[大数据] Hadoop学习（17）-- Flume 企业开发案例

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[大数据]Hadoop学习（17）-- Flume 企业开发案例

1. 复制和多路复用

1. 1 案例需求

使用 Flume-1 监控文件变动，Flume-1 将变动内容传递给 Flume-2，Flume-2 负责存储
到 HDFS。同时 Flume-1 将变动内容传递给 Flume-3，Flume-3 负责输出到 Local FileSystem。

1.2 需求分析

单数据源多出口案例（选择器）
在这里插入图片描述

1.3 实现步骤

准备工作
job 目录下创建 group1 文件夹，datas/目录下创建 flume3 文件夹

创建 flume-file-flume.conf
配置 1 个接收日志文件的 source 和两个 channel、两个 sink，分别输送给 flume-flume-hdfs 和 flume-flume-dir。
添加如下内容

# Name the components on this agent
a1.sources = r1
a1.sinks = k1 k2
a1.channels = c1 c2
# 将数据流复制给所有 channel
a1.sources.r1.selector.type = replicating
# Describe/configure the source
a1.sources.r1.type = exec
a1.sources.r1.command = tail -F /opt/module/hive/logs/hive.log
a1.sources.r1.shell = /bin/bash -c
# Describe the sink
# sink 端的 avro 是一个数据发送者
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = hadoop102
a1.sinks.k1.port = 4141
a1.sinks.k2.type = avro
a1.sinks.k2.hostname = hadoop102
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

创建 flume-flume-hdfs.conf
配置上级 Flume 输出的 Source，输出是到 HDFS 的 Sink。
添加如下内容

# Name the components on this agent
a2.sources = r1
a2.sinks = k1
a2.channels = c1
# Describe/configure the source
# source 端的 avro 是一个数据接收服务
a2.sources.r1.type = avro
a2.sources.r1.bind = hadoop102
a2.sources.r1.port = 4141
# Describe the sink
a2.sinks.k1.type = hdfs
a2.sinks.k1.hdfs.path = hdfs://hadoop102:9820/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 = 30
#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
# 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

创建flume-flume-dir.conf
配置上级 Flume 输出的 Source，输出是到本地目录的 Sink。

# Name the components on this agent
a3.sources = r1
a3.sinks = k1
a3.channels = c2
# Describe/configure the source
a3.sources.r1.type = avro
a3.sources.r1.bind = hadoop102
a3.sources.r1.port = 4142
# Describe the sink
a3.sinks.k1.type = file_roll
a3.sinks.k1.sink.directory = /opt/module/data/flume3
# Describe the channel
a3.channels.c2.type = memory
a3.channels.c2.capacity = 1000
a3.channels.c2.transactionCapacity = 100
# Bind the source and sink to the channel
a3.sources.r1.channels = c2
a3.sinks.k1.channel = c2

提示：输出的本地目录必须是已经存在的目录，如果该目录不存在，并不会创建新的目录。

执行配置文件
分别启动对应的 flume 进程：flume-flume-dir，flume-flume-hdfs，flume-file-flume。

 bin/flume-ng agent --conf conf/ --name a3 --conf-file job/group1/flume-flume-dir.conf
 bin/flume-ng agent --conf conf/ --name a2 --conf-file job/group1/flume-flume-hdfs.conf
 bin/flume-ng agent --conf conf/ --name a1 --conf-file job/group1/flume-file-flume.conf

启动 Hadoop 和 Hive
检查 HDFS 上数据
检查datas/flume3 目录中数据

2. 负载均衡和故障转移

2.1 案例需求

使用 Flume1 监控一个端口，其 sink 组中的 sink 分别对接 Flume2 和 Flume3，采用FailoverSinkProcessor，实现故障转移的功能。

2.2 需求分析

故障转移案例
在这里插入图片描述

2.3 实现步骤

准备工作
/job 目录下创建 group2 文件夹

创建 flume-netcat-flume.conf
配置 1 个 netcat source 和 1 个 channel、1 个 sink group（2 个 sink），分别输送给
flume-flume-console1 和 flume-flume-console2。

# Name the components on this agent
a1.sources = r1
a1.channels = c1
a1.sinkgroups = g1
a1.sinks = k1 k2
# Describe/configure the source
a1.sources.r1.type = netcat
a1.sources.r1.bind = localhost
a1.sources.r1.port = 44444
a1.sinkgroups.g1.processor.type = failover
a1.sinkgroups.g1.processor.priority.k1 = 5
a1.sinkgroups.g1.processor.priority.k2 = 10
a1.sinkgroups.g1.processor.maxpenalty = 10000
# Describe the sink
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = hadoop102
a1.sinks.k1.port = 4141
a1.sinks.k2.type = avro
a1.sinks.k2.hostname = hadoop102
a1.sinks.k2.port = 4142
# Describe the channel
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.sinkgroups.g1.sinks = k1 k2
a1.sinks.k1.channel = c1
a1.sinks.k2.channel = c1

