记一次Flume-KAFKA、kafka-hdfs操作

TAILDIR-KAFKA

a1.sources = r1
a1.channels = c1 c2

a1.sources.r1.type = TAILDIR
a1.sources.r1.filegroups = f1
a1.sources.r1.filegroups.f1 = /tmp/logs/app-.*log
a1.sources.r1.positionFile = /opt/installs/flume1.9/logs/taildir_position.json

a1.sources.r1.interceptors = i1
a1.sources.r1.interceptors.i1.type = demo.MyInterceptors$Bulider

a1.sources.r1.selector.type = multiplexing
a1.sources.r1.selector.header =    type        
a1.sources.r1.selector.mapping.start = c1      
a1.sources.r1.selector.mapping.event = c2

a1.channels.c1.type = org.apache.flume.channel.kafka.KafkaChannel
a1.channels.c1.kafka.bootstrap.servers = hadoop11:9092,hadoop12:9092,hadoop13:9092
a1.channels.c1.kafka.topic = topic1
a1.channels.c1.parseAsFlumeEvent = false

a1.channels.c2.type = org.apache.flume.channel.kafka.KafkaChannel
a1.channels.c2.kafka.bootstrap.servers = hadoop11:9092,hadoop12:9092,hadoop13:9092
a1.channels.c2.kafka.topic = topic2
a1.channels.c2.parseAsFlumeEvent = false

a1.sources.r1.channels = c1 c2
 

kafka-mem-hdfs

a1.sources = r1 r2
a1.channels = c1 c2
a1.sinks = k1 k2

a1.sources.r1.type = org.apache.flume.source.kafka.KafkaSource
a1.sources.r1.kafka.bootstrap.servers = hadoop11:9092,hadoop12:9092,hadoop13:9092
a1.sources.r1.kafka.topics = topic1
a1.sources.r1.kafka.consumer.group.id = g1

a1.sources.r2.type = org.apache.flume.source.kafka.KafkaSource
a1.sources.r2.kafka.bootstrap.servers = hadoop11:9092,hadoop12:9092,hadoop13:9092
a1.sources.r2.kafka.topics = topic2
a1.sources.r2.kafka.consumer.group.id = g1

a1.channels.c1.type = memory
a1.channels.c1.capacity = 10000
a1.channels.c1.transactionCapacity = 10000

a1.channels.c2.type = memory
a1.channels.c2.capacity = 10000
a1.channels.c2.transactionCapacity = 10000

a1.sinks.k1.type = hdfs
a1.sinks.k1.hdfs.path = hdfs://hdfs-cluster/origin_data/gmall/log/topic1/%Y-%m-%d
a1.sinks.k1.hdfs.useLocalTimeStamp = true
a1.sinks.k1.hdfs.fileType=DataStream
a1.sinks.k1.hdfs.rollInterval = 10
a1.sinks.k1.hdfs.rollSize = 104857600
a1.sinks.k1.hdfs.rollCount = 0
a1.sinks.k1.hdfs.filePrefix = logstart-

a1.sinks.k2.type = hdfs
a1.sinks.k2.hdfs.path = hdfs://hdfs-cluster/origin_data/gmall/log/topic2/%Y-%m-%d
a1.sinks.k2.hdfs.useLocalTimeStamp = true
a1.sinks.k2.hdfs.fileType=DataStream
a1.sinks.k2.hdfs.rollInterval = 10
a1.sinks.k2.hdfs.rollSize = 104857600
a1.sinks.k2.hdfs.rollCount = 0
a1.sinks.k2.hdfs.filePrefix = logevent-

a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

a1.sources.r2.channels = c2
a1.sinks.k2.channel = c2
 

拦截器代码

public class MyInterceptors implements Interceptor {
    @Override
    public void initialize() {

    }

    @Override
    public Event intercept(Event event) {
        byte[] body = event.getBody();
        String str = new String(body);

        Map<String, String> map = event.getHeaders();
        if(str.contains("\"en\":\"start\"")){
            map.put("type","start");
        }else{
            map.put("type","event");
        }
        return event;
    }

    @Override
    public List<Event> intercept(List<Event> list) {
        for(Event event:list){
            intercept(event);//循环，使集合中的每个event调用intercept方法，改变每个event中map的值为type-N/L
        }
        return list;
    }

    @Override
    public void close() {

    }
    public static class Bulider implements Interceptor.Builder{

        @Override
        public Interceptor build() {
            return new MyInterceptors();
        }

        @Override
        public void configure(Context context) {

        }
    }
}

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