Slick: java.util.concurrent.RejectedExecutionException in Quartz Job - scala

I have Play 2.5 App that uses Slick. The play app has few Quartz job scheduled and runs within the app. The Quartz Job uses slick to insert/update data in the database. The Quartz Job fails with the below exception.
[error] o.q.c.ErrorLogger - Job (8a3a3ec7f96a2d1aceb2dc96c5dddaed.becdc8372f54d501222a2ca94c264ff0 threw an exception.
org.quartz.SchedulerException: Job threw an unhandled exception.
at org.quartz.core.JobRunShell.run(JobRunShell.java:213)
at org.quartz.simpl.SimpleThreadPool$WorkerThread.run(SimpleThreadPool.java:573)
Caused by: java.util.concurrent.RejectedExecutionException: Task slick.backend.DatabaseComponent$DatabaseDef$$anon$2#5fae8abe rejected from java.util.concurrent.ThreadPoolExecutor#39c55f20[Terminated, pool size = 0, active threads = 0, queued tasks = 0, completed tasks = 268]
at java.util.concurrent.ThreadPoolExecutor$AbortPolicy.rejectedExecution(ThreadPoolExecutor.java:2047)
at java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:823)
at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1369)
at scala.concurrent.impl.ExecutionContextImpl$$anon$1.execute(ExecutionContextImpl.scala:136)
at slick.backend.DatabaseComponent$DatabaseDef$class.runSynchronousDatabaseAction(DatabaseComponent.scala:230)
at slick.jdbc.JdbcBackend$DatabaseDef.runSynchronousDatabaseAction(JdbcBackend.scala:38)
at slick.backend.DatabaseComponent$DatabaseDef$class.runInContext(DatabaseComponent.scala:207)
at slick.jdbc.JdbcBackend$DatabaseDef.runInContext(JdbcBackend.scala:38)
at slick.backend.DatabaseComponent$DatabaseDef$class.runInternal(DatabaseComponent.scala:75)
at slick.jdbc.JdbcBackend$DatabaseDef.runInternal(JdbcBackend.scala:38)
[error] o.q.c.ErrorLogger - Job (8a3a3ec7f96a2d1aceb2dc96c5dddaed.becdc8372f54d501222a2ca94c264ff0 threw an exception.
org.quartz.SchedulerException: Job threw an unhandled exception.
at org.quartz.core.JobRunShell.run(JobRunShell.java:213)
at org.quartz.simpl.SimpleThreadPool$WorkerThread.run(SimpleThreadPool.java:573)
Caused by: java.util.concurrent.RejectedExecutionException: Task slick.backend.DatabaseComponent$DatabaseDef$$anon$2#5fae8abe rejected from java.util.concurrent.ThreadPoolExecutor#39c55f20[Terminated, pool size = 0, active threads = 0, queued tasks = 0, completed tasks = 268]
at java.util.concurrent.ThreadPoolExecutor$AbortPolicy.rejectedExecution(ThreadPoolExecutor.java:2047)
at java.util.concurrent.ThreadPoolExecutor.reject(ThreadPoolExecutor.java:823)
at java.util.concurrent.ThreadPoolExecutor.execute(ThreadPoolExecutor.java:1369)
at scala.concurrent.impl.ExecutionContextImpl$$anon$1.execute(ExecutionContextImpl.scala:136)
at slick.backend.DatabaseComponent$DatabaseDef$class.runSynchronousDatabaseAction(DatabaseComponent.scala:230)
at slick.jdbc.JdbcBackend$DatabaseDef.runSynchronousDatabaseAction(JdbcBackend.scala:38)
at slick.backend.DatabaseComponent$DatabaseDef$class.runInContext(DatabaseComponent.scala:207)
at slick.jdbc.JdbcBackend$DatabaseDef.runInContext(JdbcBackend.scala:38)
at slick.backend.DatabaseComponent$DatabaseDef$class.runInternal(DatabaseComponent.scala:75)
at slick.jdbc.JdbcBackend$DatabaseDef.runInternal(JdbcBackend.scala:38)
This failure doesnt happen when slick calls are made outside of the Quartz job but only when inside the Quartz job. Some of the initial few Quartz job succeeds but then after few runs the above error is thrown.
what is the causing this issue and why the stacktrace says the pool size is zero as shown below?
