Apache Flume入门指南[翻译自官方文档]

2023-03-14 08:20:54

声明: 根据官方文档选择性的翻译了下,不对请指正 https://flume.apache.org/FlumeUserGuide.html

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" alt="" name="en-media:image/png:e6a6997ee4f65eae8b7005da3baef737:none:none" />
术语介绍
组件 说明
Agent 一个flume的jvm实例
Client 消息生产者
Source 从client接收数据,传递给channel
Sink 从channel接收数据发送到目的端
Channel 是source和sink的桥梁,类似队列
Events 可以是日志记录、 avro 对象等
启动方法:
$ bin/flume-ng agent -n $agent_name -c conf -f conf/flume-conf.properties.template
 
配置文件示例:
# example.conf: A single-node Flume configuration

# 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:
$ bin/flume-ng agent --conf conf --conf-file example.conf --name a1 -Dflume.root.logger=INFO,console
生产环境配置 --conf=conf_dir,那么conf_dir目录中应该有下面两个文件
  • flume-env.sh
  • log4j.properties
 
记录日志方便debug, 给java传参数
-Dorg.apache.flume.log.printconfig=true
或者在flume-env.sh里设置JAVA_OPTS=-Dorg.apache.flume.log.printconfig=true  日志级别应设置 debug或trace
$ bin/flume-ng agent --conf conf --conf-file example.conf --name a1 -Dflume.root.logger=DEBUG,console -Dorg.apache.flume.log.printconfig=true -Dorg.apache.flume.log.rawdata=true
 
flume也支持配置放在zookeeper中(实验性质)
 
第三方插件
flume-env.sh   配置FLUME_CLASSPATH  或者 放在plugins.d
 
多agent模式之间必须使用avro类型
flume还支持多路复用,即一份数据可以复制多份传给多个sink
配置文件
注意: 一个source可以有多个channle, 但是一个sink只能有一个channle,如下所示
# list the sources, sinks and channels for the agent

<Agent>.sources = <Source>

<Agent>.sinks = <Sink>

<Agent>.channels = <Channel1> <Channel2>

# set channel for source

<Agent>.sources.<Source>.channels = <Channel1> <Channel2> ...

# set channel for sink

<Agent>.sinks.<Sink>.channel = <Channel1>

　　

有两种模式可以支持扇出:  复制技术和 多路技术
  • 复制: event发送给所有的channel
  • 多路: 选择性的发送给channel
 
如果要使用多路技术,需要单独定义一个selector
<Agent>.sources.<Source1>.selector.type = replicating  这是默认的replicating
 
下面是多路的定义方法:
# Mapping for multiplexing selector

<Agent>.sources.<Source1>.selector.type = multiplexing

<Agent>.sources.<Source1>.selector.header = <someHeader>

<Agent>.sources.<Source1>.selector.mapping.<Value1> = <Channel1>

<Agent>.sources.<Source1>.selector.mapping.<Value2> = <Channel1> <Channel2>

<Agent>.sources.<Source1>.selector.mapping.<Value3> = <Channel2>

#...

<Agent>.sources.<Source1>.selector.default = <Channel2>  定义一个默认值 如果什么都不匹配则使用这个default
 
来个具体例子:
# list the sources, sinks and channels in the agent

agent_foo.sources = avro-AppSrv-source1

agent_foo.sinks = hdfs-Cluster1-sink1 avro-forward-sink2

agent_foo.channels = mem-channel-1 file-channel-2

# set channels for source

agent_foo.sources.avro-AppSrv-source1.channels = mem-channel-1 file-channel-2

# set channel for sinks

agent_foo.sinks.hdfs-Cluster1-sink1.channel = mem-channel-1

agent_foo.sinks.avro-forward-sink2.channel = file-channel-2

# channel selector configuration

agent_foo.sources.avro-AppSrv-source1.selector.type = multiplexing

agent_foo.sources.avro-AppSrv-source1.selector.header = State

agent_foo.sources.avro-AppSrv-source1.selector.mapping.CA = mem-channel-1

agent_foo.sources.avro-AppSrv-source1.selector.mapping.AZ = file-channel-2

agent_foo.sources.avro-AppSrv-source1.selector.mapping.NY = mem-channel-1 file-channel-2

agent_foo.sources.avro-AppSrv-source1.selector.default = mem-channel-1

还有一个optional的例子

agent_foo.sources.avro-AppSrv-source1.selector.optional.CA = mem-channel-1 file-channel-2

　　

当所有的channel都消费完成,selector会尝试往optional也写一份, optional channel写入失败会忽略错误不会重试
 
如何header配置的channel既是required又是optional的 那么这个channel被认为是required, 任何一个channel失败都会导致整个channel集合失败,就像上面的CA,任何一个channel失败都认为 CA失败了
如果一个header没有设置任何channel,那么event会写到default channel,也会往optional写一份. 既是指定了写入optional channel但仍然会往default写. 如果连default也没指定那么event只能写optional channel,写入失败也只是简单的忽略.
Flume source
  1. avro source
    下面是配置参数,粗体是必选
Property Name Default Description
channels –  
type – The component type name, needs to be avro
bind – hostname or IP address to listen on
port – Port # to bind to
threads – Maximum number of worker threads to spawn
selector.type    
selector.*    
interceptors – Space-separated list of interceptors
interceptors.*    
compression-type none This can be “none” or “deflate”. The compression-type must match the compression-type of matching AvroSource
ssl false Set this to true to enable SSL encryption. You must also specify a “keystore” and a “keystore-password”.
keystore – This is the path to a Java keystore file. Required for SSL.
keystore-password – The password for the Java keystore. Required for SSL.
keystore-type JKS The type of the Java keystore. This can be “JKS” or “PKCS12”.
exclude-protocols SSLv3 Space-separated list of SSL/TLS protocols to exclude. SSLv3 will always be excluded in addition to the protocols specified.
ipFilter false Set this to true to enable ipFiltering for netty
ipFilterRules – Define N netty ipFilter pattern rules with this config.
 
