Flume简介及使用

    1)官网地址
    http://flume.apache.org/
    2）日志采集工具    
　　Flume是一种分布式，可靠且可用的服务，用于有效地收集，聚合和移动大量日志数据。它具有基于流数据流的简单灵活的架构。它具有可靠的可靠性机制和许多故障转移和恢复机制，具有强大的容错能力。
它使用简单的可扩展数据模型，允许在线分析应用程序。
    3）为什么需要flume
    数据从哪里来？
    -》爬虫
    -》日志数据 flume
    -》传统型数据库 sqoop
    4)flume架构
    source:数据源
    产生数据流，同时source将产生的数据流传输到channel
    channel:传输通道
    用于桥接Source和sinks
    sinks:下沉
    从channel收集数据
    event:传输单元
    Flume数据传传输的基本单元，以事件的形式将数据送往目的地。

    1）下载安装包
    http://archive.apache.org/dist/flume/1.6.0/
    2）上传到linux
    alt+p
    3）解压
    tar -zxvf apache-flume-1.6.0-bin.tar.gz
    4)重命名
    mv apache-flume-1.6.0-bin/ flume
    cd flume/conf
    mv flume-env.sh.template flume-env.sh
    5)修改配置文件
    vi flume-env.sh
    export JAVA_HOME=/root/hd/jdk1.8.0_144

    yum search telnet
    yum intsall telnet.x86_64

#smple.conf: A single-node Flume configuration

# Name the components on this agent 定义变量方便调用 加s可以有多个此角色
a1.sources = r1
a1.sinks = k1
a1.channels = c1

# Describe/configure the source 描述source角色 进行内容定制
# 此配置属于tcp source 必须是netcat类型
a1.sources.r1.type = netcat 
a1.sources.r1.bind = localhost
a1.sources.r1.port = 44444

# Describe the sink 输出日志文件
a1.sinks.k1.type = logger

# Use a channel which buffers events in memory（file） 使用内存 总大小1000 每次传输100
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100

# Bind the source and sink to the channel 一个source可以绑定多个channel 
# 一个sinks可以只能绑定一个channel  使用的是图二的模型
a1.sources.r1.channels = c1
a1.sinks.k1.channel = c1

bin/flume-ng agent --conf conf/ --name a1 --conf-file conf/flumejob_telnet.conf -Dflume.root.logger=INFO,console

telnet localhost 44444

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

# Describe/configure the source 
# exec 执行一个命令的方式去查看文件 tail -F 实时查看
a1.sources.r1.type = exec
# 要执行的脚本command tail -F 默认10行 man tail  查看帮助
a1.sources.r1.command = tail -F /tmp/root/hive.log
# 执行这个command使用的是哪个脚本 -c 指定使用什么命令
# whereis bash
# bash: /usr/bin/bash /usr/share/man/man1/bash.1.gz 
a1.sources.r1.shell = /usr/bin/bash -c

# Describe the sink 
a1.sinks.k1.type = hdfs
a1.sinks.k1.hdfs.path = hdfs://hd09-1:9000/flume/%Y%m%d/%H
#上传文件的前缀
a1.sinks.k1.hdfs.filePrefix = logs-
#是否按照时间滚动文件夹
a1.sinks.k1.hdfs.round = true
#多少时间单位创建一个新的文件夹  秒 （默认30s）
a1.sinks.k1.hdfs.roundValue = 1
#重新定义时间单位（每小时滚动一个文件夹）
a1.sinks.k1.hdfs.roundUnit = minute
#是否使用本地时间戳
a1.sinks.k1.hdfs.useLocalTimeStamp = true
#积攒多少个 Event 才 flush 到 HDFS 一次
a1.sinks.k1.hdfs.batchSize = 500
#设置文件类型，可支持压缩
a1.sinks.k1.hdfs.fileType = DataStream
#多久生成一个新的文件 秒
a1.sinks.k1.hdfs.rollInterval = 30
#设置每个文件的滚动大小 字节（最好128M）
a1.sinks.k1.hdfs.rollSize = 134217700
#文件的滚动与 Event 数量无关
a1.sinks.k1.hdfs.rollCount = 0
#最小冗余数(备份数 生成滚动功能则生效roll hadoop本身有此功能 无需配置) 1份 不冗余
a1.sinks.k1.hdfs.minBlockReplicas = 1

# 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

bin/flume-ng agent --conf conf/ --name a1 --conf-file conf/flumejob_hdfs.conf

hdfs dfs -cat /flume/20181125/19/logs-.1543146164570

# 定义
a1.sources = r1
a1.sinks = k1
a1.channels = c1

# Describe/configure the source
a1.sources.r1.type = spooldir
# 监控的文件夹
a1.sources.r1.spoolDir = /root/spooldir
# 上传成功后显示后缀名 
a1.sources.r1.fileSuffix = .COMPLETED
# 如论如何 加绝对路径的文件名 默认false
a1.sources.r1.fileHeader = true

#忽略所有以.tmp 结尾的文件（正在被写入），不上传
# ^以任何开头 出现无限次 以.tmp结尾的
a1.sources.r1.ignorePattern = ([^ ]*\.tmp)