Caused by: java.util.concurrent.RejectedExecutionException: Task slick.backend.DatabaseComponent$DatabaseDef$$anon$2#5fae8abe rejected from java.util.concurrent.ThreadPoolExecutor#39c55f20[Terminated, pool size = 0, active threads = 0, queued tasks = 0, completed tasks = 268]
Below is the Slick and Quartz settings
slick.dbs.default.driver="slick.driver.MySQLDriver$"
slick.dbs.default.db.driver="com.mysql.jdbc.Driver"
slick.dbs.default.db.url="jdbc:mysql://mysql-server:3306/database"
slick.dbs.default.db.user=username
slick.dbs.default.db.password=password
slick.dbs.default.db.queueSize = 10000
slick.dbs.default.db.connectionTimeout=5s
// Quartz Settings
scheduler = {
org.quartz.scheduler.instanceId = AUTO
org.quartz.threadPool.class = "org.quartz.simpl.SimpleThreadPool"
org.quartz.threadPool.threadCount = 100
org.quartz.threadPool.threadPriority = 5
org.quartz.threadPool.threadsInheritContextClassLoaderOfInitializingThread = true
org.quartz.dataSource.quartzDataSource.driver=com.mysql.jdbc.Driver
org.quartz.dataSource.quartzDataSource.URL="jdbc:mysql://mysql-server:3306/database"
org.quartz.dataSource.quartzDataSource.user=username
org.quartz.dataSource.quartzDataSource.password=password
org.quartz.jobStore.misfireThreshold = 60000
org.quartz.jobStore.class = "org.quartz.impl.jdbcjobstore.JobStoreTX"
org.quartz.jobStore.driverDelegateClass = "org.quartz.impl.jdbcjobstore.StdJDBCDelegate"
org.quartz.jobStore.dataSource = quartzDataSource
org.quartz.jobStore.tablePrefix = QRTZ_
org.quartz.jobStore.isClustered = true
org.quartz.jobStore.useProperties = true
org.quartz.dataSource.quartzDataSource.maxConnections=3
}

Related

Why Spark structured streaming job is not terminating even after raising exception

I am raising a custom exception to test failure in my structured streaming job as below. I see the query gets terminated but not able to understand why driver script is not failing with a non zero exit code
streamingDF.writeStream
.trigger(Trigger.ProcessingTime(10000L))
.foreachBatch {
(batchDF: DataFrame, batchId: Long) => {
val transformedDF: DataFrame = DoSomeProcessing(batchDF)
if (batchId == 1) {
throw new Exception("Custom Exception as batchId is 1")
}
I get below trace on my console but the driver script is not exiting and no new logs are printed on console.
Exception in thread "main" org.apache.spark.sql.streaming.StreamingQueryException: Custom Exception as batchId is 1
=== Streaming Query ===
Identifier: [id = 6f4c3b4c-bc30-46fe-93ef-8378c23380ab, runId = 1241cb37-493b-4882-ab28-9df8a8c6fb1a]
Current Committed Offsets: ...
Current Available Offsets: ...
Current State: ACTIVE
Thread State: RUNNABLE
Logical Plan:
RepartitionByExpression [timestamp#12], 10
...
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:295)
at org.apache.spark.sql.execution.streaming.StreamExecution$$anon$1.run(StreamExecution.scala:189)
Caused by: java.lang.Exception: Custom Exception as batchId is 1
at MySteamingApp$$anonfun$startSparkStructuredStreaming$1.apply(MySteamingApp.scala:61)
at MySteamingApp$$anonfun$startSparkStructuredStreaming$1.apply(MySteamingApp.scala:57)
at org.apache.spark.sql.execution.streaming.sources.ForeachBatchSink.addBatch(ForeachBatchSink.scala:35)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$5$$anonfun$apply$17.apply(MicroBatchExecution.scala:534)
at org.apache.spark.sql.execution.SQLExecution$$anonfun$withNewExecutionId$1.apply(SQLExecution.scala:78)
at org.apache.spark.sql.execution.SQLExecution$.withSQLConfPropagated(SQLExecution.scala:125)
at org.apache.spark.sql.execution.SQLExecution$.withNewExecutionId(SQLExecution.scala:73)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch$5.apply(MicroBatchExecution.scala:532)
at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:351)
at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.org$apache$spark$sql$execution$streaming$MicroBatchExecution$$runBatch(MicroBatchExecution.scala:531)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply$mcV$sp(MicroBatchExecution.scala:198)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:166)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1$$anonfun$apply$mcZ$sp$1.apply(MicroBatchExecution.scala:166)
at org.apache.spark.sql.execution.streaming.ProgressReporter$class.reportTimeTaken(ProgressReporter.scala:351)
at org.apache.spark.sql.execution.streaming.StreamExecution.reportTimeTaken(StreamExecution.scala:58)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution$$anonfun$runActivatedStream$1.apply$mcZ$sp(MicroBatchExecution.scala:166)
at org.apache.spark.sql.execution.streaming.ProcessingTimeExecutor.execute(TriggerExecutor.scala:56)
at org.apache.spark.sql.execution.streaming.MicroBatchExecution.runActivatedStream(MicroBatchExecution.scala:160)
at org.apache.spark.sql.execution.streaming.StreamExecution.org$apache$spark$sql$execution$streaming$StreamExecution$$runStream(StreamExecution.scala:279)
... 1 more
I think number of task failures were configured more
spark.task.maxFailures default 4 Number of failures of any particular task before giving up on the job. The total number of failures spread across different tasks will not cause the job to fail; a particular task has to fail this number of attempts. Should be greater than or equal to 1. Number of allowed retries = this value - 1.
