I use IntelliJ IDEA locally for spark development and report an error when submitting it to the cluster to run. After searching, all the answers point to insufficient CPU/ memory resources, but I have set up enough CPU/ memory resources, and the state of the task is also running. Everything looks fine:
MasterIP is also set correctly, and there is no problem with local IDE compilation, but the complete information of the WARNING, will be reported when it is submitted to the cluster and run through the local IDE:
`2018-05-24 09:52:27 INFO SparkContext:54 - Running Spark version 2.3.0
2018-05-24 09:52:28 WARN NativeCodeLoader:62 - Unable to load native-hadoop library for your platform... using builtin-java classes where applicable
2018-05-24 09:52:28 INFO SparkContext:54 - Submitted application: Spark Pi
2018-05-24 09:52:28 INFO SecurityManager:54 - Changing view acls to: meng
2018-05-24 09:52:28 INFO SecurityManager:54 - Changing modify acls to: meng
2018-05-24 09:52:28 INFO SecurityManager:54 - Changing view acls groups to:
2018-05-24 09:52:28 INFO SecurityManager:54 - Changing modify acls groups to:
2018-05-24 09:52:28 INFO SecurityManager:54 - SecurityManager: authentication disabled; ui acls disabled; users with view permissions: Set(meng); groups with view permissions: Set(); users with modify permissions: Set(meng); groups with modify permissions: Set()
2018-05-24 09:52:28 INFO Utils:54 - Successfully started service "sparkDriver" on port 57174.
2018-05-24 09:52:28 INFO SparkEnv:54 - Registering MapOutputTracker
2018-05-24 09:52:28 INFO SparkEnv:54 - Registering BlockManagerMaster
2018-05-24 09:52:28 INFO BlockManagerMasterEndpoint:54 - Using org.apache.spark.storage.DefaultTopologyMapper for getting topology information
2018-05-24 09:52:28 INFO BlockManagerMasterEndpoint:54 - BlockManagerMasterEndpoint up
2018-05-24 09:52:28 INFO DiskBlockManager:54 - Created local directory at /private/var/folders/8v/2ltw861925785r_dw26d6y0h0000gn/T/blockmgr-e9a51357-7203-4015-b1e4-2aca46af05b1
2018-05-24 09:52:28 INFO MemoryStore:54 - MemoryStore started with capacity 912.3 MB
2018-05-24 09:52:28 INFO SparkEnv:54 - Registering OutputCommitCoordinator
2018-05-24 09:52:28 INFO log:192 - Logging initialized @2504ms
2018-05-24 09:52:28 INFO Server:346 - jetty-9.3.z-SNAPSHOT
2018-05-24 09:52:28 INFO Server:414 - Started @2607ms
2018-05-24 09:52:28 INFO AbstractConnector:278 - Started ServerConnector@1c8a918a{HTTP/1.1,[http/1.1]}{0.0.0.0:4040}
2018-05-24 09:52:28 INFO Utils:54 - Successfully started service "SparkUI" on port 4040.
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@2f94c4db{/jobs,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@7859e786{/jobs/json,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@285d851a{/jobs/job,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@664a9613{/jobs/job/json,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@5118388b{/stages,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@15a902e7{/stages/json,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@7876d598{/stages/stage,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@71104a4{/stages/stage/json,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@4985cbcb{/stages/pool,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@72f46e16{/stages/pool/json,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@3c9168dc{/storage,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@332a7fce{/storage/json,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@549621f3{/storage/rdd,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@54361a9{/storage/rdd/json,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@32232e55{/environment,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@5217f3d0{/environment/json,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@37ebc9d8{/executors,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@293bb8a5{/executors/json,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@2416a51{/executors/threadDump,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@6fa590ba{/executors/threadDump/json,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@6e9319f{/static,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@8a589a2{/,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@c65a5ef{/api,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@ec0c838{/jobs/job/kill,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@6e46d9f4{/stages/stage/kill,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO SparkUI:54 - Bound SparkUI to 0.0.0.0, and started at http://10.200.44.183:4040
2018-05-24 09:52:29 INFO SparkContext:54 - Added JAR /Users/meng/Documents/untitled/out/artifacts/untitled_jar/untitled.jar at spark://10.200.44.183:57174/jars/untitled.jar with timestamp 1527126749237
2018-05-24 09:52:29 INFO StandaloneAppClient$ClientEndpoint:54 - Connecting to master spark://myz-master:7077...
