flume对nginx群集日志收集方案

Flume是一个分布式、可靠、和高可用的海量日志聚合的系统，支持在系统中定制各类数据发送方，用于收集数据；同时，Flume提供对数据进行简单处理，并写到各种数据接受方（可定制）的能力。

flume的基本概念如下图

每个agent都具有三个元素，source、channel、sink。source：数据流的源。产生event。channel：可以理解成数据流的管道。传递eventsink : 数据流的终点。消耗event注：source可以上一节点的sink，sink可以指定为下一节点的source。比较常见的场景如下图

为以收集日志，并做实时的集中存储，元素相应类型如下1.source ： client端使用exec类型，通过tail –F 产生event。server端使用avro类型，用于接收client端发出的event2.channel ： 使用file类型。(测试期使用了mem类似)3. sink: client端使用avro类型，传递给server端。server端使用file_roll类型，指定相应目录储存日志。最终方案会使用hdfs


flume具体配置如下：1、将flume 解压到 /usr/local/flume下2、agent端配置flume允许对环境资源使用做设置，需要修改配置，/PREFIX/conf/flume-env.sh 可以通过实际情况进行调整
JAVA_OPTS="-Xms100m -Xmx200m -Dcom.sun.management.jmxremote"
#此处PREFIX 代表 /usr/local/flume

配置（/PREFIX/conf/flume-client.properties）
# Name the components on this agent
a1.sources = r1
a1.channels = c1
a1.sinks = k1

# Describe/configure the source
a1.sources.r1.type = exec
a1.sources.r1.command = tail -n 0 -F /space/nginxlogs/access.web.log
a1.sources.r1.channels = c1

# Describe/configure the channels (后面有memory channel配置方案)
a1.channels.c1.type = file
a1.channels.c1.keep-alive = 10
a1.channels.c1.write-timeout = 10
a1.channels.c1.checkpointDir = /space/guang_mobileapi_flume/checkpoint
a1.channels.c1.useDualCheckpoints = true
a1.channels.c1.backupCheckpointDir = /space/guang_mobileapi_flume/backupcheckpoint
a1.channels.c1.dataDirs = /space/guang_mobileapi_flume/data

# Describe/configure the sink
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = 192.168.10.35
a1.sinks.k1.port = 44444
a1.sinks.k1.channel = c1

（# Describe/configure the channels （次方案可以替换前面的file channel配置方案）
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
）

server配置：

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

# Describe/configure the source
a1.sources.r1.type = avro
a1.sources.r1.channels = c1
a1.sources.r1.bind = 0.0.0.0
a1.sources.r1.port = 44444

# Describe the sink
a1.sinks.k1.type = hdfs
a1.sinks.k1.hdfs.path = /logs/web/nginx/%Y%m%d
a1.sinks.k1.hdfs.rollInterval = 3600
a1.sinks.k1.hdfs.fileType = DataStream
a1.sinks.k1.hdfs.rollSize = 0
a1.sinks.k1.hdfs.rollCount = 0
a1.sinks.k1.hdfs.useLocalTimeStamp = true
a1.sinks.k1.hdfs.filePrefix = access.guang.j.cn
a1.sinks.k1.hdfs.inUseSuffix = .tmp
a1.sinks.k1.hdfs.idleTimeout = 300

# Use a channel which buffers events in memory
a1.channels.c1.type = file
a1.channels.c1.write-timeout = 10
a1.channels.c1.keep-alive = 10
a1.channels.c1.checkpointDir = /space/flume/checkpoint
a1.channels.c1.useDualCheckpoints = true
a1.channels.c1.backupCheckpointDir = /space/flume/backupcheckpoint
a1.channels.c1.dataDirs = /space/flume/data

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

(
# Describe the sink （前面面有hdfs方式）
a1.sinks.k1.type = file_roll
a1.sinks.k1.sink.directory = /tmp/test
a1.sinks.k1.sink.rollInterval = 3600

# Use a channel which buffers events in memory （前面有file channel配置方案）
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
)

以上配置1小时自动释放一次。可理解成每小时截断一次。因为hadoop目录使用日志变量，在某文件空闲5分钟后自己释放。
启动(client 和server端只有配置文件不同)cd /PREFIX./flume-ng agent -n a1 -c ../conf -f ../conf/flume-XXXXX.properties 2>/dev/null &
另附启停脚本
#!/bin/bash
PREFIX="/usr/local/flume"
AGENT="a1"start(){
echo starting
ps aux |grep -v grep|grep $PREFIX -q
if [ $? -eq 0 ];then
echo flume is already running
exit 1
fi
cd $PREFIX
bin/flume-ng agent -n $AGENT -c conf -f conf/flume-XXXXX.properties 2>/dev/null &
}
stop(){
ps aux |grep -v grep|grep $PREFIX -q
if [ $? -ne 0 ];then
echo flume is not running
else
ps aux |grep -v grep|grep $PREFIX|awk '{print $2}'|xargs kill -15
sleep 3
ps aux |grep -v grep|grep $PREFIX -q
[ $? -eq 0 ] && ps aux |grep flume|grep -v grep|awk '{print $2}'|xargs kill -9
fi
}
status(){
ps aux |grep -v grep|grep $PREFIX -q
if [ $? -eq 0 ];then
echo flume is running
else
echo flume is not running
fi
}
case $1 in
start)
start
;;
stop)
stop
;;
restart)
stop
sleep 1
start
;;
status)
status
;;
*)
echo "Useage : $0 [start|stop|restat|status]"
;;
esac

如果有不同的agent 并且server是一个 而且收集的日志不同，那么上述配置只需要修改几个地方就OK了

1、修改agent和server的端口
2、server端配置文件要换一个新的 而且中的a1 c1 r1 k1 换成其他标示如：a2 c2 r2 k2 以及a1.sinks.k1.hdfs.path a1.channels.c1.checkpointDir a1.channels.c1.backupCheckpointDir a1.channels.c1.dataDirs 的路径

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