Further have a look at Is there a way to dynamically stop Spark Structured Streaming?

pyspark on emr with boto3, copy of s3 object result with Futures timed out after [100000 milliseconds]

I have a pyspark application that will transform csv to parquet and before this happen I'm copying some S3 object from a bucket to another.
pyspark with spark 2.4, emr 5.27, maximizeResourceAllocation set to true
I have various csv files size, from 80kb to 500mb.
Nonetheless, my EMR cluster (it doesn't fail on local with spark-submit) fails at 70% completion on a file that is 166mb (a previous at 480mb succeeded).
The job is simple:
def organise_adwords_csv():
s3 = boto3.resource('s3')
bucket = s3.Bucket(S3_ORIGIN_RAW_BUCKET)
for obj in bucket.objects.filter(Prefix=S3_ORIGIN_ADWORDS_RAW + "/"):
key = obj.key
copy_source = {
'Bucket': S3_ORIGIN_RAW_BUCKET,
'Key': key
}
key_tab = obj.key.split("/")
if len(key_tab) < 5:
print("continuing from length", obj)
continue
file_name = ''.join(key_tab[len(key_tab)-1:len(key_tab)])
if file_name == '':
print("continuing", obj)
continue
table = file_name.split("_")[1].replace("-", "_")
new_path = "{0}/{1}/{2}".format(S3_DESTINATION_ORDERED_ADWORDS_RAW_PATH, table, file_name)
print("new_path", new_path) <- the last print will end here
try:
s3.meta.client.copy(copy_source, S3_DESTINATION_RAW_BUCKET, new_path)
print("copy done")
except Exception as e:
print(e)
print("an exception occured while copying")
if __name__=='__main__':
organise_adwords_csv()
print("copy Final done") <- never printed
spark = SparkSession.builder.appName("adwords_transform") \
...
but, in the stdout, no errors / exception are showing.
In stderr logs:
19/10/09 16:16:57 INFO ApplicationMaster: Waiting for spark context initialization...
19/10/09 16:18:37 ERROR ApplicationMaster: Uncaught exception:
java.util.concurrent.TimeoutException: Futures timed out after [100000 milliseconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:223)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:227)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
at org.apache.spark.deploy.yarn.ApplicationMaster.runDriver(ApplicationMaster.scala:468)
at org.apache.spark.deploy.yarn.ApplicationMaster.org$apache$spark$deploy$yarn$ApplicationMaster$$runImpl(ApplicationMaster.scala:305)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply$mcV$sp(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:779)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1844)
at org.apache.spark.deploy.yarn.ApplicationMaster.doAsUser(ApplicationMaster.scala:778)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:244)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:803)
at org.apache.spark.deploy.yarn.ApplicationMaster.main(ApplicationMaster.scala)
19/10/09 16:18:37 INFO ApplicationMaster: Final app status: FAILED, exitCode: 13, (reason: Uncaught exception: java.util.concurrent.TimeoutException: Futures timed out after [100000 milliseconds]
at scala.concurrent.impl.Promise$DefaultPromise.ready(Promise.scala:223)
at scala.concurrent.impl.Promise$DefaultPromise.result(Promise.scala:227)
at org.apache.spark.util.ThreadUtils$.awaitResult(ThreadUtils.scala:220)
at org.apache.spark.deploy.yarn.ApplicationMaster.runDriver(ApplicationMaster.scala:468)
at org.apache.spark.deploy.yarn.ApplicationMaster.org$apache$spark$deploy$yarn$ApplicationMaster$$runImpl(ApplicationMaster.scala:305)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply$mcV$sp(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anonfun$run$1.apply(ApplicationMaster.scala:245)
at org.apache.spark.deploy.yarn.ApplicationMaster$$anon$3.run(ApplicationMaster.scala:779)
at java.security.AccessController.doPrivileged(Native Method)
at javax.security.auth.Subject.doAs(Subject.java:422)
at org.apache.hadoop.security.UserGroupInformation.doAs(UserGroupInformation.java:1844)
at org.apache.spark.deploy.yarn.ApplicationMaster.doAsUser(ApplicationMaster.scala:778)
at org.apache.spark.deploy.yarn.ApplicationMaster.run(ApplicationMaster.scala:244)
at org.apache.spark.deploy.yarn.ApplicationMaster$.main(ApplicationMaster.scala:803)
at org.apache.spark.deploy.yarn.ApplicationMaster.main(ApplicationMaster.scala)
)
19/10/09 16:18:37 INFO ShutdownHookManager: Shutdown hook called
I'm completely blind, I don't understand what is failing / why.
How can I figure that out? On local it works like a charm (but super slow of course)
Edit:
After many tries I can confirm that the function:
s3.meta.client.copy(copy_source, S3_DESTINATION_RAW_BUCKET, new_path)
make the EMR cluster timeout, even tho it processed 80% of the files already.
