spark standalone zookeeper HA部署方式
虽然spark master挂掉的几率很低，不过还是被我遇到了一次。以前在spark standalone的文章中也介绍过standalone的ha,现在详细说下部署流程，其实也比较简单。一.机器
zookeeper集群
zk1:2181
zk2:2181
zk3:2181
spark master
spark-m1
spark-m2
spark worker
若干
二.步骤
1.进入spark-m1
修改conf/spark-env.sh
vi spark-env.sh
export SPARK_MASTER_IP=spark-m1
export SPARK_DAEMON_JAVA_OPTS="-Dspark.deploy.recoveryMode=ZOOKEEPER -Dspark.deploy.zookeeper.url=zk1:2181,zk2:2181,zk3:2181 -Dspark.deploy.zookeeper.dir=/spark"
启动master和slaves
./sbin/start-master.sh
./sbin/start-slaves.sh
2.进入spark-m2
修改conf/spark-env.sh
vi spark-env.sh
export SPARK_MASTER_IP=spark-m2
export SPARK_DAEMON_JAVA_OPTS="-Dspark.deploy.recoveryMode=ZOOKEEPER -Dspark.deploy.zookeeper.url=zk1:2181,zk2:2181,zk3:2181 -Dspark.deploy.zookeeper.dir=/spark"
启动master和slaves
./sbin/start-master.sh
./sbin/start-slaves.sh
三.检测
在spark-m1的web ui中可以看到状态
spark-m2中可以看到处于STANDBY状态
application提交时,master改为
--master spark://spark-m1:7077,spark-m2:7077
spark shell 测试
在spark-m1中启动spark Shell
spark-shell --master spark://spark-m1:7077,spark-m2:7077
连接后关闭spark-m1 master
./bin/stop-master.sh
发现spark-shell不会断开而是转到spark-m2的master上继续执行（该过程持续大概1分钟,woker会重新注册到spark-m2上）,同时spark-m2变为alive状态。
可以在spark-m2的master日志中看到：
15/08/17 14:45:35 INFO ZooKeeperLeaderElectionAgent: We have gained leadership
15/08/17 14:45:36 INFO Master: I have been elected leader! New state: RECOVERING
15/08/17 14:45:36 INFO Master: Trying to recover worker:...
15/08/17 14:45:36 INFO Master: Trying to recover worker: ...
15/08/17 14:45:36 INFO Master: Trying to recover worker: ...
......
15/08/17 14:45:36 INFO Master: Worker has been re-registered: worker-...
15/08/17 14:45:36 INFO Master: Worker has been re-registered: worker-...
15/08/17 14:45:36 INFO Master: Worker has been re-registered: worker-...
...
15/08/17 14:45:36 INFO Master: Recovery complete - resuming operations!
部署结束
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