一、flume概述
1.定义
Flume是Cloudera提供的一个高可用的,高可靠的,分布式的海量日志采集、聚合和传输的系统。Flume基于流式架构,灵活简单。
2.flume架构
2.1.Agent
Agent是一个JVM进程,它以事件的形式将数据从源头送至目的。
Agent主要有3个部分组成,Source、Channel、Sink。
2.2.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,包括avro、thrift、exec、jms、spooling directory、netcat、sequence generator、syslog、http、legacy。
2.3.Sink
Sink不断地轮询Channel中的事件且批量地移除它们,并将这些事件批量写入到存储或索引系统、或者被发送到另一个Flume Agent。
Sink组件目的地包括hdfs、logger、avro、thrift、ipc、file、HBase、solr、自定义。
2.4.Channel
Channel是位于Source和Sink之间的缓冲区。因此,Channel允许Source和Sink运作在不同的速率上。
Flume自带两种Channel:Memory Channel和File Channel。
2.5.Event
传输单元,Flume数据传输的基本单元,以Event的形式将数据从源头送至目的地。Event由Header和Body两部分组成,Header用来存放该event的一些属性,为K-V结构,Body用来存放该条数据,形式为字节数组。
二、Flume快速入门
1.Flume安装部署
1)将apache-flume-1.7.0-bin.tar.gz上传到linux的/opt/software目录下
2)解压apache-flume-1.7.0-bin.tar.gz到/opt/module/目录下
[atguigu@hadoop102 software]$ tar -zxf apache-flume-1.7.0-bin.tar.gz -C /opt/module/
3)修改apache-flume-1.7.0-bin的名称为flume
[atguigu@hadoop102 module]$ mv apache-flume-1.7.0-bin flume
2.Flume入门案例
2.1.需求
使用Flume监听一个端口,收集该端口数据,并打印到控制台。
2.2.需求分析
2.3.实现步骤
1)安装netcat工具
[atguigu@hadoop102 software]$ sudo yum install -y nc
2)创建Flume Agent配置文件
在flume目录下创建job文件夹并进入job文件夹。
[atguigu@hadoop102 flume]$ mkdir job
[atguigu@hadoop102 flume]$ cd job/
在job文件夹下创建Flume Agent配置文件flume-netcat-logger.conf。
[atguigu@hadoop102 job]$ vim flume-netcat-logger.conf
在flume-netcat-logger.conf文件中添加如下内容。
# 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 = localhost
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
3)先开启flume监听端口
[atguigu@hadoop102 flume]$ bin/flume-ng agent -c conf/ -n a1 -f job/flume-netcat-logger.conf -Dflume.root.logger=INFO,console
4)使用netcat工具向本机的44444端口发送内容
[atguigu@hadoop102 ~]$ nc localhost 44444
hello
world
5)在Flume监听页面观察接收数据情况
三、Flume进阶
1.Flume事务
2.Flume Agent内部原理
重要组件
1)ChannelSelector
ChannelSelector的作用就是选出Event将要被发往哪个Channel。其共有两种类型,分别是Replicating(复制)和Multiplexing(多路复用)。
ReplicatingSelector会将同一个Event发往所有的Channel,Multiplexing会根据相应的原则,将不同的Event发往不同的Channel。
2)SinkProcessor
SinkProcessor共有三种类型,分别是DefaultSinkProcessor、LoadBalancingSinkProcessor和FailoverSinkProcessor。
DefaultSinkProcessor对应的是单个的Sink,LoadBalancingSinkProcessor和FailoverSinkProcessor对应的是Sink Group,LoadBalancingSinkProcessor可以实现负载均衡的功能,FailoverSinkProcessor可以错误恢复的功能。
3.Flume拓扑结构
3.1.简单串联
3.2.复制和多路复用
3.3.负载均衡和故障转移
3.4.聚合
4.Flume数据流监控
4.1.Ganglia的安装部署
1)安装httpd服务与php
[atguigu@hadoop102 flume]$ sudo yum -y install httpd php
2)安装其他依赖
[atguigu@hadoop102 flume]$ sudo yum -y install rrdtool perl-rrdtool rrdtool-devel
[atguigu@hadoop102 flume]$ sudo yum -y install apr-devel
3)安装ganglia
[atguigu@hadoop102 flume]$ sudo rpm -Uvh http://dl.fedoraproject.org/pub/epel/6/x86_64/epel-release-6-8.noarch.rpm
[atguigu@hadoop102 flume]$ sudo yum -y install ganglia-gmetad
[atguigu@hadoop102 flume]$ sudo yum -y install ganglia-web
[atguigu@hadoop102 flume]$ sudo yum install -y ganglia-gmond
4)修改配置文件
[atguigu@hadoop102 flume]$ sudo vim /etc/httpd/conf.d/ganglia.conf
# Ganglia monitoring system php web frontend
Alias /ganglia /usr/share/ganglia
<Location /ganglia>
Order deny,allow
#Deny from all
Allow from all
# Allow from 127.0.0.1
# Allow from ::1
# Allow from .example.com
</Location>
5) 修改配置文件/etc/ganglia/gmetad.conf
[atguigu@hadoop102 flume]$ sudo vim /etc/ganglia/gmetad.conf
修改为:
data_source "hadoop102" 192.168.1.102
6) 修改配置文件/etc/ganglia/gmond.conf
[atguigu@hadoop102 flume]$ sudo vim /etc/ganglia/gmond.conf
修改为:
cluster {
name = "hadoop102"
owner = "unspecified"
latlong = "unspecified"
url = "unspecified"
}
udp_send_channel {
#bind_hostname = yes # Highly recommended, soon to be default.
# This option tells gmond to use a source address
# that resolves to the machine's hostname. Without
# this, the metrics may appear to come from any
# interface and the DNS names associated with
# those IPs will be used to create the RRDs.
# mcast_join = 239.2.11.71
host = 192.168.1.102
port = 8649
ttl = 1
}
udp_recv_channel {
# mcast_join = 239.2.11.71
port = 8649
bind = 192.168.1.102
retry_bind = true
# Size of the UDP buffer. If you are handling lots of metrics you really
# should bump it up to e.g. 10MB or even higher.
# buffer = 10485760
}
7) 修改配置文件/etc/selinux/config
[atguigu@hadoop102 flume]$ sudo vim /etc/selinux/config
修改为:
# This file controls the state of SELinux on the system.
# SELINUX= can take one of these three values:
# enforcing - SELinux security policy is enforced.
# permissive - SELinux prints warnings instead of enforcing.
# disabled - No SELinux policy is loaded.
SELINUX=disabled
# SELINUXTYPE= can take one of these two values:
# targeted - Targeted processes are protected,
# mls - Multi Level Security protection.
SELINUXTYPE=targeted
尖叫提示:selinux本次生效关闭必须重启,如果此时不想重启,可以临时生效之:
[atguigu@hadoop102 flume]$ sudo setenforce 0
8) 启动ganglia
[atguigu@hadoop102 flume]$ sudo service httpd start
[atguigu@hadoop102 flume]$ sudo service gmetad start
[atguigu@hadoop102 flume]$ sudo service gmond start
9) 打开网页浏览ganglia页面
http://192.168.1.102/ganglia
尖叫提示:如果完成以上操作依然出现权限不足错误,请修改/var/lib/ganglia目录的权限:
[atguigu@hadoop102 flume]$ sudo chmod -R 777 /var/lib/ganglia