Does anyone have a recommendation about this?
s3.meta.client.copy(copy_source, S3_DESTINATION_RAW_BUCKET, new_path)
This will fail for any source object larger than 5 GB. please use multipart upload in AWS. See https://boto3.amazonaws.com/v1/documentation/api/latest/reference/services/s3.html#multipartupload

Quartz Scheduler failed to initialize

Getting these errors:
2018-01-22 18:00:59,797 [ServerService Thread Pool -- 79] ERROR org.quartz.ee.servlet.QuartzInitializerListener - Quartz Scheduler failed to initialize: org.quartz.SchedulerException: SchedulerPlugin class 'org.quartz.plugins.xml.XMLSchedulingDataProcessorPlugin' could not be instantiated. [See nested exception: java.lang.ClassNotFoundException: Unable to load class org.quartz.plugins.xml.XMLSchedulingDataProcessorPlugin by any known loaders.]
2018-01-22 18:00:59,797 [ServerService Thread Pool -- 79] ERROR stderr - org.quartz.SchedulerException: SchedulerPlugin class 'org.quartz.plugins.xml.XMLSchedulingDataProcessorPlugin' could not be instantiated. [See nested exception: java.lang.ClassNotFoundException: Unable to load class org.quartz.plugins.xml.XMLSchedulingDataProcessorPlugin by any known loaders.]
2018-01-22 18:00:59,805 [ServerService Thread Pool -- 79] ERROR stderr - Caused by: java.lang.ClassNotFoundException: Unable to load class org.quartz.plugins.xml.XMLSchedulingDataProcessorPlugin by any known loaders.
2018-01-22 18:00:59,805 [ServerService Thread Pool -- 79] ERROR stderr - Caused by: java.lang.LinkageError: Failed to link org/quartz/plugins/xml/XMLSchedulingDataProcessorPlugin (Module "deployment.Reports.ear:main" from Service Module Loader)
2018-01-22 18:00:59,806 [ServerService Thread Pool -- 79] ERROR stderr - Caused by: java.lang.NoClassDefFoundError: org/quartz/jobs/FileScanListener
2018-01-22 18:00:59,807 [ServerService Thread Pool -- 79] ERROR stderr - Caused by: java.lang.ClassNotFoundException: org.quartz.jobs.FileScanListener from [Module "deployment.Reports.ear:main" from Service Module Loader]
quartz.properties file:
org.quartz.scheduler.instanceName = Scheduler
org.quartz.scheduler.instanceId = AUTO
org.quartz.scheduler.skipUpdateCheck = true
org.quartz.threadPool.class = org.quartz.simpl.SimpleThreadPool
org.quartz.threadPool.threadCount = 10
org.quartz.threadPool.threadPriority = 5
org.quartz.jobStore.misfireThreshold = 60000
org.quartz.jobStore.class = org.quartz.impl.jdbcjobstore.JobStoreTX
org.quartz.jobStore.driverDelegateClass = org.quartz.impl.jdbcjobstore.oracle.OracleDelegate
org.quartz.jobStore.useProperties = false
org.quartz.jobStore.dataSource = quartzDataSource
org.quartz.jobStore.tablePrefix = QUARTZ.QRTZ_
#org.quartz.jobStore.tablePrefix = QRTZ_
org.quartz.jobStore.isClustered = true
org.quartz.jobStore.clusterCheckinInterval = 20000
org.quartz.dataSource.quartzDataSource.jndiURL=java:QuartzDataSource
org.quartz.dataSource.quartzDataSource.java.naming.factory.initial=org.jnp.interfaces.NamingContextFactory
org.quartz.plugin.jobInitializer.class = org.quartz.plugins.xml.XMLSchedulingDataProcessorPlugin
org.quartz.plugin.jobInitializer.fileNames = quartz-jobs-xml
org.quartz.plugin.jobInitializer.failOnFileNotFound = true
org.quartz.plugin.jobInitializer.scanInterval = 0
org.quartz.plugin.jobInitializer.wrapInUserTransaction =false
My quartz-jobs.xml file is in the same directory as my quartz.properties.xml file. I tried playing around with that path a little. But I think the errors are just saying it can't instantiate my jobs.
I needed to add a new quartz library to my build to include the XMLSchedulingDataProcessorPlugin that I reference in my quartz.properties.
In my root build.gradle I add this to my ext.libraries section:
quartz_jobs: 'org.quartz-scheduler:quartz-jobs:2.3.0'
Then in my web services build.gradle where I use quartz, I add the library to my providedCompile section:
libraries.quartz-jobs

Map and transform methods with using serializable class on DStream elements

I am writing app that will be extract logs, so I implemented function (Lisitng 1) which is taking string as parametr and extracts valuable informations (regexs: Listing 2) from it. I wanted that this method could be send to other workers so I impelemnt serializable class.
