一、單一代理流配置
1.1 官網介紹
http://flume.apache.org/FlumeUserGuide.html#avro-source
通過一個通道將來源和接收器鏈接。需要列出源,接收器和通道,爲給定的代理,然後指向源和接收器及通道。一個源的實例可以指定多個通道,但只能指定一個接收器實例。格式如下:
# 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>
實例解析:一個代理名爲agent_foo,外部通過avro客戶端,並且發送數據通過內存通道給hdfs。在配置文件foo.config的可能看起來像這樣:
# list the sources, sinks and channels for the agent
agent_foo.sources = avro-appserver-src-1
agent_foo.sinks = hdfs-sink-1
agent_foo.channels = mem-channel-1
# set channel for source
agent_foo.sources.avro-appserver-src-1.channels = mem-channel-1
# set channel for sink
agent_foo.sinks.hdfs-sink-1.channel = mem-channel-1
案例說明:這將使事件流從avro-appserver-src-1到hdfs-sink-1通過內存通道mem-channel-1。當代理開始foo.config作爲其配置文件,它會實例化流。
配置單個組件
定義流之後,需要設置每個源,接收器和通道的屬性。可以分別設定組件的屬性值。
# properties for sources
<Agent>.sources.<Source>.<someProperty> = <someValue>
# properties for channels
<Agent>.channel.<Channel>.<someProperty> = <someValue>
# properties for sinks
<Agent>.sources.<Sink>.<someProperty> = <someValue>
“type”屬性必須爲每個組件設置,以瞭解它需要什麼樣的對象。每個源,接收器和通道類型有其自己的一套,它所需的性能,以實現預期的功能。所有這些,必須根據需要設置。在前面的例子中,從hdfs-sink-1中的流到HDFS,通過內存通道mem-channel-1的avro-appserver-src-1源。下面是 一個例子,顯示了這些組件的配置。
agent_foo.sources = avro-AppSrv-source
agent_foo.sinks = hdfs-Cluster1-sink
agent_foo.channels = mem-channel-1
# set channel for sources, sinks
# properties of avro-AppSrv-source
agent_foo.sources.avro-AppSrv-source.type = avro
agent_foo.sources.avro-AppSrv-source.bind = localhost
agent_foo.sources.avro-AppSrv-source.port = 10000
# properties of mem-channel-1
agent_foo.channels.mem-channel-1.type = memory
agent_foo.channels.mem-channel-1.capacity = 1000
agent_foo.channels.mem-channel-1.transactionCapacity = 100
# properties of hdfs-Cluster1-sink
agent_foo.sinks.hdfs-Cluster1-sink.type = hdfs
agent_foo.sinks.hdfs-Cluster1-sink.hdfs.path = hdfs://namenode/flume/webdata
#...
1.2 測試示例(一)
通過flume來監控一個目錄,當目錄中有新文件時,將文件內容輸出到控制檯。
創建一個test01.conf的文件:
#配置一個agent,agent的名稱可以自定義(如a1)
#指定agent的sources(如s1)、sinks(如k1)、channels(如c1)
#分別指定agent的sources,sinks,channels的名稱 名稱可以自定義
a1.sources = s1
a1.sinks = k1
a1.channels = c1
#描述source
#配置目錄scource
a1.sources.s1.type = spooldir
a1.sources.s1.spoolDir = /opt/flume/logs
a1.sources.s1.fileHeader= true
a1.sources.s1.channels =c1
#配置sink
a1.sinks.k1.type = logger
a1.sinks.k1.channel = c1
#配置channel(內存做緩存)
a1.channels.c1.type = memory
啓動命令
./bin/flume-ng agent --conf conf --conf-file ./conf/test1.conf --name a1 -Dflume.root.logger=INFO,console
測試 Flume
重新打開一個終端,我們將123.log移動到logs目錄
$ cp test.log logs/
原始的Flume終端將在日誌消息中輸出事件:
2018-11-03 03:54:54,207 (pool-3-thread-1) [INFO - org.apache.flume.client.avro.ReliableSpoolingFileEventReader.readEvents(ReliableSpoolingFileEventReader.java:324)] Last read took us just up to a file boundary. Rolling to the next file, if there is one.
