例子需求说明:
- 我们现在需要将日志中的数据读取到kafka当中且需要区分数据的,分别写入到两个不同的主题当中
flume作业conf配置如下:
source : taildir 实现断点续传 channel : 使用kafkachannel 写入到两个主题当中 sink : 没有使用 拦截器: 使用i1,i2两个拦截器 i1:做数据的清理, 防止脏数据,ETL拦截器 i2:做头部信息添加, 分类型拦截器 选择器:根据头部信息进行输出到kafka的哪个主题当中
a1.channels=c1 c2 a1.sources=r1 # a1.channels=c1 c2 a1.sources=r1 # a1.channels=c1 c2 a1.sources=r1 # a1.sources.r1.type = TAILDIR a1.sources.r1.positionFile = /opt/module/flume/test/taildir_position1.json a1.sources.r1.filegroups = f1 a1.sources.r1.filegroups.f1 = /tmp/logs/app.+ a1.sources.r1.fileHeader = true # channel a1.channels.c1.type = org.apache.flume.channel.kafka.KafkaChannel a1.channels.c1.kafka.bootstrap.servers = linux101:9092,linux102:9092,linux103:9092 a1.channels.c1.kafka.topic = topic_start a1.channels.c1.kafka.consumer.group.id = flume-consumer a1.channels.c1.parseAsFlumeEvent = false a1.channels.c2.type = org.apache.flume.channel.kafka.KafkaChannel a1.channels.c2.kafka.bootstrap.servers = linux101:9092,linux102:9092,linux103:9092 a1.channels.c2.kafka.topic = topic_event a1.channels.c2.kafka.consumer.group.id = flume-consumer a1.channels.c2.parseAsFlumeEvent = false # 拦截器 a1.sources.r1.interceptors=i1 i2 a1.sources.r1.interceptors.i1.type=com.dxy.LogETLInterceptor$Builder a1.sources.r1.interceptors.i2.type=com.dxy.LogTypeInterceptor$Builder #选择器 a1.sources.r1.selector.type = multiplexing a1.sources.r1.selector.header = topic a1.sources.r1.selector.mapping.topic_start = c1 a1.sources.r1.selector.mapping.topic_event = c2 # 绑定 a1.sources.r1.channels = c1 c2
依赖的导入:
org.apache.flume flume-ng-core 1.7.0 maven-compiler-plugin 3.8.0 1.8 1.8 maven-assembly-plugin jar-with-dependencies make-assembly package single
ETL清洗拦截器:
package com.dxy;
import org.apache.flume.Context;
import org.apache.flume.Event;
import org.apache.flume.interceptor.Interceptor;
import java.nio.charset.Charset;
import java.util.ArrayList;
import java.util.List;
//ETL清洗拦截器
public class LogETLInterceptor implements Interceptor {
@Override
public void initialize() {
}
@Override // 处理单事件
public Event intercept(Event event) {
byte[] bytes = event.getBody();
String str = new String(bytes, Charset.forName("UTF-8"));
//启动日志和事件日志的校验规则不一样 先进行区分
if(str.contains("start")){
//启动日志 说明:LogUtils工具类是一些脏数据判定规则
if(LogUtils.validateStartLog(str)) {
return event;
}
}else{
//事件日志
if(LogUtils.validateEventLog(str)) {
return event;
}
}
return null;
}
@Override //处理多事件
public List intercept(List list) {
ArrayList arrayList = new ArrayList<>();
for (Event event : list) {
Event intercept = intercept(event);
if(intercept!=null){
arrayList.add(intercept);
}
}
return arrayList;
}
//flume的拦截器必须要创建一个静态类对象
public static class Builder implements Interceptor.Builder{
@Override
public Interceptor build() {
return new LogETLInterceptor();
}
@Override
public void configure(Context context) {
}
}
@Override
public void close() {
}
}
分类型拦截器:
package com.dxy;
import org.apache.flume.Context;
import org.apache.flume.Event;
import org.apache.flume.interceptor.Interceptor;
import java.nio.charset.Charset;
import java.util.ArrayList;
import java.util.List;
import java.util.Map;
//分类型拦截器
public class LogTypeInterceptor implements Interceptor {
@Override
public void initialize() {
}
@Override
public Event intercept(Event event) {
byte[] body = event.getBody();
String s = new String(body, Charset.forName("UTF-8"));
Map header = event.getHeaders();
//如果日志数据中包含start字符串,就添加topic_start,就添加topic_event
if(s.contains("start")){
header.put("topic","topic_start");
}else{
header.put("topic","topic_event");
}
return event;
}
@Override//多事件处理 : 进行数据的缓冲
public List intercept(List list) {
ArrayList arrayList = new ArrayList<>();
for (Event event : list) {
Event intercept = intercept(event);
arrayList.add(intercept);
}
return arrayList;
}
//静态类
public static class Builder implements Interceptor.Builder{
@Override
public Interceptor build() {
return new LogTypeInterceptor();
}
@Override
public void configure(Context context) {
}
}
@Override
public void close() {
}
}