I have problem with apply this method on DStreams. Here is my streams minning solution:
def streamMinner(): Unit = {
val ssc = new StreamingContext(sc, Seconds(2))
val logsStream = ssc.textFileStream("logs/")
// Not works
val extractLogs = logsStream.map( log => new Matcher().matchLog(log))
extractLogs.print(1)
// Works
// val words = logsStream.transform( rdd => rdd.map( log => matchLog(log)))
// words.print()
ssc.start()
ssc.awaitTermination()
}
Problem is in line where every element of logsStream is maped with new object of Matcher class (new Matcher().matchLog(log)
Apache Spark gave my below errors:
ERROR YarnScheduler: Lost executor 2 on host1: Container marked as failed: container_e743_1499728610705_0043_01_000003 on host: host1. Exit status: 50. Diagnostics: Exception from container-launch.
Container id: container_e743_1499728610705_0043_01_000003
Exit code: 50
Stack trace: ExitCodeException exitCode=50:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:600)
at org.apache.hadoop.util.Shell.run(Shell.java:511)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:783)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:303)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 50
ERROR YarnScheduler: Lost executor 5 on host2: Container marked as failed: container_e743_1499728610705_0043_01_000006 on host: host2. Exit status: 50. Diagnostics: Exception from container-launch.
Container id: container_e743_1499728610705_0043_01_000006
Exit code: 50
Stack trace: ExitCodeException exitCode=50:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:600)
at org.apache.hadoop.util.Shell.run(Shell.java:511)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:783)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:303)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 50
...
ERROR YarnScheduler: Lost executor 6 ...
ERROR TaskSetManager: Task 0 in stage 0.0 failed 4 times; aborting job
17/07/11 09:41:09 ERROR JobScheduler: Error running job streaming job 1499758850000 ms.0
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, host1): ExecutorLostFailure (executor 6 exited caused by one of the running tasks) Reason: Container marked as failed: container_e743_1499728610705_0043_01_000007 on host: host1. Exit status: 50. Diagnostics: Exception from container-launch.
Container id: container_e743_1499728610705_0043_01_000007
Exit code: 50
Stack trace: ExitCodeException exitCode=50:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:600)
at org.apache.hadoop.util.Shell.run(Shell.java:511)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:783)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:303)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 50
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1433)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1421)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1420)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1420)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:801)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:801)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:801)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1642)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1601)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1590)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:622)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1856)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1869)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1882)
at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1335)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:323)
at org.apache.spark.rdd.RDD.take(RDD.scala:1309)
at org.apache.spark.streaming.dstream.DStream$$anonfun$print$2$$anonfun$foreachFunc$5$1.apply(DStream.scala:768)
at org.apache.spark.streaming.dstream.DStream$$anonfun$print$2$$anonfun$foreachFunc$5$1.apply(DStream.scala:767)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:426)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:49)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
at scala.util.Try$.apply(Try.scala:161)
at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:227)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:227)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:227)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:226)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
org.apache.spark.SparkException: Job aborted due to stage failure: Task 0 in stage 0.0 failed 4 times, most recent failure: Lost task 0.3 in stage 0.0 (TID 3, host1): ExecutorLostFailure (executor 6 exited caused by one of the running tasks) Reason: Container marked as failed: container_e743_1499728610705_0043_01_000007 on host: host1. Exit status: 50. Diagnostics: Exception from container-launch.
Container id: container_e743_1499728610705_0043_01_000007
Exit code: 50
Stack trace: ExitCodeException exitCode=50:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:600)
at org.apache.hadoop.util.Shell.run(Shell.java:511)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:783)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:303)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 50
Driver stacktrace:
at org.apache.spark.scheduler.DAGScheduler.org$apache$spark$scheduler$DAGScheduler$$failJobAndIndependentStages(DAGScheduler.scala:1433)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1421)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$abortStage$1.apply(DAGScheduler.scala:1420)