2018-11-03 03:54:54,207 (pool-3-thread-1) [INFO - org.apache.flume.client.avro.ReliableSpoolingFileEventReader.rollCurrentFile(ReliableSpoolingFileEventReader.java:433)] Preparing to move file /opt/flume/logs/test.log to /opt/flume/logs/test.log.COMPLETED
2.6 NetCat Source
1.3 測試案例(二)
案例2:實時模擬從web服務器中讀取數據到hdfs中
此處使用 exec source 詳細參考 上一節裏面的 2.3 Exec Source 介紹
二、單代理多流配置
單個Flume代理可以包含幾個獨立的流。你可以在一個配置文件中列出多個源,接收器和通道。這些組件可以連接形成多個流。
# 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>
可以連接源和接收器到其相應的通道,設置兩個不同的流。例如,如果需要設置一個agent_foo代理兩個流,一個從外部Avro客戶端到HDFS,另外一個是tail的輸出到Avro接收器,然後在這裏是做一個配置。
2.1 官方案例
# list the sources, sinks and channels in the agent
agent_foo.sources = avro-AppSrv-source1 exec-tail-source2
agent_foo.sinks = hdfs-Cluster1-sink1 avro-forward-sink2
agent_foo.channels = mem-channel-1 file-channel-2
# flow #1 configuration
agent_foo.sources.avro-AppSrv-source1.channels = mem-channel-1
agent_foo.sinks.hdfs-Cluster1-sink1.channel = mem-channel-1
# flow #2 configuration
agent_foo.sources.exec-tail-source2.channels = file-channel-2
agent_foo.sinks.avro-forward-sink2.channel = file-channel-2
三、配置多代理流程
設置一個多層的流,需要有一個指向下一跳avro源的第一跳的avro 接收器。這將導致第一Flume代理轉發事件到下一個Flume代理。例如,如果定期發送的文件,每個事件(1文件)AVRO客戶端使用本地Flume 代理,那麼這個當地的代理可以轉發到另一個有存儲的代理。
配置如下:
3.1 官方案例
Weblog agent config:
# list sources, sinks and channels in the agent
agent_foo.sources = avro-AppSrv-source
agent_foo.sinks = avro-forward-sink
agent_foo.channels = file-channel
# define the flow
agent_foo.sources.avro-AppSrv-source.channels = file-channel
agent_foo.sinks.avro-forward-sink.channel = file-channel
# avro sink properties
agent_foo.sinks.avro-forward-sink.type = avro
agent_foo.sinks.avro-forward-sink.hostname = 10.1.1.100
agent_foo.sinks.avro-forward-sink.port = 10000
# configure other pieces
#...
HDFS agent config:
# list sources, sinks and channels in the agent
agent_foo.sources = avro-collection-source
agent_foo.sinks = hdfs-sink
agent_foo.channels = mem-channel
# define the flow
agent_foo.sources.avro-collection-source.channels = mem-channel
agent_foo.sinks.hdfs-sink.channel = mem-channel
# avro source properties
agent_foo.sources.avro-collection-source.type = avro
agent_foo.sources.avro-collection-source.bind = 10.1.1.100
agent_foo.sources.avro-collection-source.port = 10000
# configure other pieces
#...
