日志采集框架Flume以及Flume的安装部署(一个分布式、可靠、和高可用的海量日志采集、聚合和传输的系统)

Flume支持众多的source和sink类型,详细手册可参考官方文档,更多source和sink组件

http://flume.apache.org/FlumeUserGuide.html

Flume官网入门指南:

日志采集框架Flume以及Flume的安装部署(一个分布式、可靠、和高可用的海量日志采集、聚合和传输的系统)

日志采集框架Flume以及Flume的安装部署(一个分布式、可靠、和高可用的海量日志采集、聚合和传输的系统)


1:Flume的概述和介绍:

(1):Flume是一个分布式、可靠、和高可用的海量日志采集、聚合和传输的系统。
(2):Flume可以采集文件,socket数据包等各种形式源数据,又可以将采集到的数据输出到HDFS、hbase、hive、kafka等众多外部存储系统中
(3):一般的采集需求,通过对flume的简单配置即可实现
(4):Flume针对特殊场景也具备良好的自定义扩展能力,因此,flume可以适用于大部分的日常数据采集场景

2:Flume的运行机制:

(1):Flume分布式系统中最核心的角色是agent,flume采集系统就是由一个个agent所连接起来形成。

(2):每一个agent相当于一个数据传递员,内部有三个组件:
    a):Source:采集源,用于跟数据源对接,以获取数据。主要作用是接受客户端发送的数据,并将数据发送到channel中,source和channel之间的关系是多对多的关系,不过一般情况下使用一个source对应多个channel。通过名称区分不同的source。flume常用的source有:Avro Source,Thrift Source,Exec Source,Kafka Source,Netcat Source。
    b):Sink:下沉地,采集数据的传送目的,用于往下一级agent传递数据或者往最终存储系统传递数据。主要作用就是定义数据写出方式,一般情况下sink从channel中获取数据,然后将数据写出到file,hdfs或者网络上。channel和sink之间的关系是一对多的关系,通过不同的名称来区分sink。Flume常用的sink有:hdfs sink,hive sink,file sink.hbase sink,avro sink,thrift sink,logger sink等等。
    c):Channel:angent内部的数据传输通道,用于从source将数据传递到sink。主要作用是提供一个数据传输通道,提供数据传输和数据存储等功能。source将数据放到channel中,sink从channel中拿数据。通过不同的命令来区分channel。Flume常用的channel有:memory channel,jdbc channel,kafka channel,file channel等等。

注意:Source 到 Channel 到 Sink之间传递数据的形式是Event事件;Event事件是一个数据流单元。

下面介绍单个Agent的fulme数据采集示意图:

日志采集框架Flume以及Flume的安装部署(一个分布式、可靠、和高可用的海量日志采集、聚合和传输的系统)

多级agent之间串联示意图:

日志采集框架Flume以及Flume的安装部署(一个分布式、可靠、和高可用的海量日志采集、聚合和传输的系统)

3:Flume的安装部署:

(1)、Flume的安装非常简单,只需要解压即可,当然,前提是已有hadoop环境:
  a):上传安装包到数据源所在节点上,上传过程省略。
  b):然后解压  tar -zxvf apache-flume-1.6.0-bin.tar.gz;

    [root@master package]# tar -zxvf apache-flume-1.6.0-bin.tar.gz -C /home/hadoop/
  c):然后进入flume的目录,修改conf下的flume-env.sh,在里面配置JAVA_HOME;(由于conf目录下面是 flume-env.sh.template,所以我复制一个flume-env.sh,然后进行修改JAVA_HOME)

    [root@master conf]# cp flume-env.sh.template flume-env.sh

    [root@master conf]# vim flume-env.sh

    然后将#注释去掉,加上自己的JAVA_HOME:export JAVA_HOME=/home/hadoop/jdk1.7.0_65
(2)、根据数据采集的需求配置采集方案,描述在配置文件中(文件名可任意自定义);
(3)、指定采集方案配置文件,在相应的节点上启动flume agent;

(4)、可以先用一个最简单的例子来测试一下程序环境是否正常(在flume的conf目录下新建一个文件);

4:部署安装好,可以开始配置采集方案(这里是一个简单的采集方案配置的使用,从网络端口接收数据,然后下沉到logger), 然后需要配置一个文件,这个采集配置文件名称,netcat-logger.conf,采集配置文件netcat-logger.conf的内容如下所示:

 # example.conf: A single-node Flume configuration

 # Name the components on this agent
#定义这个agent中各组件的名字,给那三个组件sources,sinks,channels取个名字,是一个逻辑代号:
#a1是agent的代表。
a1.sources = r1
a1.sinks = k1
a1.channels = c1 # Describe/configure the source 描述和配置source组件:r1
#类型, 从网络端口接收数据,在本机启动, 所以localhost, type=spoolDir采集目录源,目录里有就采
#type是类型,是采集源的具体实现,这里是接受网络端口的,netcat可以从一个网络端口接受数据的。netcat在linux里的程序就是nc,可以学习一下。
#bind绑定本机localhost。port端口号为44444。 a1.sources.r1.type = netcat
a1.sources.r1.bind = localhost
a1.sources.r1.port = # Describe the sink 描述和配置sink组件:k1
#type,下沉类型,使用logger,将数据打印到屏幕上面。
a1.sinks.k1.type = logger # Use a channel which buffers events in memory 描述和配置channel组件,此处使用是内存缓存的方式
#type类型是内存memory。
#下沉的时候是一批一批的, 下沉的时候是一个个eventChannel参数解释:
#capacity:默认该通道中最大的可以存储的event数量,1000是代表1000条数据。
#trasactionCapacity:每次最大可以从source中拿到或者送到sink中的event数量。
a1.channels.c1.type = memory
a1.channels.c1.capacity =
a1.channels.c1.transactionCapacity = # Bind the source and sink to the channel 描述和配置source  channel   sink之间的连接关系
#将sources和sinks绑定到channel上面。
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

下面在flume的conf目录下面编辑这个文件netcat-logger.conf:

[root@master conf]# vim netcat-logger.conf

日志采集框架Flume以及Flume的安装部署(一个分布式、可靠、和高可用的海量日志采集、聚合和传输的系统)

启动agent去采集数据,然后可以进行启动了,启动命令如下所示:

bin/flume-ng agent -c conf -f conf/netcat-logger.conf -n a1  -Dflume.root.logger=INFO,console

  -c conf   指定flume自身的配置文件所在目录

  -f conf/netcat-logger.con  指定我们所描述的采集方案

  -n a1  指定我们这个agent的名字

 启动命令:
#告诉flum启动一个agent。
#--conf conf指定配置参数,。
#conf/netcat-logger.conf指定采集方案的那个文件(自命名)。
#--name a1:agent的名字,即agent的名字为a1。
#-Dflume.root.logger=INFO,console给log4j传递的参数。
$ bin/flume-ng agent --conf conf --conf-file conf/netcat-logger.conf --name a1 -Dflume.root.logger=INFO,console

演示如下所示:

日志采集框架Flume以及Flume的安装部署(一个分布式、可靠、和高可用的海量日志采集、聚合和传输的系统)

启动的信息如下所示,可以启动到前台,也可以启动到后台:

 [root@master apache-flume-1.6.-bin]# bin/flume-ng agent --conf conf --conf-file conf/netcat-logger.conf --name a1 -Dflume.root.logger=INFO,console
Info: Sourcing environment configuration script /home/hadoop/apache-flume-1.6.-bin/conf/flume-env.sh
Info: Including Hadoop libraries found via (/home/hadoop/hadoop-2.4./bin/hadoop) for HDFS access
Info: Excluding /home/hadoop/hadoop-2.4./share/hadoop/common/lib/slf4j-api-1.7..jar from classpath
Info: Excluding /home/hadoop/hadoop-2.4./share/hadoop/common/lib/slf4j-log4j12-1.7..jar from classpath
Info: Including Hive libraries found via () for Hive access
+ exec /home/hadoop/jdk1..0_65/bin/java -Xmx20m -Dflume.root.logger=INFO,console -cp '/home/hadoop/apache-flume-1.6.0-bin/conf:/home/hadoop/apache-flume-1.6.0-bin/lib/*:/home/hadoop/hadoop-2.4.1/etc/hadoop:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/activation-1.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/asm-3.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/avro-1.7.4.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-beanutils-1.7.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-beanutils-core-1.8.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-cli-1.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-codec-1.4.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-collections-3.2.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-compress-1.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-configuration-1.6.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-digester-1.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-el-1.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-httpclient-3.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-io-2.4.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-lang-2.6.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-logging-1.1.3.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-math3-3.1.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/commons-net-3.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/guava-11.0.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/hadoop-annotations-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/hadoop-auth-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/httpclient-4.2.5.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/httpcore-4.2.5.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jackson-core-asl-1.8.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jackson-jaxrs-1.8.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jackson-mapper-asl-1.8.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jackson-xc-1.8.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jasper-compiler-5.5.23.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jasper-runtime-5.5.23.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/java-xmlbuilder-0.4.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jaxb-api-2.2.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jaxb-impl-2.2.3-1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jersey-core-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jersey-json-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jersey-server-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jets3t-0.9.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jettison-1.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jetty-6.1.26.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jetty-util-6.1.26.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jsch-0.1.42.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jsp-api-2.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/jsr305-1.3.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/junit-4.8.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/log4j-1.2.17.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/mockito-all-1.8.5.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/netty-3.6.2.Final.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/paranamer-2.3.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/protobuf-java-2.5.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/servlet-api-2.5.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/snappy-java-1.0.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/stax-api-1.0-2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/xmlenc-0.52.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/xz-1.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib/zookeeper-3.4.5.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/hadoop-common-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/hadoop-common-2.4.1-tests.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/hadoop-nfs-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/common/jdiff:/home/hadoop/hadoop-2.4.1/share/hadoop/common/lib:/home/hadoop/hadoop-2.4.1/share/hadoop/common/sources:/home/hadoop/hadoop-2.4.1/share/hadoop/common/templates:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/asm-3.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/commons-cli-1.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/commons-codec-1.4.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/commons-daemon-1.0.13.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/commons-el-1.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/commons-io-2.4.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/commons-lang-2.6.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/commons-logging-1.1.3.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/guava-11.0.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/jackson-core-asl-1.8.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/jackson-mapper-asl-1.8.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/jasper-runtime-5.5.23.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/jersey-core-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/jersey-server-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/jetty-6.1.26.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/jetty-util-6.1.26.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/jsp-api-2.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/jsr305-1.3.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/log4j-1.2.17.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/netty-3.6.2.Final.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/protobuf-java-2.5.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/servlet-api-2.5.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib/xmlenc-0.52.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/hadoop-hdfs-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/hadoop-hdfs-2.4.1-tests.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/hadoop-hdfs-nfs-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/jdiff:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/lib:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/sources:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/templates:/home/hadoop/hadoop-2.4.1/share/hadoop/hdfs/webapps:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/activation-1.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/aopalliance-1.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/asm-3.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/commons-cli-1.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/commons-codec-1.4.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/commons-collections-3.2.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/commons-compress-1.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/commons-httpclient-3.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/commons-io-2.4.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/commons-lang-2.6.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/commons-logging-1.1.3.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/guava-11.0.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/guice-3.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/guice-servlet-3.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jackson-core-asl-1.8.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jackson-jaxrs-1.8.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jackson-mapper-asl-1.8.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jackson-xc-1.8.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/javax.inject-1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jaxb-api-2.2.