spark从入门到放弃 之 分布式运行jar包

2024-06-09 10:32
文章标签 入门 运行 分布式 jar 放弃 spark

本文主要是介绍spark从入门到放弃 之 分布式运行jar包，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！

scala代码如下：

import org.apache.spark.SparkConf
import org.apache.spark.SparkContext
import org.apache.spark.SparkContext._/*** 统计字符出现次数*/
object WordCount {def main(args: Array[String]) {if (args.length < 1) {System.err.println("Usage: <file>")System.exit(1)}val conf = new SparkConf()val sc = new SparkContext(conf)val line = sc.textFile(args(0))line.flatMap(_.split(" ")).map((_, 1)).reduceByKey(_+_).collect().foreach(println)sc.stop()}
}
注意：build path里不但要用Spark lib文件夹下的spark-assembly-1.5.0-cdh5.5.4-hadoop2.6.0-cdh5.5.4.jar，而且要把Hadoop share/hadoop目录下的jar添加进来，具体添加哪几个我也不太清楚，反正都加进去就对了。

用eclipse将其打成jar包


注意：scala的object名不一定要和文件名相同，这一点和java不一样。例如我的object名为WordCount，但文件名是WC.scala

上传服务器

查看服务器上测试文件内容

-bash-4.1$ hadoop fs -cat /user/hdfs/test.txt
张三 张四
张三 张五
李三 李三
李四 李四
李四 王二
老王 老王

