摘要:本篇教程探讨了大数据技术 Spark初阶学习,希望阅读本篇文章以后大家有所收获,帮助大家对大数据技术的理解更加深入。
本篇教程探讨了大数据技术 Spark初阶学习,希望阅读本篇文章以后大家有所收获,帮助大家对大数据技术的理解更加深入。
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1:Spark的官方网址://spark.apache.org/
1 Spark生态系统已经发展成为一个包含多个子项目的集合,其中包含SparkSQL、Spark Streaming、GraphX、MLlib等子项目,Spark是基于内存计算的大数据并行计算框架。Spark基于内存计算,提高了在大数据环境下数据处理的实时性,同时保证了高容错性和高可伸缩性,允许用户将Spark部署在大量廉价硬件之上,形成集群。2 Spark是MapReduce的替代方案,而且兼容HDFS、Hive,可融入Hadoop的生态系统,以弥补MapReduce的不足。
2:Spark特点:
1 1:特点一:快
2 与Hadoop的MapReduce相比,Spark基于内存的运算要快100倍以上,基于硬盘的运算也要快10倍以上。Spark实现了高效的DAG执行引擎,可以通过基于内存来高效处理数据流。
3 2:特点二:易用
4 Spark支持Java、Python和Scala的API,还支持超过80种高级算法,使用户可以快速构建不同的应用。而且Spark支持交互式的Python和Scala的shell,可以非常方便地在这些shell中使用Spark集群来验证解决问题的方法。
5 3:特点三:通用
6 Spark提供了统一的解决方案。Spark可以用于批处理、交互式查询(Spark SQL)、实时流处理(Spark Streaming)、机器学习(Spark MLlib)和图计算(GraphX)。这些不同类型的处理都可以在同一个应用中无缝使用。Spark统一的解决方案非常具有吸引力,毕竟任何公司都想用统一的平台去处理遇到的问题,减少开发和维护的人力成本和部署平台的物力成本。
7 4:特点四:兼容性
8 Spark可以非常方便地与其他的开源产品进行融合。比如,Spark可以使用Hadoop的YARN和Apache Mesos作为它的资源管理和调度器,器,并且可以处理所有Hadoop支持的数据,包括HDFS、HBase和Cassandra等。这对于已经部署Hadoop集群的用户特别重要,因为不需要做任何数据迁移就可以使用Spark的强大处理能力。Spark也可以不依赖于第三方的资源管理和调度器,它实现了Standalone作为其内置的资源管理和调度框架,这样进一步降低了Spark的使用门槛,使得所有人都可以非常容易地部署和使用Spark。此外,Spark还提供了在EC2上部署Standalone的Spark集群的工具。
3:Spark的部署安装(上传jar,过程省略,记得安装好jdk。):
下载网址://www.apache.org/dyn/closer.lua/spark/ 或者 //spark.apache.org/downloads.html
Spark的解压缩操作,如下所示:
哈哈哈,犯了一个低级错误,千万记得加-C,解压安装包到指定位置。是大写的哦;
然后呢,进入到Spark安装目录,进入conf目录并重命名并修改spark-env.sh.template文件,操作如下所示:
将spark-env.sh.template 名称修改为spark-env.sh,然后在该配置文件中添加如下配置,之后保存退出:
1 [root@localhost conf]# mv spark-env.sh.template spark-env.sh
具体操作如下所示:
然后呢,重命名并修改slaves.template文件,如下所示:
1 [root@localhost conf]# mv slaves.template slaves
在该文件中添加子节点所在的位置(Worker节点),操作如下所示,然后保存退出:
将配置好的Spark拷贝到其他节点上:
1 [root@localhost hadoop]# scp -r spark-1.6.1-bin-hadoop2.6/ slaver1:/home/hadoop/
2 [root@localhost hadoop]# scp -r spark-1.6.1-bin-hadoop2.6/ slaver2:/home/hadoop/
Spark集群配置完毕,目前是1个Master,2个Work(可以是多个Work),在master节点上启动Spark集群:
启动后执行jps命令,主节点上有Master进程,其他子节点上有Work进行,登录Spark管理界面查看集群状态(主节点)://master:8080/:
可以查看一下是否启动起来,如下所示:
然后在页面可以查看信息,如下所示,如果浏览器一直加载不出来,可能是防火墙没关闭(service iptables stop暂时关闭,chkconfig iptables off永久关闭):
到此为止,Spark集群安装完毕。
1 但是有一个很大的问题,那就是Master节点存在单点故障,要解决此问题,就要借助zookeeper,并且启动至少两个Master节点来实现高可靠,配置方式比较简单,如下所示:
2 Spark集群规划:node1,node2是Master;node3,node4,node5是Worker
3 安装配置zk集群,并启动zk集群,然后呢,停止spark所有服务,修改配置文件spark-env.sh,
4 在该配置文件中删掉SPARK_MASTER_IP并添加如下配置:
5 export SPARK_DAEMON_JAVA_OPTS="-Dspark.deploy.recoveryMode=ZOOKEEPER -Dspark.deploy.zookeeper.url=zk1,zk2,zk3 -Dspark.deploy.zookeeper.dir=/spark"
6 1.在node1节点上修改slaves配置文件内容指定worker节点
7 2.在node1上执行sbin/start-all.sh脚本,然后在node2上执行sbin/start-master.sh启动第二个Master
4:执行Spark程序(执行第一个spark程序,如下所示):
执行如下所示,然后就报了一大推错误,由于错误过多就隐藏了,方便以后脑补:
1 [root@master bin]# ./spark-submit 2 > --class org.apache.spark.examples.SparkPi 3 > --master spark://master:7077 \
4 > --executor-memory 1G 5 > --total-executor-cores 2 6 > /home/hadoop/spark-1.6.1-bin-hadoop2.6/l
7 lib/ licenses/ logs/
8 > /home/hadoop/spark-1.6.1-bin-hadoop2.6/lib/spark-examples-1.6.1-hadoop2.6.0.jar 9 > 100或者如下所示也可:[root@master spark-1.6.1-bin-hadoop2.6]# bin/spark-submit --class org.apache.spark.examples.SparkPi --master spark://master:7077 --executor-memory 512M --total-executor-cores 2 /home/hadoop/spark-1.6.1-bin-hadoop2.6/lib/spark-examples-1.6.1-hadoop2.6.0.jar 10
错误如下所示,由于太长了就折叠起来了:
1 [root@master hadoop]# cd spark-1.6.1-bin-hadoop2.6/
2 [root@master spark-1.6.1-bin-hadoop2.6]# ls
3 bin conf ec2 lib licenses NOTICE R RELEASE
4 CHANGES.txt data examples LICENSE logs python README.md sbin
5 [root@master spark-1.6.1-bin-hadoop2.6]# bi
6 bind biosdecode biosdevname
7 [root@master spark-1.6.1-bin-hadoop2.6]# cd bin/
8 [root@master bin]# ls
9 beeline pyspark run-example2.cmd spark-class.cmd spark-shell spark-submit
10 beeline.cmd pyspark2.cmd run-example.cmd sparkR spark-shell2.cmd spark-submit2.cmd
11 load-spark-env.cmd pyspark.cmd spark-class sparkR2.cmd spark-shell.cmd spark-submit.cmd
12 load-spark-env.sh run-example spark-class2.cmd sparkR.cmd spark-sql
13 [root@master bin]# ./spark-submit 14 > --class org.apache.spark.examples.SparkPi 15 > --master spark://master:7077 \
16 > --executor-memory 1G 17 > --total-executor-cores 2 18 > /home/hadoop/spark-1.6.1-bin-hadoop2.6/l
19 lib/ licenses/ logs/
20 > /home/hadoop/spark-1.6.1-bin-hadoop2.6/lib/spark-examples-1.6.1-hadoop2.6.0.jar 21 > 100
22 Using Spark‘s default log4j profile: org/apache/spark/log4j-defaults.properties
23 18/01/02 19:44:01 INFO SparkContext: Running Spark version 1.6.1
24 18/01/02 19:44:05 WARN NativeCodeLoader: Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
25 18/01/02 19:44:06 INFO SecurityManager: Changing view acls to: root
26 18/01/02 19:44:06 INFO SecurityManager: Changing modify acls to: root
27 18/01/02 19:44:06 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(root); users with modify permissions: Set(root)
28 18/01/02 19:44:09 INFO Utils: Successfully started service ‘sparkDriver‘ on port 41731.