這裏連接從weblog-agent的avro-forward-sink 到hdfs-agent的avro-collection-source收集源。最終結果從外部源的appserver最終存儲在HDFS的事件。
3.2 測試案例
創建一個case_avro.conf的文件:
a1.sources = s1
a1.sinks = k1
a1.channels = c1
a1.sources.s1.type = avro
a1.sources.s1.channels = c1
a1.sources.s1.bind = localhost
a1.sources.s1.port = 22222
a1.channels.c1.type = memory
a1.channels.c1.capacity = 1000
a1.channels.c1.transactionCapacity = 100
a1.sinks.k1.type = logger
a1.sinks.k1.channel = c1
創建一個case_avro_sink.conf的文件:
a2.sources = s1
a2.sinks = k1
a2.channels = c1
a2.sources.s1.type = syslogtcp
a2.sources.s1.channels = c1
a2.sources.s1.host = 192.168.123.102
a2.sources.s1.port = 33333
a2.channels.c1.type = memory
a2.channels.c1.capacity = 1000
a2.channels.c1.transactionCapacity = 100
a2.sinks.k1.type = avro
a2.sinks.k1.hostname = 192.168.123.102
a2.sinks.k1.port = 22222
a2.sinks.k1.channel = c1
說明:case_avro_sink.conf是前面的Agent,case_avro.conf是後面的Agent
先啓動Avro的Source,監聽端口
$ ./bin/flume-ng agent --conf conf --conf-file ./conf/case_avro.conf --name a1 -Dflume.root.logger=DEBUG,console -Dorg.apache.flume.log.printconfig=true -Dorg.apache.flume.log.rawdata=true
再啓動Avro的Sink
$ ./bin/flume-ng agent --conf conf --conf-file ./conf/case_avro_sink.conf --name a2 -Dflume.root.logger=DEBUG,console -Dorg.apache.flume.log.printconfig=true -Dorg.apache.flume.log.rawdata=true
可以看到已經建立連接
在Avro Sink上生成測試log
$ echo "hello flume avro sink" | nc 192.168.1.102 33333
查看結果:
四、多路複用流
Flume支持扇出流從一個源到多個通道。有兩種模式的扇出,複製和複用。在複製流的事件被髮送到所有的配置通道。在複用的情況下,事件被髮送到合格的渠 道只有一個子集。扇出流,需要指定源和扇出通道的規則。這是通過添加一個通道“選擇”,可以複製或複用。再進一步指定選擇的規則,如果它是一個多路。如果你 不指定一個選擇,則默認情況下它複製。
# 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>
複用的選擇集的屬性進一步分叉。這需要指定一個事件屬性映射到一組通道。選擇配置屬性中的每個事件頭檢查。如果指定的值相匹配,那麼該事件被髮送到所有的通道映射到該值。如果沒有匹配,那麼該事件被髮送到設置爲默認配置的通道。
# 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>
映射允許每個值通道可以重疊。默認值可以包含任意數量的通道。下面的示例中有一個單一的流複用兩條路徑。代理有一個單一的avro源和連接道兩個接收器的兩個通道。
4.1 官方案例
# 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
“State”作爲Header的選擇檢查。如果值是“CA”,然後將其發送到mem-channel-1,如果它的“AZ”的,那麼jdbc- channel-2,如果它的“NY”那麼發到這兩個。如果“State”頭未設置或不匹配的任何三個,然後去默認的mem-channel-1通道。
4.2 測試案例(一)複製
case_replicate_sink.conf
a1.sources = s1
a1.sinks = k1 k2
a1.channels = c1 c2
a1.sources.s1.type = syslogtcp
a1.sources.s1.channels = c1 c2
a1.sources.s1.host = 192.168.1.102
a1.sources.s1.port = 6666
a1.sources.s1.selector.type = replicating
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
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = 192.168.1.102
a1.sinks.k1.port = 7777
a1.sinks.k1.channel = c1
a1.sinks.k1.type = avro
a1.sinks.k1.hostname = 192.168.1.102
a1.sinks.k1.port = 7777
a1.sinks.k1.channel = c2
case_replicate_s1.conf
a2.sources = s1
a2.sinks = k1
a2.channels = c1
a2.sources.s1.type = avro
a2.sources.s1.channels = c1
a2.sources.s1.host = 192.168.1.102
a2.sources.s1.port = 7777
a2.channels.c1.type = memory
a2.channels.c1.capacity = 1000
a2.channels.c1.transactionCapacity = 100
a2.sinks.k1.type = logger
a2.sinks.k1.channel = c1
case_replicate_s2.conf
a3.sources = s1
a3.sinks = k1
a3.channels = c1
a3.sources.s1.type = avro
a3.sources.s1.channels = c1
