04数据平台Flume

Flume 功能

Flume主要作用，就是实时读取服务器本地磁盘数据，将数据写入到 HDFS。

Flume是 Cloudera提供的高可用，高可靠性，分布式的海量日志采集、聚合和传输的系统工具。

Flume 架构

Flume组成架构如下图所示：

Agent

每个 Agent 代表着一个 JVM 进程，它以事件的方式将数据从源头送至目的地。

Agent 由 3 个部分组成，Source、Channel、Sink。

Source：Source是负责接收数据到Flume Agent 的组件，Source 组件可以处理各种类型、各种格式的日志数据。
Sink：Sink不断轮询Channel中的事件并且批量移除他们，并将这些数据批量写入到存储或者索引系统，或被发送到另一个Flume Agent。
Channel：Channel是位于Source 和Sink 之间的缓冲区。因此，Channel允许 Source和 Sink 有不同的运行速率。Channel 是线程安全的，可以同时处理几个 Source 的写操作和多个 Sink 的读操作。
Flume自带两种 Channel：Memory Channel 和File Channel。
Memory Channel 是一个内存队列，Source将事件写入其尾部，Sink从其头部读取事件。 Memory Channel 将源写入的事件存储在堆上。由于它将所有数据存储在内存中，因此提供了高吞吐量。它最适合那些不担心数据丢失的流。它不适合涉及数据丢失的数据流。
File Channel将所有事件写到磁盘。因此在程序关闭或机器宕机的情况下不会丢失数据。
Event：Flume 传输数据的基本单元，数据以 Event的形式将数据从源头送至目的地。Event由Header 和 Body 组成，Header用来存放event 的属性，为 K-V结构，Body 用于存放数据，为字节数组结构。

安装 flume

话不多说，直接开始安装 flume。

前往 http://archive.apache.org/dist/flume/ ，选择1.9.0
将apache-flume-1.9.0-bin.tar.gz使用 sftp上传到linux的/opt/software目录下
解压apache-flume-1.9.0-bin.tar.gz到/opt/module/目录下

[logan@hadoop101 hadoop]$ tar -zxf /opt/software/apache-flume-1.9.0-bin.tar.gz -C /opt/module/
创建软链接

cd /opt/module
ln -snf flume-1.9.0/ flume
删除jar 包，否则会报错

cd /opt/module/flume
rm lib/guava-11.0.2.jar

注意删除guava，一定要配置 Hadoop 环境变量，否则会报错：

Caused by: java.lang.ClassNotFoundException: com.google.common.collect.Lists
        at java.net.URLClassLoader.findClass(URLClassLoader.java:382)
        at java.lang.ClassLoader.loadClass(ClassLoader.java:424)
        at sun.misc.Launcher$AppClassLoader.loadClass(Launcher.java:349)
        at java.lang.ClassLoader.loadClass(ClassLoader.java:357)
        ... 1 more

修改log4j.properties配置文件

[logan@hadoop101 flume]$ vim conf/log4j.properties

注意是修改内容

flume.log.dir=/opt/module/flume/logs
验证 flume

[logan@hadoop101 flume]$ /opt/module/flume/bin/flume-ng version
Flume 1.9.0
Source code repository: https://git-wip-us.apache.org/repos/asf/flume.git
Revision: d4fcab4f501d41597bc616921329a4339f73585e
Compiled by fszabo on Mon Dec 17 20:45:25 CET 2018
From source with checksum 35db629a3bda49d23e9b3690c80737f9

Flume日志采集

配置解析

需要采集的日志文件分布在hadoop101，hadoop102两台日志服务器，故需要在hadoop101，hadoop102上配置日志采集 Flume。Flume需要采集日志文件内容，并对日志格式（JSON）进行校验，然后将校验通过的日志发送到 Kafka。

此处选择TailDirSource和 KafkaChannel。

TailDirSource优势：支持断点续传、多目录。
KafkaChannel优势：省去了 Sink，提高了效率。
日志采集 Flume关键配置：

Flume日志采集配置

创建Flume 配置文件

[logan@hadoop101 flume]$ pwd
/opt/module/flume
[logan@hadoop101 flume]$ mkdir job
[logan@hadoop101 flume]$ vim job/file_to_kafka.conf
#定义组件
a1.sources = r1
a1.channels = c1

#配置source
a1.sources.r1.type = TAILDIR
a1.sources.r1.filegroups = f1
a1.sources.r1.filegroups.f1 = /opt/module/applog/log/app.*
a1.sources.r1.positionFile = /opt/module/flume/taildir_position.json
a1.sources.r1.interceptors = i1
a1.sources.r1.interceptors.i1.type = com.logan.gmall.flume.interceptor.ETLInterceptor$Builder

#配置channel
a1.channels.c1.type = org.apache.flume.channel.kafka.KafkaChannel
a1.channels.c1.kafka.bootstrap.servers = hadoop101:9092
a1.channels.c1.kafka.topic = topic_log
a1.channels.c1.parseAsFlumeEvent = false