at scala.collection.mutable.ResizableArray$class.foreach(ResizableArray.scala:59)
at scala.collection.mutable.ArrayBuffer.foreach(ArrayBuffer.scala:47)
at org.apache.spark.scheduler.DAGScheduler.abortStage(DAGScheduler.scala:1420)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:801)
at org.apache.spark.scheduler.DAGScheduler$$anonfun$handleTaskSetFailed$1.apply(DAGScheduler.scala:801)
at scala.Option.foreach(Option.scala:236)
at org.apache.spark.scheduler.DAGScheduler.handleTaskSetFailed(DAGScheduler.scala:801)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.doOnReceive(DAGScheduler.scala:1642)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1601)
at org.apache.spark.scheduler.DAGSchedulerEventProcessLoop.onReceive(DAGScheduler.scala:1590)
at org.apache.spark.util.EventLoop$$anon$1.run(EventLoop.scala:48)
at org.apache.spark.scheduler.DAGScheduler.runJob(DAGScheduler.scala:622)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1856)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1869)
at org.apache.spark.SparkContext.runJob(SparkContext.scala:1882)
at org.apache.spark.rdd.RDD$$anonfun$take$1.apply(RDD.scala:1335)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:150)
at org.apache.spark.rdd.RDDOperationScope$.withScope(RDDOperationScope.scala:111)
at org.apache.spark.rdd.RDD.withScope(RDD.scala:323)
at org.apache.spark.rdd.RDD.take(RDD.scala:1309)
at org.apache.spark.streaming.dstream.DStream$$anonfun$print$2$$anonfun$foreachFunc$5$1.apply(DStream.scala:768)
at org.apache.spark.streaming.dstream.DStream$$anonfun$print$2$$anonfun$foreachFunc$5$1.apply(DStream.scala:767)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply$mcV$sp(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1$$anonfun$apply$mcV$sp$1.apply(ForEachDStream.scala:50)
at org.apache.spark.streaming.dstream.DStream.createRDDWithLocalProperties(DStream.scala:426)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply$mcV$sp(ForEachDStream.scala:49)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
at org.apache.spark.streaming.dstream.ForEachDStream$$anonfun$1.apply(ForEachDStream.scala:49)
at scala.util.Try$.apply(Try.scala:161)
at org.apache.spark.streaming.scheduler.Job.run(Job.scala:39)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply$mcV$sp(JobScheduler.scala:227)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:227)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler$$anonfun$run$1.apply(JobScheduler.scala:227)
at scala.util.DynamicVariable.withValue(DynamicVariable.scala:57)
at org.apache.spark.streaming.scheduler.JobScheduler$JobHandler.run(JobScheduler.scala:226)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
scala> 17/07/11 09:41:11 ERROR TransportResponseHandler: Still have 1 requests outstanding when connection from host3/11.11.11.11:11111 is closed
17/07/11 09:41:11 ERROR YarnScheduler: Lost executor 4 on host3: Slave lost
17/07/11 09:41:12 ERROR TransportClient: Failed to send RPC 7741519719369750843 to host3/11.11.11.11:11111: java.nio.channels.ClosedChannelException
java.nio.channels.ClosedChannelException
17/07/11 09:41:12 ERROR YarnScheduler: Lost executor 1 on host2: Slave lost
17/07/11 09:41:12 ERROR TransportClient: Failed to send RPC 7734757459881277232 to host3//11.11.11.11:11111: java.nio.channels.ClosedChannelException
java.nio.channels.ClosedChannelException
17/07/11 09:41:12 ERROR YarnScheduler: Lost executor 3 on host4: Slave lost
17/07/11 09:41:12 ERROR TransportClient: Failed to send RPC 5816053641531447955 to host3//11.11.11.11:11111: java.nio.channels.ClosedChannelException
java.nio.channels.ClosedChannelException
17/07/11 09:41:12 ERROR YarnScheduler: Lost executor 7 on host2: Slave lost
17/07/11 09:41:13 ERROR TransportClient: Failed to send RPC 8774007142277591342 to host3/11.11.11.11:11111: java.nio.channels.ClosedChannelException
java.nio.channels.ClosedChannelException
17/07/11 09:41:13 ERROR YarnScheduler: Lost executor 8 on host1: Slave lost
17/07/11 09:41:19 ERROR YarnScheduler: Lost executor 1 on host3: Container marked as failed: container_e743_1499728610705_0043_02_000002 on host: host3. Exit status: 50. Diagnostics: Exception from container-launch.
Container id: container_e743_1499728610705_0043_02_000002
Exit code: 50
Stack trace: ExitCodeException exitCode=50:
at org.apache.hadoop.util.Shell.runCommand(Shell.java:600)
at org.apache.hadoop.util.Shell.run(Shell.java:511)
at org.apache.hadoop.util.Shell$ShellCommandExecutor.execute(Shell.java:783)
at org.apache.hadoop.yarn.server.nodemanager.DefaultContainerExecutor.launchContainer(DefaultContainerExecutor.java:212)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:303)
at org.apache.hadoop.yarn.server.nodemanager.containermanager.launcher.ContainerLaunch.call(ContainerLaunch.java:82)
at java.util.concurrent.FutureTask.run(FutureTask.java:262)
at java.util.concurrent.ThreadPoolExecutor.runWorker(ThreadPoolExecutor.java:1145)
at java.util.concurrent.ThreadPoolExecutor$Worker.run(ThreadPoolExecutor.java:615)
at java.lang.Thread.run(Thread.java:745)
Container exited with a non-zero exit code 50
When I comment lines:
val extractLogs = logsStream.map( log => new Matcher().matchLog(log))
extractLogs.print(1)
and I uncomment lines:
// val words = logsStream.transform( rdd => rdd.map( log => matchLog(log)))
// words.print()
Everything works fine. My question is why? I'm afraid that solution that works may not be parallelized on cluster because method matchLog is not serializable. Someone has a similar problem or know how to deal with it?