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jaxb-impl-2.2.3-1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jersey-client-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jersey-core-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jersey-guice-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jersey-json-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jersey-server-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jettison-1.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jetty-6.1.26.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jetty-util-6.1.26.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jline-0.9.94.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/jsr305-1.3.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/leveldbjni-all-1.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/log4j-1.2.17.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/protobuf-java-2.5.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/servlet-api-2.5.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/stax-api-1.0-2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/xz-1.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib/zookeeper-3.4.5.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/hadoop-yarn-api-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/hadoop-yarn-applications-distributedshell-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/hadoop-yarn-applications-unmanaged-am-launcher-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/hadoop-yarn-client-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/hadoop-yarn-common-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/hadoop-yarn-server-applicationhistoryservice-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/hadoop-yarn-server-common-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/hadoop-yarn-server-nodemanager-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/hadoop-yarn-server-resourcemanager-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/hadoop-yarn-server-tests-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/hadoop-yarn-server-web-proxy-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/lib:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/sources:/home/hadoop/hadoop-2.4.1/share/hadoop/yarn/test:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/aopalliance-1.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/asm-3.2.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/avro-1.7.4.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/commons-compress-1.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/commons-io-2.4.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/guice-3.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/guice-servlet-3.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/hadoop-annotations-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/hamcrest-core-1.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/jackson-core-asl-1.8.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/jackson-mapper-asl-1.8.8.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/javax.inject-1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/jersey-core-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/jersey-guice-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/jersey-server-1.9.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/junit-4.10.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/log4j-1.2.17.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/netty-3.6.2.Final.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/paranamer-2.3.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/protobuf-java-2.5.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/snappy-java-1.0.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib/xz-1.0.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/hadoop-mapreduce-client-app-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/hadoop-mapreduce-client-common-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/hadoop-mapreduce-client-core-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/hadoop-mapreduce-client-hs-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/hadoop-mapreduce-client-hs-plugins-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/hadoop-mapreduce-client-jobclient-2.4.1-tests.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/hadoop-mapreduce-client-shuffle-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/hadoop-mapreduce-examples-2.4.1.jar:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/lib-examples:/home/hadoop/hadoop-2.4.1/share/hadoop/mapreduce/sources:/home/hadoop/hadoop-2.4.1/contrib/capacity-scheduler/*.jar:/lib/*' -Djava.library.path=:/home/hadoop/hadoop-2.4./lib/native org.apache.flume.node.Application --conf-file conf/netcat-logger.conf --name a1
-- ::, (lifecycleSupervisor--) [INFO - org.apache.flume.node.PollingPropertiesFileConfigurationProvider.start(PollingPropertiesFileConfigurationProvider.java:)] Configuration provider starting
-- ::, (conf-file-poller-) [INFO - org.apache.flume.node.PollingPropertiesFileConfigurationProvider$FileWatcherRunnable.run(PollingPropertiesFileConfigurationProvider.java:)] Reloading configuration file:conf/netcat-logger.conf
-- ::, (conf-file-poller-) [INFO - org.apache.flume.conf.FlumeConfiguration$AgentConfiguration.addProperty(FlumeConfiguration.java:)] Added sinks: k1 Agent: a1
-- ::, (conf-file-poller-) [INFO - org.apache.flume.conf.FlumeConfiguration$AgentConfiguration.addProperty(FlumeConfiguration.java:)] Processing:k1
-- ::, (conf-file-poller-) [INFO - org.apache.flume.conf.FlumeConfiguration$AgentConfiguration.addProperty(FlumeConfiguration.java:)] Processing:k1
-- ::, (conf-file-poller-) [INFO - org.apache.flume.conf.FlumeConfiguration.validateConfiguration(FlumeConfiguration.java:)] Post-validation flume configuration contains configuration for agents: [a1]
-- ::, (conf-file-poller-) [INFO - org.apache.flume.node.AbstractConfigurationProvider.loadChannels(AbstractConfigurationProvider.java:)] Creating channels
-- ::, (conf-file-poller-) [INFO - org.apache.flume.channel.DefaultChannelFactory.create(DefaultChannelFactory.java:)] Creating instance of channel c1 type memory
-- ::, (conf-file-poller-) [INFO - org.apache.flume.node.AbstractConfigurationProvider.loadChannels(AbstractConfigurationProvider.java:)] Created channel c1
-- ::, (conf-file-poller-) [INFO - org.apache.flume.source.DefaultSourceFactory.create(DefaultSourceFactory.java:)] Creating instance of source r1, type netcat
-- ::, (conf-file-poller-) [INFO - org.apache.flume.sink.DefaultSinkFactory.create(DefaultSinkFactory.java:)] Creating instance of sink: k1, type: logger
-- ::, (conf-file-poller-) [INFO - org.apache.flume.node.AbstractConfigurationProvider.getConfiguration(AbstractConfigurationProvider.java:)] Channel c1 connected to [r1, k1]
-- ::, (conf-file-poller-) [INFO - org.apache.flume.node.Application.startAllComponents(Application.java:)] Starting new configuration:{ sourceRunners:{r1=EventDrivenSourceRunner: { source:org.apache.flume.source.NetcatSource{name:r1,state:IDLE} }} sinkRunners:{k1=SinkRunner: { policy:org.apache.flume.sink.DefaultSinkProcessor@1ce79b8 counterGroup:{ name:null counters:{} } }} channels:{c1=org.apache.flume.channel.MemoryChannel{name: c1}} }
-- ::, (conf-file-poller-) [INFO - org.apache.flume.node.Application.startAllComponents(Application.java:)] Starting Channel c1
-- ::, (lifecycleSupervisor--) [INFO - org.apache.flume.instrumentation.MonitoredCounterGroup.register(MonitoredCounterGroup.java:)] Monitored counter group for type: CHANNEL, name: c1: Successfully registered new MBean.
-- ::, (lifecycleSupervisor--) [INFO - org.apache.flume.instrumentation.MonitoredCounterGroup.start(MonitoredCounterGroup.java:)] Component type: CHANNEL, name: c1 started
-- ::, (conf-file-poller-) [INFO - org.apache.flume.node.Application.startAllComponents(Application.java:)] Starting Sink k1
-- ::, (conf-file-poller-) [INFO - org.apache.flume.node.Application.startAllComponents(Application.java:)] Starting Source r1
-- ::, (lifecycleSupervisor--) [INFO - org.apache.flume.source.NetcatSource.start(NetcatSource.java:)] Source starting
-- ::, (lifecycleSupervisor--) [INFO - org.apache.flume.source.NetcatSource.start(NetcatSource.java:)] Created serverSocket:sun.nio.ch.ServerSocketChannelImpl[/127.0.0.1:]