运行spark-submit命令，提交jar包

-bash-4.1$ spark-submit --class "WordCount" wc.jar /user/hdfs/test.txt
16/08/22 15:54:17 INFO SparkContext: Running Spark version 1.5.0-cdh5.5.4
16/08/22 15:54:18 INFO SecurityManager: Changing view acls to: hdfs
16/08/22 15:54:18 INFO SecurityManager: Changing modify acls to: hdfs
16/08/22 15:54:18 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(hdfs); users with modify permissions: Set(hdfs)
16/08/22 15:54:19 INFO Slf4jLogger: Slf4jLogger started
16/08/22 15:54:19 INFO Remoting: Starting remoting
16/08/22 15:54:19 INFO Remoting: Remoting started; listening on addresses :[akka.tcp://sparkDriver@192.168.56.201:55886]
16/08/22 15:54:19 INFO Remoting: Remoting now listens on addresses: [akka.tcp://sparkDriver@192.168.56.201:55886]
16/08/22 15:54:19 INFO Utils: Successfully started service 'sparkDriver' on port 55886.
16/08/22 15:54:19 INFO SparkEnv: Registering MapOutputTracker
16/08/22 15:54:19 INFO SparkEnv: Registering BlockManagerMaster
16/08/22 15:54:19 INFO DiskBlockManager: Created local directory at /tmp/blockmgr-eccd9ad6-6296-4508-a9c8-a22b5a36ecbe
16/08/22 15:54:20 INFO MemoryStore: MemoryStore started with capacity 534.5 MB
16/08/22 15:54:20 INFO HttpFileServer: HTTP File server directory is /tmp/spark-bbf694e7-32e2-40b6-88a3-4d97a1d1aab9/httpd-72a45554-b57b-4a5d-af2f-24f198e6300b
16/08/22 15:54:20 INFO HttpServer: Starting HTTP Server
16/08/22 15:54:20 INFO Utils: Successfully started service 'HTTP file server' on port 59636.
16/08/22 15:54:20 INFO SparkEnv: Registering OutputCommitCoordinator
16/08/22 15:54:41 INFO Utils: Successfully started service 'SparkUI' on port 4040.
16/08/22 15:54:41 INFO SparkUI: Started SparkUI at http://192.168.56.201:4040
16/08/22 15:54:41 INFO SparkContext: Added JAR file:/var/lib/hadoop-hdfs/wc.jar at http://192.168.56.201:59636/jars/wc.jar with timestamp 1471852481181
16/08/22 15:54:41 WARN MetricsSystem: Using default name DAGScheduler for source because spark.app.id is not set.
16/08/22 15:54:41 INFO RMProxy: Connecting to ResourceManager at hadoop01/192.168.56.201:8032
16/08/22 15:54:41 INFO Client: Requesting a new application from cluster with 2 NodeManagers
16/08/22 15:54:41 INFO Client: Verifying our application has not requested more than the maximum memory capability of the cluster (1536 MB per container)
16/08/22 15:54:41 INFO Client: Will allocate AM container, with 896 MB memory including 384 MB overhead
16/08/22 15:54:41 INFO Client: Setting up container launch context for our AM
16/08/22 15:54:41 INFO Client: Setting up the launch environment for our AM container
16/08/22 15:54:41 INFO Client: Preparing resources for our AM container
16/08/22 15:54:42 INFO Client: Uploading resource file:/tmp/spark-bbf694e7-32e2-40b6-88a3-4d97a1d1aab9/__spark_conf__5421268438919389977.zip -> hdfs://hadoop01:8020/user/hdfs/.sparkStaging/application_1471848612199_0005/__spark_conf__5421268438919389977.zip
16/08/22 15:54:43 INFO SecurityManager: Changing view acls to: hdfs
16/08/22 15:54:43 INFO SecurityManager: Changing modify acls to: hdfs
16/08/22 15:54:43 INFO SecurityManager: SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(hdfs); users with modify permissions: Set(hdfs)
16/08/22 15:54:43 INFO Client: Submitting application 5 to ResourceManager
16/08/22 15:54:43 INFO YarnClientImpl: Submitted application application_1471848612199_0005
16/08/22 15:54:44 INFO Client: Application report for application_1471848612199_0005 (state: ACCEPTED)
16/08/22 15:54:44 INFO Client: client token: N/Adiagnostics: N/AApplicationMaster host: N/AApplicationMaster RPC port: -1queue: root.hdfsstart time: 1471852483082final status: UNDEFINEDtracking URL: http://hadoop01:8088/proxy/application_1471848612199_0005/user: hdfs
16/08/22 15:54:45 INFO Client: Application report for application_1471848612199_0005 (state: ACCEPTED)
16/08/22 15:54:46 INFO Client: Application report for application_1471848612199_0005 (state: ACCEPTED)
16/08/22 15:54:47 INFO Client: Application report for application_1471848612199_0005 (state: ACCEPTED)
16/08/22 15:54:48 INFO Client: Application report for application_1471848612199_0005 (state: ACCEPTED)
16/08/22 15:54:49 INFO Client: Application report for application_1471848612199_0005 (state: ACCEPTED)
16/08/22 15:54:49 INFO YarnSchedulerBackend$YarnSchedulerEndpoint: ApplicationMaster registered as AkkaRpcEndpointRef(Actor[akka.tcp://sparkYarnAM@192.168.56.206:46225/user/YarnAM#289706976])
16/08/22 15:54:49 INFO YarnClientSchedulerBackend: Add WebUI Filter. org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter, Map(PROXY_HOSTS -> hadoop01, PROXY_URI_BASES -> http://hadoop01:8088/proxy/application_1471848612199_0005), /proxy/application_1471848612199_0005
