摘要:4.4 采集日志Flume4.4.1 日志采集Flume安装集群规划:4.4.2 项目经验之Flume组件1)Source (1)Taildir Source相比Exec Source、Spooling Directory Source的优...
集群规划:
1)Source (1)Taildir Source相比Exec Source、Spooling Directory Source的优势 TailDir Source:断点续传、多目录。Flume1.6以前需要自己自定义Source记录每次读取文件位置,实现断点续传。 Exec Source可以实时搜集数据,但是在Flume不运行或者Shell命令出错的情况下,数据将会丢失。 Spooling Directory Source监控目录,不支持断点续传。 (2)batchSize大小如何设置? 答:Event 1K左右时,500-1000合适(默认为100) 2)Channel 采用Kafka Channel,省去了Sink,提高了效率。
1)Flume配置分析
Flume直接读log日志的数据,log日志的格式是app-yyyy-mm-dd.log。 2)Flume的具体配置如下: (1)在/opt/module/flume/conf目录下创建file-flume-kafka.conf文件
[kgg@hadoop101 conf]$ vim file-flume-kafka.conf
在文件配置如下内容
在文件配置如下内容
a1.sources=r1
a1.channels=c1 c2
# configure source
a1.sources.r1.type = TAILDIR
a1.sources.r1.positionFile = /opt/module/flume/test/log_position.json
a1.sources.r1.filegroups = f1
a1.sources.r1.filegroups.f1 = /tmp/logs/app.+
a1.sources.r1.fileHeader = true
a1.sources.r1.channels = c1 c2
#interceptor
a1.sources.r1.interceptors = i1 i2
a1.sources.r1.interceptors.i1.type = com.kgg.flume.interceptor.LogETLInterceptor$Builder
a1.sources.r1.interceptors.i2.type = com.kgg.flume.interceptor.LogTypeInterceptor$Builder
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
# configure channel
a1.channels.c1.type = org.apache.flume.channel.kafka.KafkaChannel
a1.channels.c1.kafka.bootstrap.servers = hadoop101:9092,hadoop102:9092,hadoop103:9092
a1.channels.c1.kafka.topic = topic_start
a1.channels.c1.parseAsFlumeEvent = false
a1.channels.c1.kafka.consumer.group.id = flume-consumer
a1.channels.c2.type = org.apache.flume.channel.kafka.KafkaChannel
a1.channels.c2.kafka.bootstrap.servers = hadoop101:9092,hadoop102:9092,hadoop103:9092
a1.channels.c2.kafka.topic = topic_event
a1.channels.c2.parseAsFlumeEvent = false
a1.channels.c2.kafka.consumer.group.id = flume-consumer
注意:com.kgg.flume.interceptor.LogETLInterceptor和com.kgg.flume.interceptor.LogTypeInterceptor是自定义的拦截器的全类名。需要根据用户自定义的拦截器做相应修改。
本项目中自定义了两个拦截器,分别是:ETL拦截器、日志类型区分拦截器。 ETL拦截器主要用于,过滤时间戳不合法和Json数据不完整的日志
日志类型区分拦截器主要用于,将启动日志和事件日志区分开来,方便发往Kafka的不同Topic。
1)创建Maven工程flume-interceptor
2)创建包名:com.kgg.flume.interceptor
3)在pom.xml文件中添加如下配置
<dependencies>
<dependency>
<groupId>org.apache.flume</groupId>
<artifactId>flume-ng-core</artifactId>
<version>1.7.0</version>
</dependency>
</dependencies>
<build>
<plugins>
<plugin>
<artifactId>maven-compiler-plugin</artifactId>
<version>2.3.2</version>
<configuration>
<source>1.8</source>
<target>1.8</target>
</configuration>
</plugin>
<plugin>
<artifactId>maven-assembly-plugin</artifactId>
<configuration>
<descriptorRefs>
<descriptorRef>jar-with-dependencies</descriptorRef>
</descriptorRefs>
</configuration>
<executions>
<execution>
<id>make-assembly</id>
<phase>package</phase>
<goals>
<goal>single</goal>
</goals>
</execution>
</executions>
</plugin>
</plugins>
</build>
4)在com.kgg.flume.interceptor包下创建LogETLInterceptor类名
Flume ETL拦截器LogETLInterceptor
package com.kgg.flume.interceptor;
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;
public class LogETLInterceptor implements Interceptor {
@Override
public void initialize() {
}
@Override
public Event intercept(Event event) {
// 1 获取数据
byte[] body = event.getBody();
String log = new String(body, Charset.forName("UTF-8"));
// 2 判断数据类型并向Header中赋值
if (log.contains("start")) {
if (LogUtils.validateStart(log)){
return event;
}
}else {
if (LogUtils.validateEvent(log)){
return event;
}
}
// 3 返回校验结果
return null;
}
@Override
public List<Event> intercept(List<Event> events) {
ArrayList<Event> interceptors = new ArrayList<>();
for (Event event : events) {
Event intercept1 = intercept(event);
if (intercept1 != null){