a3.sources.s1.host = 192.168.1.102
a3.sources.s1.port = 7777
a3.channels.c1.type = memory
a3.channels.c1.capacity = 1000
a3.channels.c1.transactionCapacity = 100
a3.sinks.k1.type = logger
a3.sinks.k1.channel = c1
先啓動Avro的Source,監聽端口
$ ./bin/flume-ng agent --conf conf --conf-file ./conf/case_replicate_s1.conf --name a2 -Dflume.root.logger=DEBUG,console -Dorg.apache.flume.log.printconfig=true -Dorg.apache.flume.log.rawdata=true
$ ./bin/flume-ng agent --conf conf --conf-file ./conf/case_replicate_s2.conf --name a3 -Dflume.root.logger=DEBUG,console -Dorg.apache.flume.log.printconfig=true -Dorg.apache.flume.log.rawdata=true
再啓動Avro的Sink
$ ./bin/flume-ng agent --conf conf --conf-file ./confcase_replicate_sink.conf --name a1 -Dflume.root.logger=DEBUG,console -Dorg.apache.flume.log.printconfig=true -Dorg.apache.flume.log.rawdata=true
生成測試log
$ echo "hello via channel selector" | nc 192.168.1.102 6666
4.3 測試案例(二)複用
case_multi_sink.conf
#2個channel和2個sink的配置文件
a1.sources = r1
a1.sinks = k1 k2
a1.channels = c1 c2
# Describe/configure the source
a1.sources.r1.type = org.apache.flume.source.http.HTTPSource
a1.sources.r1.port = 5140
a1.sources.r1.host = 0.0.0.0
a1.sources.r1.selector.type = multiplexing
a1.sources.r1.channels = c1 c2
a1.sources.r1.selector.header = state
a1.sources.r1.selector.mapping.CZ = c1
a1.sources.r1.selector.mapping.US = c2
a1.sources.r1.selector.default = c1
# Describe the sink
a1.sinks.k1.type = avro
a1.sinks.k1.channel = c1
a1.sinks.k1.hostname = 192.168.1.102
a1.sinks.k1.port = 4545
a1.sinks.k2.type = avro
a1.sinks.k2.channel = c2
a1.sinks.k2.hostname = 192.168.1.102
a1.sinks.k2.port = 4545
# Use a channel which buffers events in memory
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
case_ multi _s1.conf
# 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.channels = c1
a2.sources.r1.bind = 192.168.1.102
a2.sources.r1.port = 4545
# Describe the sink
a2.sinks.k1.type = logger
a2.sinks.k1.channel = c1
# Use a channel which buffers events in memory
a2.channels.c1.type = memory
a2.channels.c1.capacity = 1000
a2.channels.c1.transactionCapacity = 100
case_ multi _s2.conf
# 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.channels = c1
a3.sources.r1.bind = 192.168.1.102
a3.sources.r1.port = 4545
# Describe the sink
a3.sinks.k1.type = logger
a3.sinks.k1.channel = c1
# Use a channel which buffers events in memory
a3.channels.c1.type = memory
a3.channels.c1.capacity = 1000
a3.channels.c1.transactionCapacity = 100
先啓動Avro的Source,監聽端口
$ ./bin/flume-ng agent -c . -f ./conf/case_ multi _s1.conf -n a2 -Dflume.root.logger=INFO,console
$ ./bin/flume-ng agent -c . -f ./conf/case_ multi _s2.conf -n a3 -Dflume.root.logger=INFO,console
再啓動Avro的Sink
$ ./bin/lume-ng agent -c . -f ./conf/case_multi_sink.conf -n a1 -Dflume.root.logger=INFO,console
根據配置文件生成測試的header 爲state的POST請求
$ curl -X POST -d '[{ "headers" :{"state" : "CZ"},"body" : "TEST1"}]' http://localhost:5140
$ curl -X POST -d '[{ "headers" :{"state" : "US"},"body" : "TEST2"}]' http://localhost:5140
$ curl -X POST -d '[{ "headers" :{"state" : "SH"},"body" : "TEST3"}]' http://localhost:5140