创建 flume-flume-console1.conf
配置上级 Flume 输出的 Source，输出是到本地控制台。

# Name the components on this agent
a2.sources = r1
a2.sinks = k1
a2.channels = c1
# Describe/configure the source
a2.sources.r1.type = avro
a2.sources.r1.bind = hadoop102
a2.sources.r1.port = 4141
# Describe the sink
a2.sinks.k1.type = logger
# 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

创建 flume-flume-console2.conf
配置上级 Flume 输出的 Source，输出是到本地控制台。

# Name the components on this agent
a3.sources = r1
a3.sinks = k1
a3.channels = c2
# Describe/configure the source
a3.sources.r1.type = avro
a3.sources.r1.bind = hadoop102
a3.sources.r1.port = 4142
# Describe the sink
a3.sinks.k1.type = logger
# Describe the channel
a3.channels.c2.type = memory
a3.channels.c2.capacity = 1000
a3.channels.c2.transactionCapacity = 100
# Bind the source and sink to the channel
a3.sources.r1.channels = c2
a3.sinks.k1.channel = c2

执行配置文件
分别开启对应配置文件：flume-flume-console2，flume-flume-console1，flume-netcat-flume。

 bin/flume-ng agent --conf conf/ --name a3 --conf-file job/group2/flume-flume-console2.conf -Dflume.root.logger=INFO,console
 bin/flume-ng agent --conf conf/ --name a2 --conf-file job/group2/flume-flume-console1.conf -Dflume.root.logger=INFO,console
 bin/flume-ng agent --conf conf/ --name a1 --conf-file job/group2/flume-netcat-flume.conf

使用 netcat 工具向本机的 44444 端口发送内容
```
 nc localhost 44444
```
查看 Flume2 及 Flume3 的控制台打印日志
将 Flume2 kill，观察 Flume3 的控制台打印情况。

注：使用 jps -ml 查看 Flume 进程。

3. 聚合

3.1 案例需求

hadoop102上的Flume-1监控文件/opt/module/group.log，hadoop103上的Flume-2 监控某一个端口的数据流，Flume-1与Flume-2 将数据发送给hadoop104上的 Flume-3，Flume-3将最终数据打印到控制台。

3.2 需求分析

多数据源汇总案例
在这里插入图片描述

3.3 实现步骤

准备工作
分发 Flume；
在 hadoop102、hadoop103 以及 hadoop104 的/opt/module/flume/job 目录下创建一个group3 文件夹。

创建 flume1-logger-flume.conf
配置 Source 用于监控 hive.log 文件，配置 Sink 输出数据到下一级 Flume。在 hadoop102 上编辑配置文件。

# 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 /opt/module/group.log
a1.sources.r1.shell = /bin/bash -c
# Describe the sink
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = hadoop104
a1.sinks.k1.port = 4141
# Describe the channel
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

创建 flume2-netcat-flume.conf
配置 Source 监控端口 44444 数据流，配置 Sink 数据到下一级 Flume，在 hadoop103 上编辑配置文件。

# Name the components on this agent
a2.sources = r1
a2.sinks = k1
a2.channels = c1
# Describe/configure the source
a2.sources.r1.type = netcat
a2.sources.r1.bind = hadoop103
a2.sources.r1.port = 44444
# Describe the sink
a2.sinks.k1.type = avro
a2.sinks.k1.hostname = hadoop104
a2.sinks.k1.port = 4141
# Use a channel which buffers events in memory
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

创建 flume3-flume-logger.conf
配置 source 用于接收 flume1 与 flume2 发送过来的数据流，最终合并后 sink 到控制
台。

# 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 = hadoop104
a3.sources.r1.port = 4141
# Describe the sink
# Describe the sink
a3.sinks.k1.type = logger
# 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

执行配置文件
分别开启对应配置文件：flume3-flume-logger.conf，flume2-netcat-flume.conf，flume1-logger-flume.conf。

 bin/flume-ng agent --conf conf/ --name a3 --conf-file job/group3/flume3-flume-logger.conf -Dflume.root.logger=INFO,console
 bin/flume-ng agent --conf conf/ --name a2 --conf-file job/group3/flume1-logger-flume.conf
 bin/flume-ng agent --conf conf/ --name a1 --conf-file job/group3/flume2-netcat-flume.conf