【Flume学习之二】Flume 使用场景
环境
apache-flume-1.6.0
一、多agent连接
1、node101配置 option2
# 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 = node101 a1.sources.r1.port = 44444 # Describe the sink # a1.sinks.k1.type = logger a1.sinks.k1.type = avro a1.sinks.k1.hostname = node102 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
2、node102配置 option1
############################################################ # 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 = node102 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 ############################################################
3、启动顺序
先启动node102-flume,后启动node101-flume，看一下flume启动顺序就知道,要先创建sink，然后创建channel,最后创建source；然后channel连接sink和channel;最后启动channel、sink、source
[root@node102 conf]# flume-ng agent -c /usr/local/apache-flume-1.6.0-bin/conf -f /usr/local/apache-flume-1.6.0-bin/conf/option1 -n a1 -Dflume.root.logger=INFO,console [root@node101 conf]# flume-ng agent -c /usr/local/apache-flume-1.6.0-bin/conf -f /usr/local/apache-flume-1.6.0-bin/conf/option2 -n a1 -Dflume.root.logger=INFO,console
4、测试：在node101 telnet测试，在node102查看输出日志
node101 telnet:
[root@node101 ~]# telnet node101 44444 Trying 192.168.118.101... Connected to node101. Escape character is '^]'. hello world OK haha wjy OK hi xiaoming OK ^] telnet> quit Connection closed. [root@node101 ~]#
node102 flume日志：
2019-06-29 00:43:46,022 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.LoggerSink.process(LoggerSink.java:94)] Event: { headers:{} body: 68 65 6C 6C 6F 20 77 6F 72 6C 64 0D hello world. } 2019-06-29 00:45:04,365 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.LoggerSink.process(LoggerSink.java:94)] Event: { headers:{} body: 68 61 68 61 20 77 6A 79 0D haha wjy. } 2019-06-29 00:45:13,713 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.LoggerSink.process(LoggerSink.java:94)] Event: { headers:{} body: 68 69 20 78 69 61 6F 6D 69 6E 67 0D hi xiaoming. }
二、Exec Source
Source类型选择Exec
1、配置 option3
############################################################ 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 ############################################################
2、启动
[root@node101 conf]# flume-ng agent -c /usr/local/apache-flume-1.6.0-bin/conf -f /usr/local/apache-flume-1.6.0-bin/conf/option3 -n a1 -Dflume.root.logger=INFO,console
3、测试
[root@node101 home]# echo "wjy" >> flume.exec.log [root@node101 home]# echo "hi" >> flume.exec.log [root@node101 home]# echo "hello wjy" >> flume.exec.log
flume输出：
2019-06-29 01:23:28,237 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.LoggerSink.process(LoggerSink.java:94)] Event: { headers:{} body: 77 6A 79 wjy } 2019-06-29 01:23:43,333 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.LoggerSink.process(LoggerSink.java:94)] Event: { headers:{} body: 68 69 hi } 2019-06-29 01:23:58,652 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.LoggerSink.process(LoggerSink.java:94)] Event: { headers:{} body: 68 65 6C 6C 6F 20 77 6A 79 hello wjy }
三、Spooling Directory Source
监测配置的目录下新增的文件，并将文件中的数据读取出来：
1)拷贝到spool目录下的文件不可以再打开编辑；
2) spool目录下不可包含相应的子目录；
1、配置
############################################################ 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 ############################################################
2、启动
[root@node101 conf]# flume-ng agent -c /usr/local/apache-flume-1.6.0-bin/conf -f /usr/local/apache-flume-1.6.0-bin/conf/option4 -n a1 -Dflume.root.logger=INFO,console
3、测试
日志目录：/home/logs
[root@node101 home]# cat flume.exec.log hello hello hello wjy hi hello wjy [root@node101 home]# mkdir logs && mv flume.exec.log ./logs && cd logs && ls flume.exec.log.COMPLETED
flume输出：