16/08/22 15:54:49 INFO JettyUtils: Adding filter: org.apache.hadoop.yarn.server.webproxy.amfilter.AmIpFilter
16/08/22 15:54:50 INFO Client: Application report for application_1471848612199_0005 (state: RUNNING)
16/08/22 15:54:50 INFO Client: client token: N/Adiagnostics: N/AApplicationMaster host: 192.168.56.206ApplicationMaster RPC port: 0queue: root.hdfsstart time: 1471852483082final status: UNDEFINEDtracking URL: http://hadoop01:8088/proxy/application_1471848612199_0005/user: hdfs
16/08/22 15:54:50 INFO YarnClientSchedulerBackend: Application application_1471848612199_0005 has started running.
16/08/22 15:54:50 INFO Utils: Successfully started service 'org.apache.spark.network.netty.NettyBlockTransferService' on port 38391.
16/08/22 15:54:50 INFO NettyBlockTransferService: Server created on 38391
16/08/22 15:54:50 INFO BlockManager: external shuffle service port = 7337
16/08/22 15:54:50 INFO BlockManagerMaster: Trying to register BlockManager
16/08/22 15:54:50 INFO BlockManagerMasterEndpoint: Registering block manager 192.168.56.201:38391 with 534.5 MB RAM, BlockManagerId(driver, 192.168.56.201, 38391)
16/08/22 15:54:50 INFO BlockManagerMaster: Registered BlockManager
16/08/22 15:54:51 INFO EventLoggingListener: Logging events to hdfs://hadoop01:8020/user/spark/applicationHistory/application_1471848612199_0005
16/08/22 15:54:51 INFO YarnClientSchedulerBackend: SchedulerBackend is ready for scheduling beginning after reached minRegisteredResourcesRatio: 0.8
16/08/22 15:54:52 INFO MemoryStore: ensureFreeSpace(195280) called with curMem=0, maxMem=560497950
16/08/22 15:54:52 INFO MemoryStore: Block broadcast_0 stored as values in memory (estimated size 190.7 KB, free 534.3 MB)
16/08/22 15:54:52 INFO MemoryStore: ensureFreeSpace(22784) called with curMem=195280, maxMem=560497950
16/08/22 15:54:52 INFO MemoryStore: Block broadcast_0_piece0 stored as bytes in memory (estimated size 22.3 KB, free 534.3 MB)
16/08/22 15:54:52 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on 192.168.56.201:38391 (size: 22.3 KB, free: 534.5 MB)
16/08/22 15:54:52 INFO SparkContext: Created broadcast 0 from textFile at WC.scala:17
16/08/22 15:54:52 INFO FileInputFormat: Total input paths to process : 1
16/08/22 15:54:52 INFO SparkContext: Starting job: collect at WC.scala:19
16/08/22 15:54:52 INFO DAGScheduler: Registering RDD 3 (map at WC.scala:19)
16/08/22 15:54:52 INFO DAGScheduler: Got job 0 (collect at WC.scala:19) with 2 output partitions
16/08/22 15:54:52 INFO DAGScheduler: Final stage: ResultStage 1(collect at WC.scala:19)
16/08/22 15:54:52 INFO DAGScheduler: Parents of final stage: List(ShuffleMapStage 0)
16/08/22 15:54:52 INFO DAGScheduler: Missing parents: List(ShuffleMapStage 0)
16/08/22 15:54:52 INFO DAGScheduler: Submitting ShuffleMapStage 0 (MapPartitionsRDD[3] at map at WC.scala:19), which has no missing parents
16/08/22 15:54:52 INFO MemoryStore: ensureFreeSpace(4024) called with curMem=218064, maxMem=560497950
16/08/22 15:54:52 INFO MemoryStore: Block broadcast_1 stored as values in memory (estimated size 3.9 KB, free 534.3 MB)
16/08/22 15:54:52 INFO MemoryStore: ensureFreeSpace(2281) called with curMem=222088, maxMem=560497950
16/08/22 15:54:52 INFO MemoryStore: Block broadcast_1_piece0 stored as bytes in memory (estimated size 2.2 KB, free 534.3 MB)
16/08/22 15:54:52 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on 192.168.56.201:38391 (size: 2.2 KB, free: 534.5 MB)
16/08/22 15:54:52 INFO SparkContext: Created broadcast 1 from broadcast at DAGScheduler.scala:861
16/08/22 15:54:52 INFO DAGScheduler: Submitting 2 missing tasks from ShuffleMapStage 0 (MapPartitionsRDD[3] at map at WC.scala:19)
16/08/22 15:54:52 INFO YarnScheduler: Adding task set 0.0 with 2 tasks
16/08/22 15:54:53 INFO ExecutorAllocationManager: Requesting 1 new executor because tasks are backlogged (new desired total will be 1)
16/08/22 15:54:54 INFO ExecutorAllocationManager: Requesting 1 new executor because tasks are backlogged (new desired total will be 2)
16/08/22 15:54:59 INFO YarnClientSchedulerBackend: Registered executor: AkkaRpcEndpointRef(Actor[akka.tcp://sparkExecutor@hadoop05:59707/user/Executor#729574503]) with ID 1
16/08/22 15:54:59 INFO ExecutorAllocationManager: New executor 1 has registered (new total is 1)
16/08/22 15:54:59 INFO TaskSetManager: Starting task 0.0 in stage 0.0 (TID 0, hadoop05, partition 0,NODE_LOCAL, 2186 bytes)
16/08/22 15:54:59 INFO BlockManagerMasterEndpoint: Registering block manager hadoop05:53273 with 534.5 MB RAM, BlockManagerId(1, hadoop05, 53273)