29 18/01/02 19:44:11 INFO Slf4jLogger: Slf4jLogger started
30 18/01/02 19:44:11 INFO Remoting: Starting remoting
31 18/01/02 19:44:12 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriverActorSystem@192.168.3.129:49630]
32 18/01/02 19:44:12 INFO Utils: Successfully started service ‘sparkDriverActorSystem‘ on port 49630.
33 18/01/02 19:44:13 INFO SparkEnv: Registering MapOutputTracker
34 18/01/02 19:44:13 INFO SparkEnv: Registering BlockManagerMaster
35 18/01/02 19:44:13 INFO DiskBlockManager: Created local directory at /tmp/blockmgr-c154fc3f-8552-49d4-9a9a-1ce79dba74d7
36 18/01/02 19:44:13 INFO MemoryStore: MemoryStore started with capacity 517.4 MB
37 18/01/02 19:44:14 INFO SparkEnv: Registering OutputCommitCoordinator
38 18/01/02 19:44:15 INFO Utils: Successfully started service ‘SparkUI‘ on port 4040.
39 18/01/02 19:44:15 INFO SparkUI: Started SparkUI at //192.168.3.129:4040
40 18/01/02 19:44:15 INFO HttpFileServer: HTTP File server directory is /tmp/spark-2b7d6514-96ad-4999-a7d0-5797b4a53652/httpd-fda58f3c-9d2e-49df-bfe7-2a72fd6dab39
41 18/01/02 19:44:15 INFO HttpServer: Starting HTTP Server
42 18/01/02 19:44:15 INFO Utils: Successfully started service ‘HTTP file server‘ on port 42161.
43 18/01/02 19:44:18 INFO SparkContext: Added JAR file:/home/hadoop/spark-1.6.1-bin-hadoop2.6/lib/spark-examples-1.6.1-hadoop2.6.0.jar at //192.168.3.129:42161/jars/spark-examples-1.6.1-hadoop2.6.0.jar with timestamp 1514951058742
44 18/01/02 19:44:19 INFO AppClient$ClientEndpoint: Connecting to master spark://master:7077...
45 18/01/02 19:44:28 INFO SparkDeploySchedulerBackend: Connected to Spark cluster with app ID app-20180102194427-0000
46 18/01/02 19:44:30 INFO Utils: Successfully started service ‘org.apache.spark.network.netty.NettyBlockTransferService‘ on port 58259.
