1、默认拦截器

官网提供了几个默认拦截器，具体使用可查官方文档

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2、自定义拦截器（实现MapReducer中的日志的清洗功能）

a. 编写代码（实现Interceptor接口，并实现内部接口Builder）

Interceptor接口主要实现具体的拦截器的功能，内部接口Builder功能包含实例化Interceptor，以及获取配置文件传给Interceptor

package top.gujm.flume;

import org.apache.flume.Context;
import org.apache.flume.Event;
import org.apache.flume.interceptor.Interceptor;

import java.util.ArrayList;
import java.util.List;

public class LoggerFilterInterceptor implements Interceptor {
    public void initialize() {
    }
    public Event intercept(Event event) {
        String line = new String(event.getBody());
        String[] fields = line.split(" ");
        // 字段长度大于11
        if(fields.length  <= 11){
            return null;
        }
        // 校验状态码小于400
        if(Integer.parseInt(fields[8]) >= 400){
            return null;
        }
        return event;
    }
    public List<Event> intercept(List<Event> events) {
        List<Event> list = new ArrayList<Event>();
        for (Event event : events) {
            Event e = intercept(event);
            if (e != null)
                list.add(e);
        }
        return list;
    }
    public void close() {
    }
    public static class Builder implements Interceptor.Builder {
        public Interceptor build() {
            return new LoggerFilterInterceptor();
        }
        public void configure(Context context) {

        }
    }
}

b. 使用maven打包，并将jar包放入lib文件夹中

c. conf

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

a1.sources.r1.type = spooldir
a1.sources.r1.spoolDir = /opt/module/testData
#保存文件绝对路径到header
a1.sources.r1.fileHeader = true

a1.sources.r1.interceptors = i1
a1.sources.r1.interceptors.i1.type = top.gujm.flume.LoggerFilterInterceptor$Builder

a1.channels.c1.type = memory
a1.channels.c1.capacity = 10000
a1.channels.c1.transactionCapacity = 10000
a1.channels.c1.byteCapacityBufferPercentage = 20
a1.channels.c1.byteCapacity = 800000

a1.sinks.k1.type = hdfs
a1.sinks.k1.hdfs.path = hdfs://bigdata111:9000/flume/log/%y-%m-%d/%H%M
a1.sinks.k1.hdfs.filePrefix = log-
a1.sinks.k1.hdfs.useLocalTimeStamp = true
a1.sinks.k1.hdfs.rollSize = 134217728
a1.sinks.k1.hdfs.rollCount = 1000
#1小时滚动一次
a1.sinks.k1.hdfs.rollInterval = 3600

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

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