ipFilterRules例子如下:
allow:name:localhost,deny:ip:
ipFilterRules=allow:ip:127.*,allow:name:localhost,deny:ip:*    允许本机,禁止其他ip allow:name:localhost,deny:ip:
deny:name:localhost,allow:ip:   禁止本机,允许其他
 
  1. Thrift source
    Thrift source通过kerberos可以配置加密模式
    需要设置这两个参数: agent-principal   agent-keytab
  2. Exec source ( 不推荐使用)
    运行unix命令输出到标准输出(如果没有配置logStdErr=true那么错误会被抛弃)
… 太多source了  有兴趣的自己看吧
Flume sinks
支持的sink也很多这里只列举一下吧
    • HDFS
    • HIVE
    • Logger 日志级别是INFO, 这个sink大都用来测试和调试
    • Avro
    • Thrift 也支持kerberos加密
    • IRC
    • File Roll
    • Null  丢弃收到的消息
    • HBase
    • AsyncHBase  异步模式
    • MorphlineSolr
    • ElasticSearch
    • Kite Dataset
    • Kafka
Flume channel
channel就是在agent端存储event的, source发送过来event,sink去消费
支持的channel如下
    • memory
    • JDBC  用户持久化存储到数据库, 支持内置的Derby
    • Kafka
    • File
    • Spillable memory
      大体解释下这个channel, 有一个内存的队列和一个文件的channle组成,数据先在queue中存,存不下了就往file channle写,这个channel的想法是在正常情况下的高吞吐就是内存的队列, file channel就是应对突然来了很大的数据量或者agent突然挂了,那么数据还能从file恢复
      重点来了: 实验性质,不推荐在生产环境使用
    • Pseudo Transaction  用来做单元测试,不推荐生产环境
Flume channle selector
前面说过了,默认的selector是复制模式,而不是多路模式
来一个多路模式的配置文件 
a1.sources = r1

a1.channels = c1 c2 c3 c4

a1.sources.r1.selector.type = multiplexing  这里注意

a1.sources.r1.selector.header = state

a1.sources.r1.selector.mapping.CZ = c1

a1.sources.r1.selector.mapping.US = c2 c3

a1.sources.r1.selector.default = c4

　　

Flume sink processors
可以给sink分组,实现负载均衡或者容错
Property Name Default Description
sinks – Space-separated list of sinks that are participating in the group
processor.type default The component type name, needs to be default, failover or load_balance
Example for agent named a1:
 
a1.sinkgroups = g1

a1.sinkgroups.g1.sinks = k1 k2

a1.sinkgroups.g1.processor.type = load_balance
 
有三种类型的processor: default, failover, load_balance
 
    1. 这篇文档中配置的source-channel-sink就是default模式,什么都不用配置
    2. failover
      给多个sink配置优先级,保证至少有一个sink是可用的,优先级的数字越大优先级越高
      这些sink被放到一个池子pool里,发送event失败的sink会被暂时移除pool,并被冷却30s(默认),后续的event由次高优先级的sink处理,如果没有设置优先级那么按照配置文件中的次序
    3. load balance
      有两个负载均衡的策略: 轮训(round_robin默认), 随机(random)
      如果有一个sink发送失败,processor会选择下一个sink,如果你没有设置backoff,它也不会被从可用sink中移除,如果所有的sink都失败了,那么这个信息就传递给调用者
Event serializer
file_roll和hdfs sink都支持eventSerializer
    1. Body text serializer
      就是普通的文本,event的header会被忽略
    2. "Flume event" Avro Event serializer
    3. Avro event serializer
Flume interceptor
flume可以使用拦截器修改和丢弃event,支持链式拦截器,多个拦截器用空格分隔 
a1.sources = r1

a1.sinks = k1

a1.channels = c1

a1.sources.r1.interceptors = i1 i2

a1.sources.r1.interceptors.i1.type = org.apache.flume.interceptor.HostInterceptor$Builder

a1.sources.r1.interceptors.i1.preserveExisting = false

a1.sources.r1.interceptors.i1.hostHeader = hostname

a1.sources.r1.interceptors.i2.type = org.apache.flume.interceptor.TimestampInterceptor$Builder

a1.sinks.k1.filePrefix = FlumeData.%{CollectorHost}.%Y-%m-%d

a1.sinks.k1.channel = c1 
  1. Timestamp   在header中添加一个timestamp的key 显示处理event的时间
  2. Host  在header中添加host     保存agent的ip地址
  3. Static 用户可以自定义一个key,一次只能添加一个key,如果要添加多个可以使用多个interceptor拦截器
  4. UUID  生成一个128位的值
  5. Morphline
  6. search and replace  基于java的正则表达式   java matcher.replaceAll
  7. regex filter
  8. regex extractor 把正则分组中的匹配放到header中
flume properties
flume.called.from.service 每30s flume会重新载入配置文件.
如果你这是了这个参数 -Dflume.called.from.service
当agent第一次读取配置文件并且这个文件不存在时,恰巧你设置了上面的参数,那么agent不会报错,并会继续等待30s重载配置文件
如果你没设置上面的参数,那么agent立即退出
当agent到了30s重载配置文件, 而这不是第一次载入这个文件,那么agent不会退出,而是认为配置文件没有变化继续使用旧的配置
Json Reporting
flume可以启动一个内置的http server以json的形式报告各种指标
$ bin/flume-ng agent --conf-file example.conf --name a1 -Dflume.monitoring.type=http -Dflume.monitoring.port=34545
 
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