47 18/01/02 19:44:30 INFO NettyBlockTransferService: Server created on 58259
48 18/01/02 19:44:30 INFO BlockManagerMaster: Trying to register BlockManager
49 18/01/02 19:44:30 INFO BlockManagerMasterEndpoint: Registering block manager 192.168.3.129:58259 with 517.4 MB RAM, BlockManagerId(driver, 192.168.3.129, 58259)
50 18/01/02 19:44:30 INFO BlockManagerMaster: Registered BlockManager
51 18/01/02 19:44:31 INFO AppClient$ClientEndpoint: Executor added: app-20180102194427-0000/0 on worker-20180103095039-192.168.3.131-39684 (192.168.3.131:39684) with 1 cores
52 18/01/02 19:44:31 INFO SparkDeploySchedulerBackend: Granted executor ID app-20180102194427-0000/0 on hostPort 192.168.3.131:39684 with 1 cores, 1024.0 MB RAM
53 18/01/02 19:44:31 INFO AppClient$ClientEndpoint: Executor added: app-20180102194427-0000/1 on worker-20180103095039-192.168.3.130-46477 (192.168.3.130:46477) with 1 cores
54 18/01/02 19:44:31 INFO SparkDeploySchedulerBackend: Granted executor ID app-20180102194427-0000/1 on hostPort 192.168.3.130:46477 with 1 cores, 1024.0 MB RAM
55 18/01/02 19:44:33 INFO SparkDeploySchedulerBackend: SchedulerBackend is ready for scheduling beginning after reached minRegisteredResourcesRatio: 0.0
56 18/01/02 19:44:37 INFO SparkContext: Starting job: reduce at SparkPi.scala:36
57 18/01/02 19:44:38 INFO DAGScheduler: Got job 0 (reduce at SparkPi.scala:36) with 100 output partitions
58 18/01/02 19:44:38 INFO DAGScheduler: Final stage: ResultStage 0 (reduce at SparkPi.scala:36)
59 18/01/02 19:44:38 INFO DAGScheduler: Parents of final stage: List()
60 18/01/02 19:44:38 INFO DAGScheduler: Missing parents: List()
61 18/01/02 19:44:38 INFO DAGScheduler: Submitting ResultStage 0 (MapPartitionsRDD[1] at map at SparkPi.scala:32), which has no missing parents
62 18/01/02 19:44:41 INFO AppClient$ClientEndpoint: Executor updated: app-20180102194427-0000/0 is now RUNNING
63 18/01/02 19:44:41 INFO AppClient$ClientEndpoint: Executor updated: app-20180102194427-0000/1 is now RUNNING
64 18/01/02 19:44:44 WARN SizeEstimator: Failed to check whether UseCompressedOops is set; assuming yes
65 18/01/02 19:44:45 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 1904.0 B, free 1904.0 B)
66 18/01/02 19:44:46 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 1216.0 B, free 3.0 KB)
67 18/01/02 19:44:46 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 192.168.3.129:58259 (size: 1216.0 B, free: 517.4 MB)
68 18/01/02 19:44:46 INFO SparkContext: Created broadcast 0 from broadcast at DAGScheduler.scala:1006
69 18/01/02 19:44:46 INFO DAGScheduler: Submitting 100 missing tasks from ResultStage 0 (MapPartitionsRDD[1] at map at SparkPi.scala:32)
70 18/01/02 19:44:46 INFO TaskSchedulerImpl: Adding task set 0.0 with 100 tasks
71 18/01/02 19:45:01 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
72 18/01/02 19:45:16 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
73 18/01/02 19:45:31 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
74 18/01/02 19:45:46 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
75 18/01/02 19:46:01 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
76 18/01/02 19:46:07 INFO AppClient$ClientEndpoint: Executor updated: app-20180102194427-0000/0 is now EXITED (Command exited with code 1)
77 18/01/02 19:46:07 INFO SparkDeploySchedulerBackend: Executor app-20180102194427-0000/0 removed: Command exited with code 1
78 18/01/02 19:46:16 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
79 18/01/02 19:46:31 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
80 18/01/02 19:46:46 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
81 18/01/02 19:47:01 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
82 18/01/02 19:47:16 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
83 18/01/02 19:47:31 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
84 18/01/02 19:47:46 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
85 ^C18/01/02 19:47:58 INFO SparkContext: Invoking stop() from shutdown hook
86 18/01/02 19:47:58 INFO SparkUI: Stopped Spark web UI at //192.168.3.129:4040