2019-06-29 01:35:28,281 (pool-3-thread-1) [INFO - org.apache.flume.client.avro.ReliableSpoolingFileEventReader.rollCurrentFile(ReliableSpoolingFileEventReader.java:348)] Preparing to move file /home/logs/flume.exec.log to /home/logs/flume.exec.log.COMPLETED 2019-06-29 01:35:28,282 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.LoggerSink.process(LoggerSink.java:94)] Event: { headers:{file=/home/logs/flume.exec.log} body: 68 65 6C 6C 6F hello } 2019-06-29 01:35:28,282 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.LoggerSink.process(LoggerSink.java:94)] Event: { headers:{file=/home/logs/flume.exec.log} body: 68 65 6C 6C 6F hello } 2019-06-29 01:35:28,282 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.LoggerSink.process(LoggerSink.java:94)] Event: { headers:{file=/home/logs/flume.exec.log} body: 68 65 6C 6C 6F hello } 2019-06-29 01:35:28,283 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.LoggerSink.process(LoggerSink.java:94)] Event: { headers:{file=/home/logs/flume.exec.log} body: 77 6A 79 wjy } 2019-06-29 01:35:28,283 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.LoggerSink.process(LoggerSink.java:94)] Event: { headers:{file=/home/logs/flume.exec.log} body: 68 69 hi } 2019-06-29 01:35:28,283 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.LoggerSink.process(LoggerSink.java:94)] Event: { headers:{file=/home/logs/flume.exec.log} body: 68 65 6C 6C 6F 20 77 6A 79 hello wjy }
四、日志输出到HDFS
1、配置
############################################################ 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://node101:8020/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 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
[root@node101 conf]# hdfs dfs -mkdir /flume
2、启动
[root@node101 conf]# flume-ng agent -c /usr/local/apache-flume-1.6.0-bin/conf -f /usr/local/apache-flume-1.6.0-bin/conf/option5 -n a1 -Dflume.root.logger=INFO,console
3、测试
制造测试数据：
[root@node101 home]# echo "hello wjy" >> test.log [root@node101 home]# echo "hello xiaoming" >> test.log [root@node101 home]# echo "hi xiaowang" >> test.log [root@node101 home]# cp test.log ./logs
flume执行日志：
2019-07-01 18:48:18,213 (pool-3-thread-1) [INFO - org.apache.flume.client.avro.ReliableSpoolingFileEventReader.readEvents(ReliableSpoolingFileEventReader.java:258)] Last read took us just up to a file boundary. Rolling to the next file, if there is one. 2019-07-01 18:48:18,213 (pool-3-thread-1) [INFO - org.apache.flume.client.avro.ReliableSpoolingFileEventReader.rollCurrentFile(ReliableSpoolingFileEventReader.java:348)] Preparing to move file /home/logs/test.log to /home/logs/test.log.COMPLETED 2019-07-01 18:48:20,197 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.HDFSDataStream.configure(HDFSDataStream.java:58)] Serializer = TEXT, UseRawLocalFileSystem = false 2019-07-01 18:48:20,522 (SinkRunner-PollingRunner-DefaultSinkProcessor) [INFO - org.apache.flume.sink.hdfs.BucketWriter.open(BucketWriter.java:234)] Creating hdfs://node101:8020/flume/2019-07-01/1845/FlumeData.1561978100198.tmp 2019-07-01 18:48:28,285 (hdfs-k1-roll-timer-0) [INFO - org.apache.flume.sink.hdfs.BucketWriter$5.call(BucketWriter.java:429)] Closing idle bucketWriter hdfs://node101:8020/flume/2019-07-01/1845/FlumeData.1561978100198.tmp at 1561978108285 2019-07-01 18:48:28,286 (hdfs-k1-roll-timer-0) [INFO - org.apache.flume.sink.hdfs.BucketWriter.close(BucketWriter.java:363)] Closing hdfs://node101:8020/flume/2019-07-01/1845/FlumeData.1561978100198.tmp 2019-07-01 18:48:28,331 (hdfs-k1-call-runner-6) [INFO - org.apache.flume.sink.hdfs.BucketWriter$8.call(BucketWriter.java:629)] Renaming hdfs://node101:8020/flume/2019-07-01/1845/FlumeData.1561978100198.tmp to hdfs://node101:8020/flume/2019-07-01/1845/FlumeData.1561978100198 2019-07-01 18:48:28,357 (hdfs-k1-roll-timer-0) [INFO - org.apache.flume.sink.hdfs.HDFSEventSink$1.run(HDFSEventSink.java:394)] Writer callback called.
hdfs文件：
五、其他：
多路日志合并
多路日志输出
学习技术不是用来写HelloWorld和Demo的，而是要用来解决线上系统的真实问题的.
