本文主要目的在于将Storm运行环境集成到docker容器中，在一个快速开发模式下运行测试。代码内容来自 Storm Blueprints: Patterns for Distributed Real-time Computation 第四章。
本代码仅供学习。这个样例程序主要是分析日志文件，一旦符合某个threshold，将通过XMPP告警。
- 将日志信息写到Apache Kafka；
- Storm流处理streaming功能负责分析日志；
- 实现移动平均线式的分析；
- Storm将告警信息使用XMPP协议通知给管理员。
##下载源码 git clone https://github.com/jiekechoo/log-analysis-kafka-storm-docker.git
- kafka-log-appender：将日志内容写到kafka程序
- log-kafka-storm：docker-compose脚本和storm程序 ##准备docker环境 ###启动docker docker-compose环境搭建过程请查看我的另一篇博客:CentOS 6 install docker and docker-compose
进入log-kafka-storm目录，查看docker-compose.yml文件，假设我们的宿主主机是：192.168.1.231，如有需要改成你自己的主机地址，代码里所有的地方都要把地址改一下。
[root@docker2 log-kafka-storm]# more docker-compose.yml
zookeeper:
image: jplock/zookeeper
ports:
- "2181:2181"
nimbus:
image: wurstmeister/storm-nimbus:0.9.2
ports:
- "3773:3773"
- "3772:3772"
- "6627:6627"
links:
- zookeeper:zk
- kafka:kafka
supervisor:
image: wurstmeister/storm-supervisor:0.9.2
ports:
- "8000:8000"
links:
- nimbus:nimbus
- zookeeper:zk
- kafka:kafka
ui:
image: wurstmeister/storm-ui:0.9.2
ports:
- "8080:8080"
links:
- nimbus:nimbus
- zookeeper:zk
kafka:
image: wurstmeister/kafka:0.8.1
ports:
- "9092:9092"
links:
- zookeeper:zk
environment:
BROKER_ID: 1
HOST_IP: 192.168.1.231
PORT: 9092
volumes:
- /var/run/docker.sock:/var/run/docker.sock
openfire:
image: mdouglas/openfire
ports:
- "5222:5222"
- "5223:5223"
- "9091:9091"
- "9090:9090"
启动docker-compose
[root@docker2 log-kafka-storm]# docker-compose up -d
Creating logkafkastorm_zookeeper_1...
Creating logkafkastorm_openfire_1...
Creating logkafkastorm_kafka_1...
Creating logkafkastorm_nimbus_1...
Creating logkafkastorm_ui_1...
Creating logkafkastorm_supervisor_1...
启动完成后应该都是 Up 状态
[root@docker2 log-kafka-storm]# docker-compose ps
Name Command State Ports
-----------------------------------------------------------------------------------------------------------------------------
logkafkastorm_kafka_1 /bin/sh -c start-kafka.sh Up 0.0.0.0:9092->9092/tcp
logkafkastorm_nimbus_1 /bin/sh -c /usr/bin/start- Up 0.0.0.0:3772->3772/tcp,
... 0.0.0.0:3773->3773/tcp,
0.0.0.0:6627->6627/tcp
logkafkastorm_openfire_1 /start.sh Up 0.0.0.0:5222->5222/tcp,
0.0.0.0:5223->5223/tcp,
0.0.0.0:9090->9090/tcp,
0.0.0.0:9091->9091/tcp
logkafkastorm_supervisor_1 /bin/sh -c /usr/bin/start- Up 6700/tcp, 6701/tcp, 6702/tcp,
... 6703/tcp,
0.0.0.0:8000->8000/tcp
logkafkastorm_ui_1 /bin/sh -c /usr/bin/start- Up 0.0.0.0:8080->8080/tcp
...
logkafkastorm_zookeeper_1 /opt/zookeeper-3.4.5/bin/z Up 0.0.0.0:2181->2181/tcp,
... 2888/tcp, 3888/tcp
打开浏览器查询Storm UI状态，查看 http://192.168.1.231:8080/ 应该看到下面的画面，没有报错就可以了。
至此，docker算是启动完毕。
###配置kafka 运行 start-kafka-shell.sh 脚本，主要是两个工作：
- 1.进入kafka容器；
- 2.创建topic名为 log-analysis
[root@docker2 log-kafka-storm]# ./start-kafka-shell.sh
root@4c7a5d233991:/# $KAFKA_HOME/bin/kafka-topics.sh --create --topic log-analysis --partitions 1 --zookeeper zk --replication-factor 1
Created topic "log-analysis".