然后可以向这个端口发送数据,就打印出来了,因为这里输出是在console的:

相当于产生数据的源:[root@master hadoop]# telnet localhost 44444

[root@master hadoop]# telnet localhost 44444
bash: telnet: command not found

我的机器没有安装telnet ,所以先安装一下telnet ,如下所示:

第一步:检测telnet-server的rpm包是否安装 ???
  [root@localhost ~]# rpm -qa telnet-server
  若无输入内容,则表示没有安装。出于安全考虑telnet-server.rpm是默认没有安装的,而telnet的客户端是标配。即下面的软件是默认安装的。

第二步:若未安装,则安装telnet-server:

   [root@localhost ~]#yum install telnet-server

第三步:3、检测telnet的rpm包是否安装 ???
  [root@localhost ~]# rpm -qa telnet
  telnet-0.17-47.el6_3.1.x86_64

第四步:若未安装,则安装telnet:

  [root@localhost ~]# yum install telnet

第五步:重新启动xinetd守护进程???

  由于telnet服务也是由xinetd守护的,所以安装完telnet-server,要启动telnet服务就必须重新启动xinetd
  [root@locahost ~]#service xinetd restart

完成以上步骤以后可以开始你的命令,如我的:

  [root@master hadoop]# telnet localhost 44444
  Trying ::1...
  telnet: connect to address ::1: Connection refused
  Trying 127.0.0.1...
  Connected to localhost.
  Escape character is '^]'.

解决完上面的错误以后就可以开始测试telnet数据源发送和flume的接受:

测试,先要往agent采集监听的端口上发送数据,让agent有数据可采集,随便在一个能跟agent节点联网的机器上:telnet localhost 44444

日志采集框架Flume以及Flume的安装部署(一个分布式、可靠、和高可用的海量日志采集、聚合和传输的系统)

然后可以看到flume已经接受到了数据:

日志采集框架Flume以及Flume的安装部署(一个分布式、可靠、和高可用的海量日志采集、聚合和传输的系统)

如何退出telnet呢???

  首先按ctrl+]退出到telnet > ,然后输入telnet> quit即可退出,记住,quit后面不要加;

5:flume监视文件夹案例:

 监视文件夹

 第一步:
首先 在flume的conf的目录下创建文件名称为:vim spool-logger.conf的文件。
将下面的内容复制到这个文件里面。 # Name the components on this agent
a1.sources = r1
a1.sinks = k1
a1.channels = c1 # Describe/configure the source
#监听目录,spoolDir指定目录, fileHeader要不要给文件夹前坠名
a1.sources.r1.type = spooldir
a1.sources.r1.spoolDir = /home/hadoop/flumespool
a1.sources.r1.fileHeader = true # 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 =
a1.channels.c1.transactionCapacity = # Bind the source and sink to the channel
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1 第二步:根据a1.sources.r1.spoolDir = /home/hadoop/flumespool配置的文件路径,创建相应的目录。必须先创建对应的目录,不然报错。java.lang.IllegalStateException: Directory does not exist: /home/hadoop/flumespool
[root@master conf]# mkdir /home/hadoop/flumespool 第三步:启动命令:
bin/flume-ng agent -c ./conf -f ./conf/spool-logger.conf -n a1 -Dflume.root.logger=INFO,console
[root@master apache-flume-1.6.0-bin]# bin/flume-ng agent --conf conf --conf-file conf/spool-logger.conf --name a1 -Dflume.root.logger=INFO,console
第四步:测试:
往/home/hadoop/flumeSpool放文件(mv ././xxxFile /home/hadoop/flumeSpool),但是不要在里面生成文件。

6:采集目录到HDFS案例:

