KStreamBuilder();
   KStream<String, String> source = builder.stream("topic1");//input topic
   processMessage(source);
   KafkaStreams streams = new KafkaStreams(builder, props);
   streams.start();
}

private static void processMessage(KStream<String, String> source) throws FileNotFoundException {
   final PrintWriter printWriter = new PrintWriter(WordCountDemo.class.getResource("").getPath() + "outputfile");
   source.foreach(new ForeachAction<String, String>() {
       @Override
       public void apply(String key, String value) {
           printWriter.append("|").append(key).append("|").append("   ").append("|").append(value).append("|").append("\n");
           printWriter.flush();
       }
   });
source.print();//打印到控制台
source.writeAsText(WordCountDemo.class.getResource("").getPath() + "outputfile");//写入文件    
}

kafka用途

参考:http://kafka.apache.org/uses#uses_commitlog

1. 消息处理
2. 网站实时监测
3. 监控
4. 日志收集
5. 数据流处理
6. 事件跟踪(存在事件顺序)
   7.分布式系统的提交记录

源代码编译

1. 下载源码
   git clone http://git-wip-us.apache.org/repos/asf/kafka.git<kafka.project.dir>
2. gradle编译

• cd <kafka.project.dir>
• gradle idea