87 18/01/02 19:47:58 INFO DAGScheduler: Job 0 failed: reduce at SparkPi.scala:36, took 201.147338 s
88 18/01/02 19:47:58 INFO DAGScheduler: ResultStage 0 (reduce at SparkPi.scala:36) failed in 191.823 s
89 Exception in thread "main" 18/01/02 19:47:58 ERROR LiveListenerBus: SparkListenerBus has already stopped! Dropping event SparkListenerStageCompleted(org.apache.spark.scheduler.StageInfo@10d7390)
90 18/01/02 19:47:58 ERROR LiveListenerBus: SparkListenerBus has already stopped! Dropping event SparkListenerJobEnd(0,1514951278747,JobFailed(org.apache.spark.SparkException: Job 0 cancelled because SparkContext was shut down))
91 18/01/02 19:47:58 INFO SparkDeploySchedulerBackend: Shutting down all executors
92 org.apache.spark.SparkException: Job 0 cancelled because SparkContext was shut down
93 at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:806)
94 at org.apache.spark.scheduler.DAGScheduler$$anonfun$cleanUpAfterSchedulerStop$1.apply(DAGScheduler.scala:804)
95 at scala.collection.mutable.HashSet.foreach(HashSet.scala:79)
96 at org.apache.spark.scheduler.DAGScheduler.cleanUpAfterSchedulerStop(DAGScheduler.scala:804)
97 at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onStop(DAGScheduler.scala:1658)
98 at org.apache.spark.util.EventLoop.stop(EventLoop.scala:84)
99 at org.apache.spark.scheduler.DAGScheduler.stop(DAGScheduler.scala:1581)
100 at org.apache.spark.SparkContext$$anonfun$stop$9.apply$mcV$sp(SparkContext.scala:1740)
101 at org.apache.spark.util.Utils$.tryLogNonFatalError(Utils.scala:1229)
102 at org.apache.spark.SparkContext.stop(SparkContext.scala:1739)
103 at org.apache.spark.SparkContext$$anonfun$3.apply$mcV$sp(SparkContext.scala:596)
104 at org.apache.spark.util.SparkShutdownHook.run(ShutdownHookManager.scala:267)
105 at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ShutdownHookManager.scala:239)
106 at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply(ShutdownHookManager.scala:239)
107 at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1$$anonfun$apply$mcV$sp$1.apply(ShutdownHookManager.scala:239)
108 at org.apache.spark.util.Utils$.logUncaughtExceptions(Utils.scala:1765)
109 at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply$mcV$sp(ShutdownHookManager.scala:239)
110 at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply(ShutdownHookManager.scala:239)
111 at org.apache.spark.util.SparkShutdownHookManager$$anonfun$runAll$1.apply(ShutdownHookManager.scala:239)
112 at scala.util.Try$.apply(Try.scala:161)
113 at org.apache.spark.util.SparkShutdownHookManager.runAll(ShutdownHookManager.scala:239)
114 at org.apache.spark.util.SparkShutdownHookManager$$anon$2.run(ShutdownHookManager.scala:218)
115 at org.apache.hadoop.util.ShutdownHookManager$1.run(ShutdownHookManager.java:54)
116 at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:620)
117 at org.apache.spark.SparkContext.runJob(SparkContext.scala:1832)
118 at org.apache.spark.SparkContext.runJob(SparkContext.scala:1952)
119 at org.apache.spark.rdd.RDD$$anonfun$reduce$1.apply(RDD.scala:1025)
120 at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
121 at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
122 at org.apache.spark.rdd.RDD.withScope(RDD.scala:316)
123 at org.apache.spark.rdd.RDD.reduce(RDD.scala:1007)
124 at org.apache.spark.examples.SparkPi$.main(SparkPi.scala:36)
125 at org.apache.spark.examples.SparkPi.main(SparkPi.scala)
126 at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
127 at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:57)
128 at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:43)
129 at java.lang.reflect.Method.invoke(Method.java:606)
130 at org.apache.spark.deploy.SparkSubmit$.org$apache$spark$deploy$SparkSubmit$$runMain(SparkSubmit.scala:731)
131 at org.apache.spark.deploy.SparkSubmit$.doRunMain$1(SparkSubmit.scala:181)
132 at org.apache.spark.deploy.SparkSubmit$.submit(SparkSubmit.scala:206)
133 at org.apache.spark.deploy.SparkSubmit$.main(SparkSubmit.scala:121)
134 at org.apache.spark.deploy.SparkSubmit.main(SparkSubmit.scala)
135 ^C18/01/02 19:48:01 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
