spark1.5开始为mesos粗粒度模式和standalone模式提供了Dynamic Allocation的机制。
通过将闲置executor移除，达到提高资源利用率的目的。
一.动态资源调配
为standalone模式和mesos的粗粒度模式提供了executor的动态管理，具体表现为：如果executor在一段时间内空闲就会移除这个executor。
动态申请executor
如果有新任务处于等待状态，并且等待时间超过spark.dynamicAllocation.schedulerBacklogTimeout(默认1s)，则会依次启动executor,每次启动1,2,4,8...个executor（如果有的话）。
启动的间隔由spark.dynamicAllocation.sustainedSchedulerBacklogTimeout控制(默认与schedulerBacklogTimeout相同)。
动态移除executor
executor空闲时间超过spark.dynamicAllocation.executorIdleTimeout设置的值(默认60s )，该executor会被移除，除非有缓存数据。
二.配置
conf/spark-default.conf中配置
spark.dynamicAllocation.enabled true
spark.shuffle.service.enabled true
开启shuffle service(每个worker节点)
sbin/start-shuffle-service.sh
启动worker
sbin/start-slave.sh -h hostname sparkURL
如果有节点没开，运行任务时该节点就报错
ExecutorLostFailure
相关配置
| 参数名 | 默认值 | 描述 |
|---|---|---|
| spark.dynamicAllocation.executorIdleTimeout | 60s | executor空闲时间达到规定值，则将该executor移除。 |
| spark.dynamicAllocation.cachedExecutorIdleTimeout | infinity | 缓存了数据的executor默认不会被移除 |
| spark.dynamicAllocation.maxExecutors | infinity | 最多使用的executor数，默认为你申请的最大executor数 |
| spark.dynamicAllocation.minExecutors | 0 | 最少保留的executor数 |
| spark.dynamicAllocation.schedulerBacklogTimeout | 1s | 有task等待运行时间超过该值后开始启动executor |
| spark.dynamicAllocation.executorIdleTimeout | schedulerBacklogTimeout | 动态启动executor的间隔 |
| spark.dynamicAllocation.initialExecutors | spark.dynamicAllocation.minExecutors | 如果所有的executor都移除了，重新请求时启动的初始executor数 |
三.使用
启动一个spark-shell,有5个executor,每个executor使用2个core
bin/spark-shell --total-executor-cores 10 --executor-cores 2
如果在60s内无动作，在终端会看到如下提示
scala> 15/11/17 15:40:47 ERROR TaskSchedulerImpl: Lost executor 0 on spark047213: remote Rpc client disassociated
15/11/17 15:40:47 WARN ReliableDeliverySupervisor: Association with remote system [akka.tcp://sparkExecutor@spark047213:50015] has failed, address is now gated for [5000] ms. Reason: [Disassociated]
15/11/17 15:40:50 ERROR TaskSchedulerImpl: Lost executor 1 on spark047213: remote Rpc client disassociated
15/11/17 15:40:50 WARN ReliableDeliverySupervisor: Association with remote system [akka.tcp://sparkExecutor@spark047213:49847] has failed, address is now gated for [5000] ms. Reason: [Disassociated]
...
吐槽一下，executor移除后会提示你和executor断开连接，给的提示居然是ERROR....
然后可以在web ui上看到使用的10个core已经处于left状态
提交一个只需要2个core的任务
sc.parallelize(1 to 2).count
看到有2个core开始进入注册状态，提供服务
