Flume对接Kafka之KafkaSink
默认配置对接
配置flume
创建并配置file-flume-kafka.conf
1.在flume/job中创建配置文件file-flume-kafka.conf
2.配置
#define
a1.sources = r1
a1.sinks = k1
a1.channels = c1
# source
a1.sources.r1.type = exec
a1.sources.r1.command = tail -F -c +0 /opt/module/data/flume.log
a1.sources.r1.shell = /bin/bash -c
# sink
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.bootstrap.servers = hadoop120:9092,hadoop121:9092,hadoop122:9092
a1.sinks.k1.kafka.topic = first
a1.sinks.k1.kafka.flumeBatchSize = 20
a1.sinks.k1.kafka.producer.acks = 1
a1.sinks.k1.kafka.producer.linger.ms = 1
# channel
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
# bind
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1
启动kafka消费者
[DIao@hadoop120 kafka]$ bin/kafka-console-consumer.sh --bootstrap-server hadoop120:9092 --topic first
启动flume
[Diao@hadoop120 flume]$ bin/flume-ng agent -c conf -f job/file-flume-kafka.conf -n a1
追加数据查看消费情况
[Diao@hadoop120 ~]$ cd /opt/module/datas/
[Diao@hadoop120 datas]$ echo aaa >> flume.log
自定义Flume的Kafka拦截器
创建自定义拦截
public class MyKafkainterceptor implements Interceptor {
//创建集合
private List<Event> eventHeader = null;
public void initialize() {
//初始化集合
eventHeader = new ArrayList<Event>();
}
public Event intercept(Event event) {
//获取event的header
Map<String, String> header = event.getHeaders();
//获取event的body
String body = new String(event.getBody());
//判断body中是否包含Diao
if(body != null && body.contains("Diao")){
header.put("topic","first"); ←这里的first是kafka中的分区号
}else{
header.put("topic", "second");←这里的second是kafka中的分区号
}
//返回event
return event;
}
public List<Event> intercept(List<Event> events) {
//清空集合
eventHeader.clear();
//遍历events
for(Event event:events){
eventHeader.add(intercept(event));
}
//返回集合
return eventHeader;
}
public static class Mybuilder implements Builder{
public Interceptor build() {
//创建自定义flume拦截器
return new MyKafkainterceptor();
}
public void configure(Context context) {
}
}
public void close() {
}
}
打成jar包放进flume/lib中
配置flume(和默认有所不同)
#define
a1.sources = r1
a1.sinks = k1
a1.channels = c1
# source
a1.sources.r1.type = exec
a1.sources.r1.command = tail -F -c +0 /opt/module/datas/flume.log
a1.sources.r1.shell = /bin/bash -c
a1.sources.r1.interceptors = i1 ←新东西 ←新东西 ←新东西 ←新东西
a1.sources.r1.interceptors.i1.type = com.alibaba.interceptor.MyKafkainterceptor$Mybuilder ←新东西 ←新东西
# sink
a1.sinks.k1.type = org.apache.flume.sink.kafka.KafkaSink
a1.sinks.k1.kafka.bootstrap.servers = hadoop120:9092,hadoop121:9092,hadoop122:9092
a1.sinks.k1.kafka.topic = first
# channel
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
# bind
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1
注意:不要配置成flume的自定义拦截器配置
a1.sources.r1.selector.type = multiplexing
a1.sources.r1.selector.header = title
a1.sources.r1.selector.mapping.A = c1
a1.sources.r1.selector.mapping.B = c2
a1.sources.r1.interceptors = i1
a1.sources.r1.interceptors.i1.type = com.alibaba.flume.Myinterceptor$MyBuild
flume的kafka拦截器不需要配上面四个配置
开启kakfa的两个消费者分别获取first和second分区信息
[Diao@hadoop120 kafka]$ bin/kafka-console-consumer.sh --bootstrap-server hadoop120:9092 --topic first
[Diao@hadoop120 kafka]$ bin/kafka-console-consumer.sh --bootstrap-server hadoop120:9092 -topic second
追加数据查看消费情况
数据1: echo BigDiao >> flume.log
数据2: echo OtherSmall >> flume.log
查看两个消费者是否分别接受到相应的数据