电商数仓项目(八) Flume(3) 生产者和消费者配置

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本节讲解Flume 生产者和消费者配置。
源码下载

一、生产数据写到kafka

1. 将上节生成的flume-interceptor-1.0.0.jar文件上传到$FLUME_HOME/lib目录下
2. 在$FLUME_HOME/conf目录中创建file-flume-kafka.conf文件，
   文件目录：/u01/gmall/data/in/log-data
   读取的文件：app开头的文件

内容如下：

#定义Agent必需的组件名称，同时指定本配置文件的Agent名称为a1
a1.sources=r1
a1.channels=c1 c2

#定义Source组件相关配置
#使用Taildir Source
a1.sources.r1.type = TAILDIR
#配置Taildir Source，保存断点位置文件的目录
a1.sources.r1.positionFile = /u01/flume-1.9.0/position/log_position.json
#配置监控目录组
a1.sources.r1.filegroups = f1
#配置目录组下的目录，可配置多个目录
a1.sources.r1.filegroups.f1 = /u01/gmall/data/in/log-data/app.*

#配置Source发送数据的目标Channel
a1.sources.r1.channels = c1 c2

#拦截器
#配置拦截器名称
a1.sources.r1.interceptors =  i1 i2
#配置拦截器名称，需要写明全类名
a1.sources.r1.interceptors.i1.type = com.jack.flume.interceptor.LogETLInterceptor$Builder
a1.sources.r1.interceptors.i2.type = com.jack.flume.interceptor.LogTypeInterceptor$Builder

#配置Channel选择器
#配置选择器类型
a1.sources.r1.selector.type = multiplexing
#配置选择器识别header中的key
a1.sources.r1.selector.header = topic
#配置不同的header信息，发往不同的Channel
a1.sources.r1.selector.mapping.topicStart = c1
a1.sources.r1.selector.mapping.topicEvent = c2

# configure channel配置Channel
#配置Channel类型为Kafka Channel
a1.channels.c1.type = org.apache.flume.channel.kafka.KafkaChannel
#配置Kafka集群节点服务器列表
a1.channels.c1.kafka.bootstrap.servers = node01:9092,node02:9092,node03:9092
#配置该Channel发往Kafka的Topic，该Topic需要在Kafka中提前创建
a1.channels.c1.kafka.topic = topicStart
#配置不将header信息解析为event内容
a1.channels.c1.parseAsFlumeEvent = false
#配置该Kafka Channel所属的消费者组名，为实现multiplexing类型的Channel选择器，应将2个Kafka Channel配置相同的消费者组
a1.channels.c1.kafka.consumer.group.id = flume-consumer

#配置同上
a1.channels.c2.type = org.apache.flume.channel.kafka.KafkaChannel
a1.channels.c2.kafka.bootstrap.servers = node01:9092,node02:9092,node03:9092
a1.channels.c2.kafka.topic = topicEvent
a1.channels.c2.parseAsFlumeEvent = false
a1.channels.c2.kafka.consumer.group.id = flume-consumer

3. 分发到其他服务器（node01,node02)

[jack@node01 bin]$ cd /u01/bin
[jack@node01 bin]$ xsync /u01/flume-1.9.0

4. 生产者统一启动集群
   名称：flume_p.sh
   存放目录：/u01/bin
   问题跟踪：在使用中如果出现问题，在控制台使用 -Dflume.root.logger=DEBUG,console来跟踪问题

#!/bin/bash

pgmName=`basename $0`
pgmName=${pgmName##*/}    # remove the path
pgmExt=${pgmName##*.}     # get the extension
pgmName=${pgmName%.*}     # get the program name

USAGE="Usage: $pgmName.$pgmExt \n"

if [ $# -lt 1 ]
then
   echo $USAGE
   exit 1
fi

case $1 in
"start"){
  for i in node01 node02
  do
    echo "----------- start $i to collect flume ------------"
    ssh $i " source /etc/profile;nohup $FLUME_HOME/bin/flume-ng agent --conf-file $FLUME_HOME/conf/file-flume-kafka.conf --name a1 -Dflume.root.logger=INFO,LOGFILE >/dev/null 2>&1 &"
  done
};;
"stop"){
  for i in node01 node02
  do
    echo "----------- end $i to collect flume ------------"
    ssh $i "ps -ef|grep file-flume-kafka | grep -v grep |awk '{print \$2}' | xargs kill"
  done
};;
esac

二、消费kafka数据写到hdfs

1. 在node03节点，在$FLUME_HOME/conf目录中创建 kafka-flume-hdfs.conf 文件，hdfs文件使用lzo压缩。接收不同类型的文件放到不同的hdfs目录中。