136 ^C^C^C^C^C
137 18/01/02 19:48:07 WARN NettyRpcEndpointRef: Error sending message [message = RemoveExecutor(0,Command exited with code 1)] in 1 attempts
138 org.apache.spark.rpc.RpcTimeoutException: Futures timed out after [120 seconds]. This timeout is controlled by spark.rpc.askTimeout
139 at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:48)
140 at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:63)
141 at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
142 at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33)
143 at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:76)
144 at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:101)
145 at org.apache.spark.rpc.RpcEndpointRef.askWithRetry(RpcEndpointRef.scala:77)
146 at org.apache.spark.scheduler.cluster.CoarseGrainedSchedulerBackend.removeExecutor(CoarseGrainedSchedulerBackend.scala:359)
147 at org.apache.spark.scheduler.cluster.SparkDeploySchedulerBackend.executorRemoved(SparkDeploySchedulerBackend.scala:144)
148 at org.apache.spark.deploy.client.AppClient$ClientEndpoint$$anonfun$receive$1.applyOrElse(AppClient.scala:186)
149 at org.apache.spark.rpc.netty.Inbox$$anonfun$process$1.apply$mcV$sp(Inbox.scala:116)
150 at org.apache.spark.rpc.netty.Inbox.safelyCall(Inbox.scala:204)
151 at org.apache.spark.rpc.netty.Inbox.process(Inbox.scala:100)
152 at org.apache.spark.rpc.netty.Dispatcher$MessageLoop.run(Dispatcher.scala:215)
153 at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
154 at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
155 at java.lang.Thread.run(Thread.java:745)
156 Caused by: java.util.concurrent.TimeoutException: Futures timed out after [120 seconds]
157 at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:219)
158 at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:223)
159 at scala.concurrent.Await$$anonfun$result$1.apply(package.scala:107)
160 at scala.concurrent.BlockContext$DefaultBlockContext$.blockOn(BlockContext.scala:53)
161 at scala.concurrent.Await$.result(package.scala:107)
162 at org.apache.spark.rpc.RpcTimeout.awaitResult(RpcTimeout.scala:75)
163 ... 12 more
164 ^C^C^C^C^C^C^C^C^C
165
166
167 ^C^C^C^C^C^C^C^C^C^C^C18/01/02 19:48:16 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
168 ^C^C^C^C^C^C^C^C^C^C18/01/02 19:48:31 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
169 18/01/02 19:48:46 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
170 18/01/02 19:49:01 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
171 18/01/02 19:49:16 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
172 18/01/02 19:49:31 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
173 18/01/02 19:49:46 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
174 18/01/02 19:49:58 WARN NettyRpcEndpointRef: Error sending message [message = StopExecutors] in 1 attempts
175 org.apache.spark.rpc.RpcTimeoutException: Cannot receive any reply in 120 seconds. This timeout is controlled by spark.rpc.askTimeout
176 at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:48)
177 at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:63)
178 at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
179 at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33)
180 at scala.util.Failure$$anonfun$recover$1.apply(Try.scala:185)
181 at scala.util.Try$.apply(Try.scala:161)
182 at scala.util.Failure.recover(Try.scala:185)
183 at scala.concurrent.Future$$anonfun$recover$1.apply(Future.scala:324)
184 at scala.concurrent.Future$$anonfun$recover$1.apply(Future.scala:324)
185 at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32)
186 at org.spark-project.guava.util.concurrent.MoreExecutors$SameThreadExecutorService.execute(MoreExecutors.java:293)
187 at scala.concurrent.impl.ExecutionContextImpl$$anon$1.execute(ExecutionContextImpl.scala:133)
188 at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:40)
189 at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:248)
190 at scala.concurrent.Promise$class.complete(Promise.scala:55)
191 at scala.concurrent.impl.Promise$DefaultPromise.complete(Promise.scala:153)