# Describe the sink 
a1.sinks.k1.type = hdfs
a1.sinks.k1.hdfs.path = hdfs://hd09-1:9000/flume/spooldir/%Y%m%d/%H
#上传文件的前缀
a1.sinks.k1.hdfs.filePrefix = spooldir-
#是否按照时间滚动文件夹
a1.sinks.k1.hdfs.round = true
#多少时间单位创建一个新的文件夹
a1.sinks.k1.hdfs.roundValue = 1
#重新定义时间单位
a1.sinks.k1.hdfs.roundUnit = hour
#是否使用本地时间戳
a1.sinks.k1.hdfs.useLocalTimeStamp = true
#积攒多少个 Event 才 flush 到 HDFS 一次
a1.sinks.k1.hdfs.batchSize = 50

#设置文件类型，可支持压缩
a1.sinks.k1.hdfs.fileType = DataStream
#多久生成一个新的文件
a1.sinks.k1.hdfs.rollInterval = 600
#设置每个文件的滚动大小大概是 128M 
a1.sinks.k1.hdfs.rollSize = 134217700
#文件的滚动与 Event 数量无关
a1.sinks.k1.hdfs.rollCount = 0
#最小副本数
a1.sinks.k1.hdfs.minBlockReplicas = 1

# 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

cd /root
mkdir spooldir

bin/flume-ng agent --conf conf/ --name a1 --conf-file conf/flumejob_dir.conf

cp -rf /root/a.txt /root/spooldir/

需求：监控hive.log文件，同时产生两个channel，一个channel对应的sink存储到hdfs中，另外一个channel对应的sink存储到本地。

# name the components on this agent 
a1.sources = r1
a1.sinks = k1 k2 
a1.channels = c1 c2
# 将数据流复制给多个 channel
a1.sources.r1.selector.type = replicating

# Describe/configure the source 
a1.sources.r1.type = exec
a1.sources.r1.command = tail -F /tmp/root/hive.log
a1.sources.r1.shell = /bin/bash -c


# Describe the sink
# 分两个端口发送数据 
a1.sinks.k1.type = avro 
a1.sinks.k1.hostname = hd09-1 
a1.sinks.k1.port = 4141

a1.sinks.k2.type = avro 
a1.sinks.k2.hostname = hd09-1 
a1.sinks.k2.port = 4142

# Describe the channel 
a1.channels.c1.type = memory 
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100

a1.channels.c2.type = memory 
a1.channels.c2.capacity = 1000
a1.channels.c2.transactionCapacity = 100

# Bind the source and sink to the channel 
a1.sources.r1.channels = c1 c2 
a1.sinks.k1.channel = c1
a1.sinks.k2.channel = c2

# Name the components on this agent 
a2.sources = r1
a2.sinks = k1 
a2.channels = c1

# Describe/configure the source
a2.sources.r1.type = avro 
# 端口抓取数据
a2.sources.r1.bind = hd09-1
a2.sources.r1.port = 4141

# Describe the sink 
a2.sinks.k1.type = hdfs
a2.sinks.k1.hdfs.path = hdfs://hd09-1:9000/flume2/%Y%m%d/%H

#上传文件的前缀
a2.sinks.k1.hdfs.filePrefix = flume2-
#是否按照时间滚动文件夹
a2.sinks.k1.hdfs.round = true
#多少时间单位创建一个新的文件夹
a2.sinks.k1.hdfs.roundValue = 1
#重新定义时间单位
a2.sinks.k1.hdfs.roundUnit = hour
#是否使用本地时间戳
a2.sinks.k1.hdfs.useLocalTimeStamp = true
#积攒多少个 Event 才 flush 到 HDFS 一次
a2.sinks.k1.hdfs.batchSize = 100

#设置文件类型，可支持压缩
a2.sinks.k1.hdfs.fileType = DataStream
#多久生成一个新的文件
a2.sinks.k1.hdfs.rollInterval = 600
#设置每个文件的滚动大小大概是 128M 
a2.sinks.k1.hdfs.rollSize = 134217700
#文件的滚动与 Event 数量无关
a2.sinks.k1.hdfs.rollCount = 0
#最小副本数
a2.sinks.k1.hdfs.minBlockReplicas = 1

# Describe the channel 
a2.channels.c1.type = memory 
a2.channels.c1.capacity = 1000
a2.channels.c1.transactionCapacity = 100

# Bind the source and sink to the channel 
a2.sources.r1.channels = c1
a2.sinks.k1.channel = c1

# Name the components on this agent 
a3.sources = r1
a3.sinks = k1 
a3.channels = c1

# Describe/configure the source 
a3.sources.r1.type = avro
a3.sources.r1.bind = hd09-1
a3.sources.r1.port = 4142

# Describe the sink 
a3.sinks.k1.type = file_roll
a3.sinks.k1.sink.directory = /root/flume2

# Describe the channel 
a3.channels.c1.type = memory 
a3.channels.c1.capacity = 1000
a3.channels.c1.transactionCapacity = 100


# Bind the source and sink to the channel 
a3.sources.r1.channels = c1
a3.sinks.k1.channel = c1

bin/flume-ng agent --conf conf/ --name a1 --conf-file conf/flumejob_1.conf

bin/flume-ng agent --conf conf/ --name a2 --conf-file conf/flumejob_2.conf

bin/flume-ng agent --conf conf/ --name a3 --conf-file conf/flumejob_3.conf

hdfs dfs -cat /flume2/20181125/20/flume2-.1543149406953.tmp