Spark Streaming实时流处理笔记（3）——日志采集Flume

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1 Flume介绍

1.1 设计目标

• 可靠性
• 扩展性
• 管理性

1.2 同类产品

• Flume: Cloudera/Apache,Java
• Scribe: Facebook ,C/C++(不维护了)
• Chukwa: Yahoo/Apache,Java
• Fluentd: Ruby
• Logstash:ELK(ElasticSearch,Kibana)

1.3 Flume发展史

1. Cloudera ,0.9.2,Flume-OG
2. Apache,flume-728,flume-NG

1.4 Event

Event是Flume中传输的基本数据单元，
Event = 可选header + byte array

2 Flume 架构及核心组件

• Source ,收集
• Channel, 聚集
• Sink,输出

2 Flume环境部署

2.1 配置JDK

2.2 下载 Flume

http://archive-primary.cloudera.com/cdh5/cdh/5/

[hadoop@node1 ~]$ ll
total 66760
drwxrwxr-x. 15 hadoop hadoop     4096 Nov  1 08:52 apps
drwxrwxr-x.  4 hadoop hadoop       30 Oct 25 21:59 elasticsearchData
-rw-r--r--.  1 hadoop hadoop 67321333 Dec  3 19:37 flume-ng-1.6.0-cdh5.7.0.tar.gz
drwxrwxr-x.  4 hadoop hadoop       28 Sep 14 19:02 hbase
drwxrwxr-x.  4 hadoop hadoop       32 Sep 14 14:44 hdfsdir
drwxrwxrwx.  3 hadoop hadoop       26 Oct 30 16:53 hdp2.6-cdh5.7-data
drwxrwxrwx.  3 hadoop hadoop       18 Oct 24 21:45 kafkaData
drwxrwxr-x.  5 hadoop hadoop      133 Oct 23 14:40 metastore_db
-rw-r--r--.  1 hadoop hadoop   999635 Aug 29  2017 mysql-connector-java-5.1.44-bin.jar
drwxr-xr-x. 30 hadoop hadoop     4096 Dec  2 18:40 spark-2.2.0
drwxrwxr-x.  3 hadoop hadoop       63 Oct 24 21:21 zookeeperData
-rw-rw-r--.  1 hadoop hadoop    26108 Oct 25 17:54 zookeeper.out
[hadoop@node1 ~]$ pwd
/home/hadoop
[hadoop@node1 ~]$ tar -zxvf flume-ng-1.6.0-cdh5.7.0.tar.gz -C /home/hadoop/apps

2.3 把 flume 配置到环境变量

vim /ect/profile

export FLUME_HOME=/home/hadoop/apps/apache-flume-1.6.0-cdh5.7.0-bin
export PATH=$PATH:$FLUME_HOME/bin

2.4 配置 flume-env.sh

[hadoop@node1 ~]$ cd $FLUME_HOME
[hadoop@node1 apache-flume-1.6.0-cdh5.7.0-bin]$ cd conf
[hadoop@node1 conf]$ ll
total 16
-rw-r--r--. 1 hadoop hadoop 1661 Mar 24  2016 flume-conf.properties.template
-rw-r--r--. 1 hadoop hadoop 1110 Mar 24  2016 flume-env.ps1.template
-rw-r--r--. 1 hadoop hadoop 1214 Mar 24  2016 flume-env.sh.template
-rw-r--r--. 1 hadoop hadoop 3107 Mar 24  2016 log4j.properties
[hadoop@node1 conf]$ cp flume-env.sh.template flume-env.sh
[hadoop@node1 conf]$ ll
total 20
-rw-r--r--. 1 hadoop hadoop 1661 Mar 24  2016 flume-conf.properties.template
-rw-r--r--. 1 hadoop hadoop 1110 Mar 24  2016 flume-env.ps1.template
-rw-r--r--. 1 hadoop hadoop 1214 Dec  3 19:48 flume-env.sh
-rw-r--r--. 1 hadoop hadoop 1214 Mar 24  2016 flume-env.sh.template
-rw-r--r--. 1 hadoop hadoop 3107 Mar 24  2016 log4j.properties
[hadoop@node1 conf]$ 