## Flume Agent组件声明
a1.sources=r1 r2
a1.channels=c1 c2
a1.sinks=k1 k2

## Source1属性配置
#配置Source类型为Kafka Source
a1.sources.r1.type = org.apache.flume.source.kafka.KafkaSource
#配置Kafka Source每次从Kafka Topic中拉取的event个数
a1.sources.r1.batchSize = 5000
#配置拉取数据批次间隔为2000毫秒
a1.sources.r1.batchDurationMillis = 2000
#配置Kafka集群地址
a1.sources.r1.kafka.bootstrap.servers = node01:9092,node02:9092,node03:9092
#配置Source 对接Kafka主题
a1.sources.r1.kafka.topics=topicStart

## source2属性配置，与Source1配置类似，只是消费主题不同
a1.sources.r2.type = org.apache.flume.source.kafka.KafkaSource
a1.sources.r2.batchSize = 5000
a1.sources.r2.batchDurationMillis = 2000
a1.sources.r2.kafka.bootstrap.servers = node01:9092,node02:9092,node03:9092
a1.sources.r2.kafka.topics=topicEvent

## Channel1属性配置
#配置Channel类型为File Channel
a1.channels.c1.type = file
#配置存储File Channel传输数据的断点信息目录
a1.channels.c1.checkpointDir = /u01/flume-1.9.0/checkpoint/behavior1
#配置File Channel传输数据的存储位置
a1.channels.c1.dataDirs = /u01/flume-1.9.0/data/behavior1
#配置File Channel的最大存储容量
a1.channels.c1.maxFileSize = 2146435071
#配置File Channel最多存储event的个数
a1.channels.c1.capacity = 1000000
#配置Channel满时put事务的超时时间
a1.channels.c1.keep-alive = 6

## Channel2属性配置同Channel1，注意需要配置不同的目录路径
a1.channels.c2.type = file
a1.channels.c2.checkpointDir = /u01/flume-1.9.0/checkpoint/behavior2
a1.channels.c2.dataDirs = /u01/flume-1.9.0/data/behavior2
a1.channels.c2.maxFileSize = 2146435071
a1.channels.c2.capacity = 1000000
a1.channels.c2.keep-alive = 6

## Sink1属性配置
#配置Sink1类型为HDFS Sink
a1.sinks.k1.type = hdfs
#配置发到HDFS的存储路径
a1.sinks.k1.hdfs.path = hdfs://node01:9000/gmall/log/topicStart/%Y-%m-%d
#配置HDFS落盘文件的文件名前缀
a1.sinks.k1.hdfs.filePrefix = logstart-

##Sink2 属性配置同Sink1
a1.sinks.k2.type = hdfs
a1.sinks.k2.hdfs.path = hdfs://node01:9000/gmall/log/topicEvent/%Y-%m-%d
a1.sinks.k2.hdfs.filePrefix = logevent-

## 避免产生大量小文件的相关属性配置
a1.sinks.k1.hdfs.rollInterval = 10
a1.sinks.k1.hdfs.rollSize = 134217728
a1.sinks.k1.hdfs.rollCount = 0

a1.sinks.k2.hdfs.rollInterval = 10
a1.sinks.k2.hdfs.rollSize = 134217728
a1.sinks.k2.hdfs.rollCount = 0

## 控制输出文件是压缩文件
a1.sinks.k1.hdfs.fileType = CompressedStream 
a1.sinks.k2.hdfs.fileType = CompressedStream 

a1.sinks.k1.hdfs.codeC = lzop
a1.sinks.k2.hdfs.codeC = lzop

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

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

2. 消费者统一启动集群
   文件名：flume_c.sh
   目录：/u01/bin

#!/bin/bash

pgmName=`basename $0`
pgmName=${pgmName##*/}    # remove the path
pgmExt=${pgmName##*.}     # get the extension
pgmName=${pgmName%.*}     # get the program name

USAGE="Usage: $pgmName.$pgmExt \n"

if [ $# -lt 1 ]
then
   echo $USAGE
   exit 1
fi

case $1 in
"start"){
  for i in node03
  do
    echo "----------- start $i to collect flume ------------"
    ssh $i "source /etc/profile;nohup $FLUME_HOME/bin/flume-ng agent --conf-file $FLUME_HOME/conf/kafka-flume-hdfs.conf --name a1 -Dflume.root.logger=INFO,LOGFILE >/dev/null 2>&1 &"
  done
};;
"stop"){
  for i in node03
  do
    echo "----------- end $i to collect flume ------------"
    ssh $i "ps -ef|grep kafka-flume-hdfs | grep -v grep |awk '{print \$2}' | xargs kill"
  done
};;
esac

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电商数仓项目(一) 系统规划和配置
电商数仓项目(二) Maven 安装和hadoop-lzo编译
电商数仓项目(三) hadoop3.2.2 安装与配置
电商数仓项目(四) 模拟电商日志数据开发
电商数仓项目(五) azkaban安装、配置和使用
电商数仓项目(六) zookeeper安装和配置
电商数仓项目(七) kafka 安装、配置和简单操作
电商数仓项目(八) Flume(1) 安装和配置
电商数仓项目(八) Flume(2) 拦截器开发