Lisitng 1:
case class logValues2(time_stamp: String, action: String, protocol: String, connection_id: String, src_ip: String, dst_ip: String, src_port: String, dst_port: String, duration: String, bytes: String, user: String) extends Serializable
class Matcher extends Serializable {
def matchLog(x: String): logValues2 = {
var dst_ip = " "
var dst_port = " "
var time_stamp = time_stamp_reg.findAllIn(x).mkString(",")
var action = action_reg.findAllIn(x).mkString(",")
var protocol = protocol_reg.findAllIn(x).mkString(",")
var connection_id = connection_id_reg.findAllIn(x).mkString(",")
var ips = ips_reg.findAllIn(x).mkString(" ").split(""" """)
var src_ip = ips(0)
if (ips.length > 1) {
dst_ip = ips(1)
} else {
dst_ip = " "
}
var ports = ports_reg.findAllIn(x).mkString(" ").split(""" """)
var src_port = ports(0)
if (ports.length > 1) {
dst_port = ports(1)
} else {
dst_port = " "
}
var duration = duration_reg.findAllIn(x).mkString(",")
var bytes = bytes_reg.findAllIn(x).mkString(",")
var user = user_reg.findAllIn(x).mkString(",")
var logObject = logValues2(time_stamp, action, protocol, connection_id, src_ip, dst_ip, src_port, dst_port, duration, bytes, user)
return logObject
}
Above method is implemented also separately (no within Matcher class).
UPDATE:
My Regular expressions: Listing 2:
val time_stamp_reg = """^.*?(?=\s\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3}\s%)""".r
val action_reg = """((?<=:\s)\w{4,10}(?=\s\w{2})|(?<=\w\s)(\w{7,9})(?=\s[f]))""".r
val protocol_reg = """(?<=[\w:]\s)(\w+)(?=\s[cr])""".r
val connection_id_reg = """(?<=\w\s)(\d+)(?=\sfor)""".r
val ips_reg = """(?<=[\d\w][:\s])(\d{1,3}\.\d{1,3}\.\d{1,3}\.\d{1,3})(?=\/\d+|\z| \w)""".r
val ports_reg = """(?<=\d\/)(\d{1,6})(?=\z|[\s(])""".r
val duration_reg = """(?<=duration\s)(\d{1,2}:\d{1,2}:\d{1,2})(?=\s|\z)""".r
val bytes_reg = """(?<=bytes\s)(\d+)(?=\s|\z)""".r
val user_reg = """(?<=\\\\)(\d+)(?=\W)""".r

jboss seam + quartz scheduler 2.2.1 + clustering

I have problem with configuration quartz version 2.2.1 with seam framevork.
Now a get error in log:
[24.4.14 12:51:37:843 SELČ] 0000000b SystemOut O ERROR manage:3853 - ClusterManager: Error managing cluster: Failure updating scheduler state when checking-in: ORA-01400: cannot insert NULL into ("JDC"."QRTZ_SCHEDULER_STATE"."SCHED_NAME")
org.quartz.JobPersistenceException: Failure updating scheduler state when checking-in: ORA-01400: cannot insert NULL into
("JDC"."QRTZ_SCHEDULER_STATE"."SCHED_NAME")
[See nested exception: java.sql.SQLIntegrityConstraintViolationException: ORA-01400: cannot
insert NULL into ("JDC"."QRTZ_SCHEDULER_STATE"."SCHED_NAME")
]
at org.quartz.impl.jdbcjobstore.JobStoreSupport.clusterCheckIn(JobStoreSupport.java:3373)
at org.quartz.impl.jdbcjobstore.JobStoreSupport.doCheckin(JobStoreSupport.java:3226)
at org.quartz.impl.jdbcjobstore.JobStoreSupport$ClusterManager.manage(JobStoreSupport.java:3847)
at org.quartz.impl.jdbcjobstore.JobStoreSupport$ClusterManager.initialize(JobStoreSupport.java:3832)
at org.quartz.impl.jdbcjobstore.JobStoreSupport.schedulerStarted(JobStoreSupport.java:639)
at org.quartz.core.QuartzScheduler.start(QuartzScheduler.java:513)
at org.quartz.impl.StdScheduler.start(StdScheduler.java:143)
at org.jboss.seam.async.QuartzDispatcher.initScheduler(QuartzDispatcher.java:70)
at sun.reflect.NativeMethodAccessorImpl.invoke0(Native Method)
at sun.reflect.NativeMethodAccessorImpl.invoke(NativeMethodAccessorImpl.java:60)
at sun.reflect.DelegatingMethodAccessorImpl.invoke(DelegatingMethodAccessorImpl.java:37)
at java.lang.reflect.Method.invoke(Method.java:611)
at org.jboss.seam.util.Reflections.invoke(Reflections.java:22)
at org.jboss.seam.util.Reflections.invokeAndWrap(Reflections.java:144)
at org.jboss.seam.Component.callComponentMethod(Component.java:2275)
at org.jboss.seam.Component.callCreateMethod(Component.java:2198)
at org.jboss.seam.Component.newInstance(Component.java:2158)