查看kafka的topic是否创建成功
root@4c7a5d233991:/# $KAFKA_HOME/bin/kafka-topics.sh --describe --zookeeper zk
Topic:log-analysis PartitionCount:1 ReplicationFactor:1 Configs:
Topic: log-analysis Partition: 0 Leader: 9092 Replicas: 9092 Isr: 9092
###配置Openfire
浏览器打开 http://192.168.1.231:9090/ ，首先是初始化，域使用你自己的，我们这里是 sectong.com 。删除 服务器证书，否则android和ios客户端登录不上。
- 用户名 storm 密码 storm ，用于发送消息；
- 用户名 alarm 密码 alarm ，用户接收消息；
下载一个windows版本的IM客户端，Spark windows版本安装后如下图所示：
#编译程序 ##Storm运行程序 编译Storm程序
[root@docker2 log-kafka-storm]# mvn clean package
...此处省略过程
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 16.359 s
[INFO] Finished at: 2015-09-25T23:53:29+08:00
[INFO] Final Memory: 31M/373M
[INFO] ------------------------------------------------------------------------
[root@docker2 log-kafka-storm]# ll target/
total 20M
drwxr-xr-x+ 1 ppl None 0 Sep 25 23:53 archive-tmp/
drwxr-xr-x+ 1 ppl None 0 Sep 25 23:53 classes/
drwxr-xr-x+ 1 ppl None 0 Sep 25 23:53 generated-sources/
-rwxr-xr-x 1 ppl None 20M Sep 25 23:53 log-kafka-storm-1.0-SNAPSHOT-jar-with-dependencies.jar
-rwxr-xr-x 1 ppl None 17K Sep 25 23:53 log-kafka-storm-1.0-SNAPSHOT.jar
drwxr-xr-x+ 1 ppl None 0 Sep 25 23:53 maven-archiver/
上传至Storm集群
[root@docker2 log-kafka-storm]# storm jar ./target/log-kafka-storm-1.0-SNAPSHOT-jar-with-dependencies.jar com.log.kafka.storm.topology.LogAnalysisTopology 192.168.1.231 log-analysis-topology
...省略
36971 [main] INFO backtype.storm.StormSubmitter - Submitting topology log-analysis-topology in distributed mode with conf {"storm.xmpp.server":"192.168.1.231","nimbus.host":"192.168.1.231","storm.xmpp.password":"storm","topology.workers":3,"storm.zookeeper.port":2181,"storm.xmpp.user":"storm","storm.xmpp.to":"[email protected]","nimbus.thrift.port":6627,"storm.zookeeper.servers":["192.168.1.231"],"topology.max.spout.pending":5,"topology.trident.batch.emit.interval.millis":2000}
37663 [main] INFO backtype.storm.StormSubmitter - Finished submitting topology: log-analysis-topology
jar包上传完毕，Storm UI 应该增加一个 Topology
到这里，Storm程序已经上传完毕。
##日志写入kafka程序
进入 kafka-log-appender 目录，编译程序
[root@docker2 kafka-log-appender]# mvn clean package
...省略
[INFO] ------------------------------------------------------------------------
[INFO] BUILD SUCCESS
[INFO] ------------------------------------------------------------------------
[INFO] Total time: 3.287 s
[INFO] Finished at: 2015-09-26T00:13:35+08:00
[INFO] Final Memory: 20M/180M
[INFO] ------------------------------------------------------------------------
[root@docker2 kafka-log-appender]# ll target/
total 8.0K
drwxr-xr-x+ 1 ppl None 0 Sep 26 00:13 classes/
-rwxr-xr-x 1 ppl None 7.0K Sep 26 00:13 kafka-log-appender-1.0-SNAPSHOT.jar
drwxr-xr-x+ 1 ppl None 0 Sep 26 00:13 maven-archiver/
drwxr-xr-x+ 1 ppl None 0 Sep 26 00:13 maven-status/
运行jar包程序，向kafka发送日志内容。这里需要注意：运行此jar包的主机需要得到kafka容器的主机名和ip，写入hosts文件。
[root@docker2 kafka-log-appender]# java -cp target/kafka-log-appender-1.0-SNAPSHOT.jar com.log.kafka.RogueApplication
913 [main] INFO kafka.client.ClientUtils$ - Fetching metadata from broker id:0,host:192.168.1.231,port:9092 with correlation id 0 for 1 topic(s) Set(log-analysis)
931 [main] INFO kafka.producer.SyncProducer - Connected to 192.168.1.231:9092 for producing
989 [main] INFO kafka.producer.SyncProducer - Disconnecting from 192.168.1.231:9092
1053 [main] INFO kafka.producer.SyncProducer - Connected to c470c1bea851:9092 for producing
796 [main] WARN com.log.kafka.RogueApplication - This is a warning (slow state).
1566 [main] WARN com.log.kafka.RogueApplication - This is a warning (slow state).
2069 [main] WARN com.log.kafka.RogueApplication - This is a warning (slow state).
2572 [main] WARN com.log.kafka.RogueApplication - This is a warning (slow state).
3074 [main] WARN com.log.kafka.RogueApplication - This is a warning (slow state).
3578 [main] WARN com.log.kafka.RogueApplication - This is a warning (slow state).
4080 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
4183 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
4286 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
4389 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
4494 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
4598 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
4702 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
4806 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
4912 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
5018 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
5137 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
5240 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
5343 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
5446 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
5550 [main] WARN com.log.kafka.RogueApplication - This is a warning (rapid state).
5653 [main] WARN com.log.kafka.RogueApplication - This is a warning (slow state).
6157 [main] WARN com.log.kafka.RogueApplication - This is a warning (slow state).
6660 [main] WARN com.log.kafka.RogueApplication - This is a warning (slow state).
7162 [main] WARN com.log.kafka.RogueApplication - This is a warning (slow state).
7664 [main] WARN com.log.kafka.RogueApplication - This is a warning (slow state).
8166 [main] WARN com.log.kafka.RogueApplication - This is a warning (slow state).
发送成功后，Storm UI 相应数字增加，证明已经运行成功
Spark IM 客户端也会收到相应的告警信息
Android手机下载 Xabber客户端，iOS下载Monal IM，登录IM，可以实时收到推送告警消息
谢谢观赏！
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