16/08/22 15:55:00 INFO BlockManagerInfo: Added broadcast_1_piece0 in memory on hadoop05:53273 (size: 2.2 KB, free: 534.5 MB)
16/08/22 15:55:01 INFO BlockManagerInfo: Added broadcast_0_piece0 in memory on hadoop05:53273 (size: 22.3 KB, free: 534.5 MB)
16/08/22 15:55:03 INFO TaskSetManager: Starting task 1.0 in stage 0.0 (TID 1, hadoop05, partition 1,NODE_LOCAL, 2186 bytes)
16/08/22 15:55:03 INFO TaskSetManager: Finished task 0.0 in stage 0.0 (TID 0) in 3733 ms on hadoop05 (1/2)
16/08/22 15:55:03 INFO DAGScheduler: ShuffleMapStage 0 (map at WC.scala:19) finished in 10.621 s
16/08/22 15:55:03 INFO DAGScheduler: looking for newly runnable stages
16/08/22 15:55:03 INFO DAGScheduler: running: Set()
16/08/22 15:55:03 INFO DAGScheduler: waiting: Set(ResultStage 1)
16/08/22 15:55:03 INFO DAGScheduler: failed: Set()
16/08/22 15:55:03 INFO TaskSetManager: Finished task 1.0 in stage 0.0 (TID 1) in 150 ms on hadoop05 (2/2)
16/08/22 15:55:03 INFO YarnScheduler: Removed TaskSet 0.0, whose tasks have all completed, from pool 
16/08/22 15:55:03 INFO DAGScheduler: Missing parents for ResultStage 1: List()
16/08/22 15:55:03 INFO DAGScheduler: Submitting ResultStage 1 (ShuffledRDD[4] at reduceByKey at WC.scala:19), which is now runnable
16/08/22 15:55:03 INFO MemoryStore: ensureFreeSpace(2288) called with curMem=224369, maxMem=560497950
16/08/22 15:55:03 INFO MemoryStore: Block broadcast_2 stored as values in memory (estimated size 2.2 KB, free 534.3 MB)
16/08/22 15:55:03 INFO MemoryStore: ensureFreeSpace(1363) called with curMem=226657, maxMem=560497950
16/08/22 15:55:03 INFO MemoryStore: Block broadcast_2_piece0 stored as bytes in memory (estimated size 1363.0 B, free 534.3 MB)
16/08/22 15:55:03 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on 192.168.56.201:38391 (size: 1363.0 B, free: 534.5 MB)
16/08/22 15:55:03 INFO SparkContext: Created broadcast 2 from broadcast at DAGScheduler.scala:861
16/08/22 15:55:03 INFO DAGScheduler: Submitting 2 missing tasks from ResultStage 1 (ShuffledRDD[4] at reduceByKey at WC.scala:19)
16/08/22 15:55:03 INFO YarnScheduler: Adding task set 1.0 with 2 tasks
16/08/22 15:55:03 INFO TaskSetManager: Starting task 0.0 in stage 1.0 (TID 2, hadoop05, partition 0,PROCESS_LOCAL, 1950 bytes)
16/08/22 15:55:03 INFO BlockManagerInfo: Added broadcast_2_piece0 in memory on hadoop05:53273 (size: 1363.0 B, free: 534.5 MB)
16/08/22 15:55:03 INFO MapOutputTrackerMasterEndpoint: Asked to send map output locations for shuffle 0 to hadoop05:59707
16/08/22 15:55:03 INFO MapOutputTrackerMaster: Size of output statuses for shuffle 0 is 148 bytes
16/08/22 15:55:03 INFO TaskSetManager: Starting task 1.0 in stage 1.0 (TID 3, hadoop05, partition 1,PROCESS_LOCAL, 1950 bytes)
16/08/22 15:55:03 INFO TaskSetManager: Finished task 0.0 in stage 1.0 (TID 2) in 155 ms on hadoop05 (1/2)
16/08/22 15:55:03 INFO DAGScheduler: ResultStage 1 (collect at WC.scala:19) finished in 0.193 s
16/08/22 15:55:03 INFO TaskSetManager: Finished task 1.0 in stage 1.0 (TID 3) in 53 ms on hadoop05 (2/2)
16/08/22 15:55:03 INFO YarnScheduler: Removed TaskSet 1.0, whose tasks have all completed, from pool 
16/08/22 15:55:03 INFO DAGScheduler: Job 0 finished: collect at WC.scala:19, took 11.041942 s
(张五,1)
(老王,2)
(张三,2)
(张四,1)
(王二,1)
(李四,3)
(李三,2)
16/08/22 15:55:03 INFO SparkUI: Stopped Spark web UI at http://192.168.56.201:4040
16/08/22 15:55:03 INFO DAGScheduler: Stopping DAGScheduler
16/08/22 15:55:03 INFO YarnClientSchedulerBackend: Interrupting monitor thread
16/08/22 15:55:03 INFO YarnClientSchedulerBackend: Shutting down all executors
16/08/22 15:55:03 INFO YarnClientSchedulerBackend: Asking each executor to shut down
16/08/22 15:55:03 INFO YarnClientSchedulerBackend: Stopped
16/08/22 15:55:03 INFO MapOutputTrackerMasterEndpoint: MapOutputTrackerMasterEndpoint stopped!
16/08/22 15:55:03 INFO MemoryStore: MemoryStore cleared
16/08/22 15:55:03 INFO BlockManager: BlockManager stopped
16/08/22 15:55:03 INFO BlockManagerMaster: BlockManagerMaster stopped
16/08/22 15:55:03 INFO OutputCommitCoordinator$OutputCommitCoordinatorEndpoint: OutputCommitCoordinator stopped!
16/08/22 15:55:03 INFO RemoteActorRefProvider$RemotingTerminator: Shutting down remote daemon.
16/08/22 15:55:03 INFO SparkContext: Successfully stopped SparkContext
16/08/22 15:55:03 INFO RemoteActorRefProvider$RemotingTerminator: Remote daemon shut down; proceeding with flushing remote transports.
16/08/22 15:55:03 INFO ShutdownHookManager: Shutdown hook called
16/08/22 15:55:03 INFO ShutdownHookManager: Deleting directory /tmp/spark-bbf694e7-32e2-40b6-88a3-4d97a1d1aab9

执行成功。

这篇关于spark从入门到放弃 之 分布式运行jar包的文章就介绍到这儿，希望我们推荐的文章对编程师们有所帮助！


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