#组装
a1.sources.r1.channels = c1
编写拦截器
- 创建Maven工程flume-interceptor
- 创建包：com.logan.gmall.flume.interceptor
- 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>1.9.0</version> <scope>provided</scope> </dependency>
```
  <dependency>
      <groupId>com.alibaba</groupId>
      <artifactId>fastjson</artifactId>
      <version>1.2.62</version>
  </dependency>
```
  </dependencies> <build> <plugins> <plugin> <groupId>org.apache.maven.plugins</groupId> <artifactId>maven-compiler-plugin</artifactId> <version>2.4</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>
- 在com.logan.gmall.flume.utils包下创建JSONUtil类
  
  package com.logan.gmall.flume.utils;
  
  import com.alibaba.fastjson.JSON;
  import com.alibaba.fastjson.JSONException;
  
  public class JSONUtil {
  /**
  * 通过异常判定是否是JSON字符串
  */
  public static boolean isJSONValidate(String input){
  try {
  JSON.parseObject(input);
  return true;
  } catch (JSONException e) {
  return false;
  }
  }
  }
- 在com.logan.gmall.flume.interceptor包下创建ETLInterceptor类
  
  package com.logan.gmall.flume.interceptor;
  
  import com.logan.gmall.flume.utils.JSONUtil;
  import org.apache.flume.Context;
  import org.apache.flume.Event;
  import org.apache.flume.interceptor.Interceptor;
  
  import java.nio.charset.StandardCharsets;
  import java.util.Iterator;
  import java.util.List;
  
  public class ETLInterceptor implements Interceptor {
  @Override
  public void initialize() {
```
  }

  @Override
  public Event intercept(Event event) {

      //1、获取body当中的数据并转成字符串
      byte[] body = event.getBody();
      String log = new String(body, StandardCharsets.UTF_8);
      //2、判断字符串是否是一个合法的json，是：返回当前event；不是：返回null
      if (JSONUtil.isJSONValidate(log)) {
          return event;
      } else {
          return null;
      }
  }


  @Override
  public List<Event> intercept(List<Event> list) {

      Iterator<Event> iterator = list.iterator();

      while (iterator.hasNext()){
          Event next = iterator.next();
          if(intercept(next)==null){
              iterator.remove();
          }
      }

      return list;
  }

  public static class Builder implements Interceptor.Builder{

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

      @Override
      public void configure(Context context) {

      }
  }


  @Override
  public void close() {

  }
```
  }
- 打包
- 将打包文件放到hadoop101 的/opt/moduie/flume/lib文件夹下

采集测试

启动Zookeeper、Kafka集群
启动 hadoop101上的日志采集Flume

[logan@hadoop101 flume]$ bin/flume-ng agent -n a1 -c conf/ -f job/file_to_kafka.conf -Dflume.root.logger=info,console
启动一个Kafka的Console-Consumer

[logan@hadoop101 kafka]$ bin/kafka-console-consumer.sh --bootstrap-server hadoop11:9092 --topic topic_log
生成模拟数据

[logan@hadoop101 module]$ mkdir -p /opt/module/applog/log/
[logan@hadoop101 module]$ vim /opt/module/applog/log/app.2023-12-02.log
{"common":{"ar":"500000","ba":"iPhone","ch":"Appstore","is_new":"1","md":"iPhone Xs","mid":"mid_552171","os":"iOS 13.3.1","uid":"919","vc":"v2.1.134"},"displays":[{"display_type":"activity","item":"1","item_type":"activity_id","order":1,"pos_id":5},{"display_type":"activity","item":"2","item_type":"activity_id","order":2,"pos_id":5},{"display_type":"query","item":"19","item_type":"sku_id","order":3,"pos_id":4},{"display_type":"query","item":"3","item_type":"sku_id","order":4,"pos_id":2},{"display_type":"query","item":"5","item_type":"sku_id","order":5,"pos_id":2},{"display_type":"promotion","item":"19","item_type":"sku_id","order":6,"pos_id":4},{"display_type":"query","item":"14","item_type":"sku_id","order":7,"pos_id":2},{"display_type":"query","item":"9","item_type":"sku_id","order":8,"pos_id":2},{"display_type":"promotion","item":"35","item_type":"sku_id","order":9,"pos_id":1}],"page":{"during_time":9853,"page_id":"home"},"ts":1672512476000}
{"actions":[{"action_id":"favor_add","item":"9","item_type":"sku_id","ts":1672512480386},{"action_id":"get_coupon","item":"2","item_type":"coupon_id","ts":1672512483772}],"common":{"ar":"500000","ba":"iPhone","ch":"Appstore","is_new":"1","md":"iPhone Xs","mid":"mid_552171","os":"iOS 13.3.1","uid":"919","vc":"v2.1.134"},"displays":[{"display_type":"promotion","item":"19","item_type":"sku_id","order":1,"pos_id":4},{"display_type":"promotion","item":"14","item_type":"sku_id","order":2,"pos_id":5},{"display_type":"query","item":"21","item_type":"sku_id","order":3,"pos_id":1},{"display_type":"query","item":"11","item_type":"sku_id","order":4,"pos_id":2},{"display_type":"promotion","item":"28","item_type":"sku_id","order":5,"pos_id":1}],"page":{"during_time":10158,"item":"9","item_type":"sku_id","last_page_id":"home","page_id":"good_detail","source_type":"promotion"},"ts":1672512477000}
观察kafka是否有消费到数据