配置里面的 JAVA_HOME

3 Flume 测试案例

3.1 从指定网络端口采集数据到控制台

1. 编写配置文件
   参考https://flume.apache.org/FlumeUserGuide.html

[hadoop@node1 conf]$ pwd
/home/hadoop/apps/apache-flume-1.6.0-cdh5.7.0-bin/conf
[hadoop@node1 conf]$ mkdir myconf
[hadoop@node1 conf]$ cd myconf/
[hadoop@node1 myconf]$ vim logger.conf

# example.conf: A single-node Flume configuration

# Name the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1

# Describe/configure the source
a1.sources.r1.type = netcat
a1.sources.r1.bind = node1
a1.sources.r1.port = 44444

# Describe the sink
a1.sinks.k1.type = logger

# Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100

# Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

2. 启动 agent

flume-ng agent --name a1 --conf $FLUME_HOME/conf --conf-file $FLUME_HOME/conf/myconf/logger.conf -Dflume.root.logger=INFO,console

3. 测试
   
   

3.2 监控一个文件实时采集新增的数据输出到控制台

1. Agent选型 exec source + memory channel + logger sink
2. 新建配置文件

[hadoop@node1 myconf]$ vim exec-memory-logger.conf

# example.conf: A single-node Flume configuration

# Name the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1

# Describe/configure the source
a1.sources.r1.type = exec
a1.sources.r1.command = tail -F /home/hadoop/tempdata/data.log
a1.sources.r1.shell = /bin/sh -c

# Describe the sink
a1.sinks.k1.type = logger

# Use a channel which buffers events in memory
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100

# Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

3. 启动客户端

flume-ng agent --name a1 --conf $FLUME_HOME/conf --conf-file $FLUME_HOME/conf/myconf/exec-memory-logger.conf -Dflume.root.logger=INFO,console

3.3 将A服务器上的日志实时采集到B服务器

3.3.1 技术选型

• 第一组： exec source + memory channel +avro sink
• 第二组 ：avro source + memory channel + logger sink

3.3.2 配置文件

1. exec-memory-avro.conf

# Name the components on this agent
exec-memory-avro.sources = exec-source
exec-memory-avro.sinks = avro-sink
exec-memory-avro.channels = memory-channel

# Describe/configure the source
exec-memory-avro.sources.exec-source.type = exec
exec-memory-avro.sources.exec-source.command = tail -F /home/hadoop/tempdata/data.log
exec-memory-avro.sources.exec-source.shell = /bin/sh -c

# Describe the sink
exec-memory-avro.sinks.avro-sink.type = avro
exec-memory-avro.sinks.avro-sink.hostname = node1
exec-memory-avro.sinks.avro-sink.port = 44444

# Use a channel which buffers events in memory
exec-memory-avro.channels.memory-channel.type = memory

# Bind the source and sink to the channel
exec-memory-avro.sources.exec-source.channels = memory-channel
exec-memory-avro.sinks.avro-sink.channel = memory-channel

2. avro-memory-logger.conf

# Name the components on this agent
avro-memory-logger.sources = avro-source
avro-memory-logger.sinks = logger-sink
avro-memory-logger.channels = memory-channel

# Describe/configure the source
avro-memory-logger.sources.avro-source.type = avro
avro-memory-logger.sources.avro-source.bind = node1
avro-memory-logger.sources.avro-source.port = 44444

# Describe the sink
avro-memory-logger.sinks.logger-sink.type = logger

# Use a channel which buffers events in memory
avro-memory-logger.channels.memory-channel.type = memory


# Bind the source and sink to the channel
avro-memory-logger.sources.avro-source.channels = memory-channel
avro-memory-logger.sinks.logger-sink.channel = memory-channel

3.3.3 启动客户端

先启动

flume-ng agent --name avro-memory-logger --conf $FLUME_HOME/conf --conf-file $FLUME_HOME/conf/myconf/avro-memory-logger.conf -Dflume.root.logger=INFO,console

再启动

flume-ng agent --name exec-memory-avro --conf $FLUME_HOME/conf --conf-file $FLUME_HOME/conf/myconf/exec-memory-avro.conf -Dflume.root.logger=INFO,console

3.3.4 结果