官网
安装
1、上传
2、解压
3、修改conf/flume-env.sh 文件中的JDK目录
注意：JAVA_OPTS 配置 如果我们传输文件过大 报内存溢出时 需要修改这个配置项
4、验证安装是否成功 ./flume-ng version
5、配置环境变量
export FLUME_HOME=/home/apache-flume-1.6.0-bin
Source、Channel、Sink有哪些类型
更多类型看官网或者https://blog.csdn.net/qq_45710900/article/details/102294408
Flume Source Source类型 | 说明 Avro Source | 支持Avro协议（实际上是Avro RPC），内置支持 Thrift Source | 支持Thrift协议，内置支持 Exec Source | 基于Unix的command在标准输出上生产数据 JMS Source | 从JMS系统（消息、主题）中读取数据 Spooling Directory Source | 监控指定目录内数据变更 Twitter 1% firehose Source| 通过API持续下载Twitter数据，试验性质 Netcat Source | 监控某个端口，将流经端口的每一个文本行数据作为Event输入 Sequence Generator Source | 序列生成器数据源，生产序列数据 Syslog Sources | 读取syslog数据，产生Event，支持UDP和TCP两种协议 HTTP Source | 基于HTTP POST或GET方式的数据源，支持JSON、BLOB表示形式 Legacy Sources | 兼容老的Flume OG中Source（0.9.x版本） Flume Channel Channel类型 说明 Memory Channel | Event数据存储在内存中 JDBC Channel | Event数据存储在持久化存储中，当前Flume Channel内置支持Derby File Channel | Event数据存储在磁盘文件中 Spillable Memory Channel | Event数据存储在内存中和磁盘上，当内存队列满了，会持久化到磁盘文件 Pseudo Transaction Channel | 测试用途 Custom Channel | 自定义Channel实现 Flume Sink Sink类型 说明 HDFS Sink | 数据写入HDFS Logger Sink | 数据写入日志文件 Avro Sink | 数据被转换成Avro Event，然后发送到配置的RPC端口上 Thrift Sink | 数据被转换成Thrift Event，然后发送到配置的RPC端口上 IRC Sink | 数据在IRC上进行回放 File Roll Sink | 存储数据到本地文件系统 Null Sink | 丢弃到所有数据 HBase Sink | 数据写入HBase数据库 Morphline Solr Sink | 数据发送到Solr搜索服务器（集群） ElasticSearch Sink | 数据发送到Elastic Search搜索服务器（集群） Kite Dataset Sink | 写数据到Kite Dataset，试验性质的 Custom Sink | 自定义Sink实现
案例1、netcat source - 简单的单个agent
http://flume.apache.org/FlumeUserGuide.html#a-simple-example
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 = 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 ############################################################ 启动flume flume-ng agent -n a1 -c conf -f simple.conf -Dflume.root.logger=INFO,console 安装telnet yum install telnet 退出 ctrl+] quit Memory Chanel 配置 capacity：默认该通道中最大的可以存储的event数量是100， trasactionCapacity：每次最大可以source中拿到或者送到sink中的event数量也是100 keep-alive：event添加到通道中或者移出的允许时间 byte**：即event的字节量的限制，只包括eventbody
案例2、netcat source - 两个flume做集群
node01服务器中，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 = netcat a1.sources.r1.bind = node1 a1.sources.r1.port = 44444 # Describe the sink # a1.sinks.k1.type = logger a1.sinks.k1.type = avro a1.sinks.k1.hostname = node2 a1.sinks.k1.port = 60000 # 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 ############################################################ node02服务器中，安装Flume（步骤略） 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 = avro a1.sources.r1.bind = node2 a1.sources.r1.port = 60000 # 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 ############################################################ 先启动node02的Flume flume-ng agent -n a1 -c conf -f avro.conf -Dflume.root.logger=INFO,console 再启动node01的Flume flume-ng agent -n a1 -c conf -f simple.conf2 -Dflume.root.logger=INFO,console 打开telnet 测试 node02控制台输出结果
案例3、Exec Source
http://flume.apache.org/FlumeUserGuide.html#exec-source
配置文件 ############################################################ a1.sources = r1 a1.sinks = k1 a1.channels = c1 # Describe/configure the source a1.sources.r1.type = exec a1.sources.r1.command = tail -F /home/flume.exec.log # 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 ############################################################ 启动Flume flume-ng agent -n a1 -c conf -f exec.conf -Dflume.root.logger=INFO,console 创建空文件演示 touch flume.exec.log 循环添加数据 for i in {1..50}; do echo "$i hi flume" >> flume.exec.log ; sleep 0.1; done
案例4、Spooling Directory Source
http://flume.apache.org/FlumeUserGuide.html#spooling-directory-source
配置文件 ############################################################ a1.sources = r1 a1.sinks = k1 a1.channels = c1 # Describe/configure the source a1.sources.r1.type = spooldir a1.sources.r1.spoolDir = /home/logs 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 = 1000 a1.channels.c1.transactionCapacity = 100 # Bind the source and sink to the channel a1.sources.r1.channels = c1 a1.sinks.k1.channel = c1 ############################################################ 启动Flume flume-ng agent -n a1 -c conf -f spool.conf -Dflume.root.logger=INFO,console 拷贝文件演示 mkdir logs cp flume.exec.log logs/
案例5、hdfs sink
http://flume.apache.org/FlumeUserGuide.html#hdfs-sink
配置文件 ############################################################ a1.sources = r1 a1.sinks = k1 a1.channels = c1 # Describe/configure the source a1.sources.r1.type = spooldir a1.sources.r1.spoolDir = /home/logs a1.sources.r1.fileHeader = true # Describe the sink ***只修改上一个spool sink的配置代码块 a1.sinks.k1.type = logger a1.sinks.k1.type=hdfs a1.sinks.k1.hdfs.path=hdfs://sxt/flume/%Y-%m-%d/%H%M ##每隔60s或者文件大小超过10M的时候产生新文件 # hdfs有多少条消息时新建文件，0不基于消息个数 a1.sinks.k1.hdfs.rollCount=0 # hdfs创建多长时间新建文件，0不基于时间 a1.sinks.k1.hdfs.rollInterval=60 # hdfs多大时新建文件，0不基于文件大小 a1.sinks.k1.hdfs.rollSize=10240 # 当目前被打开的临时文件在该参数指定的时间（秒）内，没有任何数据写入，则将该临时文件关闭并重命名成目标文件 # 如果设置过小会造成很多小文件，再大数据中，小文件是一定要规避掉的。如果不设置，则会造成文件打开描述符占用过多甚至资源耗尽，自己权衡即可 a1.sinks.k1.hdfs.idleTimeout=3 a1.sinks.k1.hdfs.fileType=DataStream a1.sinks.k1.hdfs.useLocalTimeStamp=true ## 每五分钟生成一个目录: # 是否启用时间上的”舍弃”，这里的”舍弃”，类似于”四舍五入”，后面再介绍。如果启用，则会影响除了%t的其他所有时间表达式 a1.sinks.k1.hdfs.round=true # 时间上进行“舍弃”的值； a1.sinks.k1.hdfs.roundValue=5 # 时间上进行”舍弃”的单位，包含：second,minute,hour a1.sinks.k1.hdfs.roundUnit=minute # 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 ############################################################ 创建HDFS目录 hadoop fs -mkdir /flume 启动Flume flume-ng agent -n a1 -c conf -f hdfs.conf -Dflume.root.logger=INFO,console 查看hdfs文件 hadoop fs -ls /flume/... hadoop fs -get /flume/...