192 at scala.concurrent.Future$$anonfun$map$1.apply(Future.scala:235)
193 at scala.concurrent.Future$$anonfun$map$1.apply(Future.scala:235)
194 at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32)
195 at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.processBatch$1(Future.scala:643)
196 at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.apply$mcV$sp(Future.scala:658)
197 at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.apply(Future.scala:635)
198 at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.apply(Future.scala:635)
199 at scala.concurrent.BlockContext$.withBlockContext(BlockContext.scala:72)
200 at scala.concurrent.Future$InternalCallbackExecutor$Batch.run(Future.scala:634)
201 at scala.concurrent.Future$InternalCallbackExecutor$.scala$concurrent$Future$InternalCallbackExecutor$$unbatchedExecute(Future.scala:694)
202 at scala.concurrent.Future$InternalCallbackExecutor$.execute(Future.scala:685)
203 at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:40)
204 at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:248)
205 at scala.concurrent.Promise$class.tryFailure(Promise.scala:112)
206 at scala.concurrent.impl.Promise$DefaultPromise.tryFailure(Promise.scala:153)
207 at org.apache.spark.rpc.netty.NettyRpcEnv$$anon$1.run(NettyRpcEnv.scala:241)
208 at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
209 at java.util.concurrent.FutureTask.run(FutureTask.java:262)
210 at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:178)
211 at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:292)
212 at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
213 at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
214 at java.lang.Thread.run(Thread.java:745)
215 Caused by: java.util.concurrent.TimeoutException: Cannot receive any reply in 120 seconds
216 at org.apache.spark.rpc.netty.NettyRpcEnv$$anon$1.run(NettyRpcEnv.scala:242)
217 ... 7 more
218 18/01/02 19:50:01 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
219 18/01/02 19:50:10 WARN NettyRpcEndpointRef: Error sending message [message = RemoveExecutor(0,Command exited with code 1)] in 2 attempts
220 org.apache.spark.rpc.RpcTimeoutException: Cannot receive any reply in 120 seconds. This timeout is controlled by spark.rpc.askTimeout
221 at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:48)
222 at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:63)
223 at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
224 at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33)
225 at scala.util.Failure$$anonfun$recover$1.apply(Try.scala:185)
226 at scala.util.Try$.apply(Try.scala:161)
227 at scala.util.Failure.recover(Try.scala:185)
228 at scala.concurrent.Future$$anonfun$recover$1.apply(Future.scala:324)
229 at scala.concurrent.Future$$anonfun$recover$1.apply(Future.scala:324)
230 at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32)
231 at org.spark-project.guava.util.concurrent.MoreExecutors$SameThreadExecutorService.execute(MoreExecutors.java:293)
232 at scala.concurrent.impl.ExecutionContextImpl$$anon$1.execute(ExecutionContextImpl.scala:133)
233 at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:40)
234 at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:248)
235 at scala.concurrent.Promise$class.complete(Promise.scala:55)
236 at scala.concurrent.impl.Promise$DefaultPromise.complete(Promise.scala:153)
237 at scala.concurrent.Future$$anonfun$map$1.apply(Future.scala:235)
238 at scala.concurrent.Future$$anonfun$map$1.apply(Future.scala:235)
239 at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32)
240 at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.processBatch$1(Future.scala:643)
241 at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.apply$mcV$sp(Future.scala:658)
242 at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.apply(Future.scala:635)
243 at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.apply(Future.scala:635)
244 at scala.concurrent.BlockContext$.withBlockContext(BlockContext.scala:72)
245 at scala.concurrent.Future$InternalCallbackExecutor$Batch.run(Future.scala:634)