interceptors.add(intercept1);
}
}
return interceptors;
}
@Override
public void close() {
}
public static class Builder implements Interceptor.Builder{
@Override
public Interceptor build() {
return new LogETLInterceptor();
}
@Override
public void configure(Context context) {
}
}
}
4)Flume日志过滤工具类
package com.kgg.flume.interceptor;
import org.apache.commons.lang.math.NumberUtils;
public class LogUtils {
public static boolean validateEvent(String log) {
// 服务器时间 | json
// 1549696569054 | {"cm":{"ln":"-89.2","sv":"V2.0.4","os":"8.2.0","g":"M67B4QYU@gmail.com","nw":"4G","l":"en","vc":"18","hw":"1080*1920","ar":"MX","uid":"u8678","t":"1549679122062","la":"-27.4","md":"sumsung-12","vn":"1.1.3","ba":"Sumsung","sr":"Y"},"ap":"weather","et":[]}
// 1 切割
String[] logContents = log.split("\\|");
// 2 校验
if(logContents.length != 2){
return false;
}
//3 校验服务器时间
if (logContents[0].length()!=13 || !NumberUtils.isDigits(logContents[0])){
return false;
}
// 4 校验json
if (!logContents[1].trim().startsWith("{") || !logContents[1].trim().endsWith("}")){
return false;
}
return true;
}
public static boolean validateStart(String log) {
// {"action":"1","ar":"MX","ba":"HTC","detail":"542","en":"start","entry":"2","extend1":"","g":"S3HQ7LKM@gmail.com","hw":"640*960","l":"en","la":"-43.4","ln":"-98.3","loading_time":"10","md":"HTC-5","mid":"993","nw":"WIFI","open_ad_type":"1","os":"8.2.1","sr":"D","sv":"V2.9.0","t":"1559551922019","uid":"993","vc":"0","vn":"1.1.5"}
if (log == null){
return false;
}
// 校验json
if (!log.trim().startsWith("{") || !log.trim().endsWith("}")){
return false;
}
return true;
}
}
5)Flume日志类型区分拦截器LogTypeInterceptor
package com.kgg.flume.interceptor;
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;
public class LogTypeInterceptor implements Interceptor {
@Override
public void initialize() {
}
@Override
public Event intercept(Event event) {
// 区分日志类型: body header
// 1 获取body数据
byte[] body = event.getBody();
String log = new String(body, Charset.forName("UTF-8"));
// 2 获取header
Map<String, String> headers = event.getHeaders();
// 3 判断数据类型并向Header中赋值
if (log.contains("start")) {
headers.put("topic","topic_start");
}else {
headers.put("topic","topic_event");
}
return event;
}
@Override
public List<Event> intercept(List<Event> events) {
ArrayList<Event> interceptors = new ArrayList<>();
for (Event event : events) {
Event intercept1 = intercept(event);
interceptors.add(intercept1);
}
return interceptors;
}
@Override
public void close() {
}
public static class Builder implements Interceptor.Builder{
@Override
public Interceptor build() {
return new LogTypeInterceptor();
}
@Override
public void configure(Context context) {
}
}
}
6)打包 拦截器打包之后,只需要单独包,不需要将依赖的包上传。打包之后要放入Flume的lib文件夹下面。
注意:为什么不需要依赖包?因为依赖包在flume的lib目录下面已经存在了。
7)需要先将打好的包放入到hadoop101的/opt/module/flume/lib文件夹下面。
ls | grep interceptor
flume-interceptor-1.0-SNAPSHOT.jar
1)在/home/kgg/bin目录下创建脚本f1.sh
vim f1.sh
在脚本中填写如下内容
#! /bin/bash
case $1 in
"start"){
for i in hadoop101 hadoop102
do
echo " --------启动 $i 采集flume-------"
ssh $i "nohup /opt/module/flume/bin/flume-ng agent --conf-file /opt/module/flume/conf/file-flume-kafka.conf --name a1 -Dflume.root.logger=INFO,LOGFILE > /dev/null 2>&1 &"
done
};;
"stop"){
for i in hadoop101 hadoop102
do
echo " --------停止 $i 采集flume-------"
ssh $i "ps -ef | grep file-flume-kafka | grep -v grep |awk "{print \$2}" | xargs kill"
done
};;
esac
说明1:nohup,该命令可以在你退出帐户/关闭终端之后继续运行相应的进程。nohup就是不挂起的意思,不挂断地运行命令。 说明2:/dev/null代表linux的空设备文件,所有往这个文件里面写入的内容都会丢失,俗称“黑洞”。 标准输入0:从键盘获得输入 /proc/self/fd/0 标准输出1:输出到屏幕(即控制台) /proc/self/fd/1 错误输出2:输出到屏幕(即控制台) /proc/self/fd/2 2)增加脚本执行权限
chmod 777 f1.sh
3)f1集群启动脚本
f1.sh start
4)f1集群停止脚本
f1.sh stop