(1)采集需求:某服务器的某特定目录下,会不断产生新的文件,每当有新文件出现,就需要把文件采集到HDFS中去
(2)根据需求,首先定义以下3大要素
  a):采集源,即source——监控文件目录 :  spooldir
  b):下沉目标,即sink——HDFS文件系统  :  hdfs sink
  c):source和sink之间的传递通道——channel,可用file channel 也可以用内存channel
(3):Channel参数解释:

  capacity:默认该通道中最大的可以存储的event数量;

  trasactionCapacity:每次最大可以从source中拿到或者送到sink中的event数量;

  keep-alive:event添加到通道中或者移出的允许时间;

配置文件编写:

 #定义三大组件的名称
agent1.sources = source1
agent1.sinks = sink1
agent1.channels = channel1 # 配置source组件
agent1.sources.source1.type = spooldir
agent1.sources.source1.spoolDir = /home/hadoop/logs/
agent1.sources.source1.fileHeader = false #配置拦截器
agent1.sources.source1.interceptors = i1
agent1.sources.source1.interceptors.i1.type = host
agent1.sources.source1.interceptors.i1.hostHeader = hostname # 配置sink组件
agent1.sinks.sink1.type = hdfs
agent1.sinks.sink1.hdfs.path =hdfs://master:9000/weblog/flume-collection/%y-%m-%d/%H-%M
agent1.sinks.sink1.hdfs.filePrefix = access_log
agent1.sinks.sink1.hdfs.maxOpenFiles =
agent1.sinks.sink1.hdfs.batchSize=
agent1.sinks.sink1.hdfs.fileType = DataStream
agent1.sinks.sink1.hdfs.writeFormat =Text
agent1.sinks.sink1.hdfs.rollSize =
agent1.sinks.sink1.hdfs.rollCount =
agent1.sinks.sink1.hdfs.rollInterval =
#agent1.sinks.sink1.hdfs.round = true
#agent1.sinks.sink1.hdfs.roundValue =
#agent1.sinks.sink1.hdfs.roundUnit = minute
agent1.sinks.sink1.hdfs.useLocalTimeStamp = true
# Use a channel which buffers events in memory
agent1.channels.channel1.type = memory
agent1.channels.channel1.keep-alive =
agent1.channels.channel1.capacity =
agent1.channels.channel1.transactionCapacity = # Bind the source and sink to the channel
agent1.sources.source1.channels = channel1
agent1.sinks.sink1.channel = channel1

7:采集文件到HDFS案例:

(1):采集需求:比如业务系统使用log4j生成的日志,日志内容不断增加,需要把追加到日志文件中的数据实时采集到hdfs

(2):根据需求,首先定义以下3大要素

  采集源,即source——监控文件内容更新 :  exec  ‘tail -F file’

  下沉目标,即sink——HDFS文件系统  :  hdfs sink

  Source和sink之间的传递通道——channel,可用file channel 也可以用 内存channel

配置文件编写:

 agent1.sources = source1
agent1.sinks = sink1
agent1.channels = channel1 # Describe/configure tail -F source1
agent1.sources.source1.type = exec
agent1.sources.source1.command = tail -F /home/hadoop/logs/access_log
agent1.sources.source1.channels = channel1 #configure host for source
agent1.sources.source1.interceptors = i1
agent1.sources.source1.interceptors.i1.type = host
agent1.sources.source1.interceptors.i1.hostHeader = hostname # Describe sink1
agent1.sinks.sink1.type = hdfs
#a1.sinks.k1.channel = c1
agent1.sinks.sink1.hdfs.path =hdfs://master:9000/weblog/flume-collection/%y-%m-%d/%H-%M
agent1.sinks.sink1.hdfs.filePrefix = access_log
agent1.sinks.sink1.hdfs.maxOpenFiles =
agent1.sinks.sink1.hdfs.batchSize=
agent1.sinks.sink1.hdfs.fileType = DataStream
agent1.sinks.sink1.hdfs.writeFormat =Text
agent1.sinks.sink1.hdfs.rollSize =
agent1.sinks.sink1.hdfs.rollCount =
agent1.sinks.sink1.hdfs.rollInterval =
agent1.sinks.sink1.hdfs.round = true
agent1.sinks.sink1.hdfs.roundValue =
agent1.sinks.sink1.hdfs.roundUnit = minute
agent1.sinks.sink1.hdfs.useLocalTimeStamp = true # Use a channel which buffers events in memory
agent1.channels.channel1.type = memory
agent1.channels.channel1.keep-alive =
agent1.channels.channel1.capacity =
agent1.channels.channel1.transactionCapacity = # Bind the source and sink to the channel
agent1.sources.source1.channels = channel1
agent1.sinks.sink1.channel = channel1

待续......

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