2018-05-24 09:52:29 INFO TransportClientFactory:267 - Successfully created connection to myz-master/210.14.69.105:7077 after 43 ms (0 ms spent in bootstraps)
2018-05-24 09:52:29 INFO StandaloneSchedulerBackend:54 - Connected to Spark cluster with app ID app-20180524095229-0002
2018-05-24 09:52:29 INFO StandaloneAppClient$ClientEndpoint:54 - Executor added: app-20180524095229-0002/0 on worker-20180524093453-192.168.0.212-34919 (192.168.0.212:34919) with 4 core(s)
2018-05-24 09:52:29 INFO StandaloneSchedulerBackend:54 - Granted executor ID app-20180524095229-0002/0 on hostPort 192.168.0.212:34919 with 4 core(s), 512.0 MB RAM
2018-05-24 09:52:29 INFO StandaloneAppClient$ClientEndpoint:54 - Executor added: app-20180524095229-0002/1 on worker-20180524093455-192.168.0.213-43602 (192.168.0.213:43602) with 4 core(s)
2018-05-24 09:52:29 INFO StandaloneSchedulerBackend:54 - Granted executor ID app-20180524095229-0002/1 on hostPort 192.168.0.213:43602 with 4 core(s), 512.0 MB RAM
2018-05-24 09:52:29 INFO Utils:54 - Successfully started service "org.apache.spark.network.netty.NettyBlockTransferService" on port 57176.
2018-05-24 09:52:29 INFO NettyBlockTransferService:54 - Server created on 10.200.44.183:57176
2018-05-24 09:52:29 INFO BlockManager:54 - Using org.apache.spark.storage.RandomBlockReplicationPolicy for block replication policy
2018-05-24 09:52:29 INFO BlockManagerMaster:54 - Registering BlockManager BlockManagerId(driver, 10.200.44.183, 57176, None)
2018-05-24 09:52:29 INFO StandaloneAppClient$ClientEndpoint:54 - Executor updated: app-20180524095229-0002/0 is now RUNNING
2018-05-24 09:52:29 INFO StandaloneAppClient$ClientEndpoint:54 - Executor updated: app-20180524095229-0002/1 is now RUNNING
2018-05-24 09:52:29 INFO BlockManagerMasterEndpoint:54 - Registering block manager 10.200.44.183:57176 with 912.3 MB RAM, BlockManagerId(driver, 10.200.44.183, 57176, None)
2018-05-24 09:52:29 INFO BlockManagerMaster:54 - Registered BlockManager BlockManagerId(driver, 10.200.44.183, 57176, None)
2018-05-24 09:52:29 INFO BlockManager:54 - Initialized BlockManager: BlockManagerId(driver, 10.200.44.183, 57176, None)
2018-05-24 09:52:29 INFO ContextHandler:781 - Started o.s.j.s.ServletContextHandler@5aa6202e{/metrics/json,null,AVAILABLE,@Spark}
2018-05-24 09:52:29 INFO StandaloneSchedulerBackend:54 - SchedulerBackend is ready for scheduling beginning after reached minRegisteredResourcesRatio: 0.0
2018-05-24 09:52:30 INFO SparkContext:54 - Starting job: reduce at SparkPi.scala:26
2018-05-24 09:52:30 INFO DAGScheduler:54 - Got job 0 (reduce at SparkPi.scala:26) with 2 output partitions
2018-05-24 09:52:30 INFO DAGScheduler:54 - Final stage: ResultStage 0 (reduce at SparkPi.scala:26)
2018-05-24 09:52:30 INFO DAGScheduler:54 - Parents of final stage: List()
2018-05-24 09:52:30 INFO DAGScheduler:54 - Missing parents: List()
2018-05-24 09:52:30 INFO DAGScheduler:54 - Submitting ResultStage 0 (MapPartitionsRDD[1] at map at SparkPi.scala:21), which has no missing parents
2018-05-24 09:52:30 INFO MemoryStore:54 - Block broadcast_0 stored as values in memory (estimated size 1776.0 B, free 912.3 MB)
2018-05-24 09:52:30 INFO MemoryStore:54 - Block broadcast_0_piece0 stored as bytes in memory (estimated size 1169.0 B, free 912.3 MB)
2018-05-24 09:52:30 INFO BlockManagerInfo:54 - Added broadcast_0_piece0 in memory on 10.200.44.183:57176 (size: 1169.0 B, free: 912.3 MB)
2018-05-24 09:52:30 INFO SparkContext:54 - Created broadcast 0 from broadcast at DAGScheduler.scala:1039
2018-05-24 09:52:30 INFO DAGScheduler:54 - Submitting 2 missing tasks from ResultStage 0 (MapPartitionsRDD[1] at map at SparkPi.scala:21) (first 15 tasks are for partitions Vector(0, 1))
2018-05-24 09:52:30 INFO TaskSchedulerImpl:54 - Adding task set 0.0 with 2 tasks