246 at scala.concurrent.Future$InternalCallbackExecutor$.scala$concurrent$Future$InternalCallbackExecutor$$unbatchedExecute(Future.scala:694)
247 at scala.concurrent.Future$InternalCallbackExecutor$.execute(Future.scala:685)
248 at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:40)
249 at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:248)
250 at scala.concurrent.Promise$class.tryFailure(Promise.scala:112)
251 at scala.concurrent.impl.Promise$DefaultPromise.tryFailure(Promise.scala:153)
252 at org.apache.spark.rpc.netty.NettyRpcEnv$$anon$1.run(NettyRpcEnv.scala:241)
253 at java.util.concurrent.Executors$RunnableAdapter.call(Executors.java:471)
254 at java.util.concurrent.FutureTask.run(FutureTask.java:262)
255 at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.access$201(ScheduledThreadPoolExecutor.java:178)
256 at java.util.concurrent.ScheduledThreadPoolExecutor$ScheduledFutureTask.run(ScheduledThreadPoolExecutor.java:292)
257 at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
258 at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
259 at java.lang.Thread.run(Thread.java:745)
260 Caused by: java.util.concurrent.TimeoutException: Cannot receive any reply in 120 seconds
261 at org.apache.spark.rpc.netty.NettyRpcEnv$$anon$1.run(NettyRpcEnv.scala:242)
262 ... 7 more
263 18/01/02 19:50:16 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
264 18/01/02 19:50:31 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
265 18/01/02 19:50:46 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
266 18/01/02 19:51:01 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
267 18/01/02 19:51:16 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
268 18/01/02 19:51:31 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
269 18/01/02 19:51:46 WARN TaskSchedulerImpl: Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
270 18/01/02 19:52:01 WARN NettyRpcEndpointRef: Error sending message [message = StopExecutors] in 2 attempts
271 org.apache.spark.rpc.RpcTimeoutException: Cannot receive any reply in 120 seconds. This timeout is controlled by spark.rpc.askTimeout
272 at org.apache.spark.rpc.RpcTimeout.org$apache$spark$rpc$RpcTimeout$$createRpcTimeoutException(RpcTimeout.scala:48)
273 at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:63)
274 at org.apache.spark.rpc.RpcTimeout$$anonfun$addMessageIfTimeout$1.applyOrElse(RpcTimeout.scala:59)
275 at scala.runtime.AbstractPartialFunction.apply(AbstractPartialFunction.scala:33)
276 at scala.util.Failure$$anonfun$recover$1.apply(Try.scala:185)
277 at scala.util.Try$.apply(Try.scala:161)
278 at scala.util.Failure.recover(Try.scala:185)
279 at scala.concurrent.Future$$anonfun$recover$1.apply(Future.scala:324)
280 at scala.concurrent.Future$$anonfun$recover$1.apply(Future.scala:324)
281 at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32)
282 at org.spark-project.guava.util.concurrent.MoreExecutors$SameThreadExecutorService.execute(MoreExecutors.java:293)
283 at scala.concurrent.impl.ExecutionContextImpl$$anon$1.execute(ExecutionContextImpl.scala:133)
284 at scala.concurrent.impl.CallbackRunnable.executeWithValue(Promise.scala:40)
285 at scala.concurrent.impl.Promise$DefaultPromise.tryComplete(Promise.scala:248)
286 at scala.concurrent.Promise$class.complete(Promise.scala:55)
287 at scala.concurrent.impl.Promise$DefaultPromise.complete(Promise.scala:153)
288 at scala.concurrent.Future$$anonfun$map$1.apply(Future.scala:235)
289 at scala.concurrent.Future$$anonfun$map$1.apply(Future.scala:235)
290 at scala.concurrent.impl.CallbackRunnable.run(Promise.scala:32)
291 at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.processBatch$1(Future.scala:643)
292 at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.apply$mcV$sp(Future.scala:658)
293 at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.apply(Future.scala:635)
294 at scala.concurrent.Future$InternalCallbackExecutor$Batch$$anonfun$run$1.apply(Future.scala:635)
295 at scala.concurrent.BlockContext$.withBlockContext(BlockContext.scala:72)
296
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