**2018-05-24 09:52:45 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources**
2018-05-24 09:53:00 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
2018-05-24 09:53:15 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
2018-05-24 09:53:30 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
2018-05-24 09:53:45 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
2018-05-24 09:54:00 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
2018-05-24 09:54:15 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
2018-05-24 09:54:30 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources
2018-05-24 09:54:30 INFO StandaloneAppClient$ClientEndpoint:54 - Executor updated: app-20180524095229-0002/0 is now EXITED (Command exited with code 1)
2018-05-24 09:54:30 INFO StandaloneSchedulerBackend:54 - Executor app-20180524095229-0002/0 removed: Command exited with code 1
2018-05-24 09:54:30 INFO StandaloneAppClient$ClientEndpoint:54 - Executor added: app-20180524095229-0002/2 on worker-20180524093453-192.168.0.212-34919 (192.168.0.212:34919) with 4 core(s)
2018-05-24 09:54:30 INFO StandaloneSchedulerBackend:54 - Granted executor ID app-20180524095229-0002/2 on hostPort 192.168.0.212:34919 with 4 core(s), 512.0 MB RAM
2018-05-24 09:54:30 INFO StandaloneAppClient$ClientEndpoint:54 - Executor updated: app-20180524095229-0002/2 is now RUNNING
2018-05-24 09:54:31 INFO BlockManagerMaster:54 - Removal of executor 0 requested
2018-05-24 09:54:31 INFO CoarseGrainedSchedulerBackend$DriverEndpoint:54 - Asked to remove non-existent executor 0
2018-05-24 09:54:31 INFO BlockManagerMasterEndpoint:54 - Trying to remove executor 0 from BlockManagerMaster.
2018-05-24 09:54:31 INFO StandaloneAppClient$ClientEndpoint:54 - Executor updated: app-20180524095229-0002/1 is now EXITED (Command exited with code 1)
2018-05-24 09:54:31 INFO StandaloneSchedulerBackend:54 - Executor app-20180524095229-0002/1 removed: Command exited with code 1
2018-05-24 09:54:31 INFO BlockManagerMasterEndpoint:54 - Trying to remove executor 1 from BlockManagerMaster.
2018-05-24 09:54:31 INFO BlockManagerMaster:54 - Removal of executor 1 requested
2018-05-24 09:54:31 INFO StandaloneAppClient$ClientEndpoint:54 - Executor added: app-20180524095229-0002/3 on worker-20180524093455-192.168.0.213-43602 (192.168.0.213:43602) with 4 core(s)
2018-05-24 09:54:31 INFO StandaloneSchedulerBackend:54 - Granted executor ID app-20180524095229-0002/3 on hostPort 192.168.0.213:43602 with 4 core(s), 512.0 MB RAM
2018-05-24 09:54:31 INFO CoarseGrainedSchedulerBackend$DriverEndpoint:54 - Asked to remove non-existent executor 1
2018-05-24 09:54:31 INFO StandaloneAppClient$ClientEndpoint:54 - Executor updated: app-20180524095229-0002/3 is now RUNNING
**2018-05-24 09:54:45 WARN TaskSchedulerImpl:66 - Initial job has not accepted any resources; check your cluster UI to ensure that workers are registered and have sufficient resources**
The WANRING information will be output repeatedly after .
my Scala code:
import scala.math.random
import org.apache.spark.{SparkConf, SparkContext}
/**
* Created by meng on 2018/5/21.
*/
object SparkPi {
def main(args: Array[String]) {
val conf = new SparkConf()
.setAppName("Spark Pi")
.setMaster("spark://210.14.69.105:7077")
.setJars(List("/Users/meng/Documents/untitled/out/artifacts/untitled_jar/untitled.jar"))
.set("spark.executor.memory", "512M")
val spark = new SparkContext(conf)
val slices = if (args.length > 0) args(0).toInt else 2
val n = 100000 * slices
val count = spark
.parallelize(1 to n, slices)
.map {
i => val x = random * 2 - 1
val y = random * 2 - 1
if (x * x + y * y < 1) 1 else 0
}
.reduce(_ + _)
println("Pi is roughly " + 4.0 * count / n)
spark.stop()
}
}
Thank you very much for asking for help.