at org.jboss.seam.contexts.Contexts.startup(Contexts.java:304)
at org.jboss.seam.contexts.Contexts.startup(Contexts.java:278)
at org.jboss.seam.contexts.ServletLifecycle.endInitialization(ServletLifecycle.java:143)
at org.jboss.seam.init.Initialization.init(Initialization.java:744)
at org.jboss.seam.servlet.SeamListener.contextInitialized(SeamListener.java:36)
at com.ibm.ws.webcontainer.webapp.WebApp.notifyServletContextCreated(WebApp.java:1682)
at com.ibm.ws.webcontainer.webapp.WebAppImpl.initialize(WebAppImpl.java:410)
at com.ibm.ws.webcontainer.webapp.WebGroupImpl.addWebApplication(WebGroupImpl.java:88)
at com.ibm.ws.webcontainer.VirtualHostImpl.addWebApplication(VirtualHostImpl.java:169)
at com.ibm.ws.webcontainer.WSWebContainer.addWebApp(WSWebContainer.java:749)
at com.ibm.ws.webcontainer.WSWebContainer.addWebApplication(WSWebContainer.java:634)
at com.ibm.ws.webcontainer.component.WebContainerImpl.install(WebContainerImpl.java:422)
at com.ibm.ws.webcontainer.component.WebContainerImpl.start(WebContainerImpl.java:714)
at com.ibm.ws.runtime.component.ApplicationMgrImpl.start(ApplicationMgrImpl.java:1163)
at com.ibm.ws.runtime.component.DeployedApplicationImpl.fireDeployedObjectStart(DeployedApplicationImpl.java:1369)
at com.ibm.ws.runtime.component.DeployedModuleImpl.start(DeployedModuleImpl.java:639)
at com.ibm.ws.runtime.component.DeployedApplicationImpl.start(DeployedApplicationImpl.java:967)
at com.ibm.ws.runtime.component.ApplicationMgrImpl.startApplication(ApplicationMgrImpl.java:769)
at com.ibm.ws.runtime.component.ApplicationMgrImpl$5.run(ApplicationMgrImpl.java:2160)
at com.ibm.ws.security.auth.ContextManagerImpl.runAs(ContextManagerImpl.java:5468)
at com.ibm.ws.security.auth.ContextManagerImpl.runAsSystem(ContextManagerImpl.java:5594)
at com.ibm.ws.security.core.SecurityContext.runAsSystem(SecurityContext.java:255)
at com.ibm.ws.runtime.component.ApplicationMgrImpl.start(ApplicationMgrImpl.java:2165)
at com.ibm.ws.runtime.component.CompositionUnitMgrImpl.start(CompositionUnitMgrImpl.java:446)
at com.ibm.ws.runtime.component.CompositionUnitImpl.start(CompositionUnitImpl.java:123)
at com.ibm.ws.runtime.component.CompositionUnitMgrImpl.start(CompositionUnitMgrImpl.java:389)
at com.ibm.ws.runtime.component.CompositionUnitMgrImpl.access$500(CompositionUnitMgrImpl.java:117)
at com.ibm.ws.runtime.component.CompositionUnitMgrImpl$CUInitializer.run(CompositionUnitMgrImpl.java:995)
at com.ibm.wsspi.runtime.component.WsComponentImpl$_AsynchInitializer.run(WsComponentImpl.java:496)
at com.ibm.ws.util.ThreadPool$Worker.run(ThreadPool.java:1700)
Caused by:
java.sql.SQLIntegrityConstraintViolationException: ORA-01400: cannot insert NULL into ("JDC"."QRTZ_SCHEDULER_STATE"."SCHED_NAME")
at oracle.jdbc.driver.SQLStateMapping.newSQLException(SQLStateMapping.java:85)
at oracle.jdbc.driver.DatabaseError.newSQLException(DatabaseError.java:133)
at oracle.jdbc.driver.DatabaseError.throwSqlException(DatabaseError.java:206)
at oracle.jdbc.driver.T4CTTIoer.processError(T4CTTIoer.java:455)
at oracle.jdbc.driver.T4CTTIoer.processError(T4CTTIoer.java:413)
at oracle.jdbc.driver.T4C8Oall.receive(T4C8Oall.java:1034)
at oracle.jdbc.driver.T4CPreparedStatement.doOall8(T4CPreparedStatement.java:194)
at oracle.jdbc.driver.T4CPreparedStatement.executeForRows(T4CPreparedStatement.java:953)
at oracle.jdbc.driver.OracleStatement.doExecuteWithTimeout(OracleStatement.java:1222)
at oracle.jdbc.driver.OraclePreparedStatement.executeInternal(OraclePreparedStatement.java:3387)
at oracle.jdbc.driver.OraclePreparedStatement.executeUpdate(OraclePreparedStatement.java:3468)
at oracle.jdbc.driver.OraclePreparedStatementWrapper.executeUpdate(OraclePreparedStatementWrapper.java:1350)
at com.ibm.ws.rsadapter.jdbc.WSJdbcPreparedStatement.pmiExecuteUpdate(WSJdbcPreparedStatement.java:1185)
at com.ibm.ws.rsadapter.jdbc.WSJdbcPreparedStatement.executeUpdate(WSJdbcPreparedStatement.java:802)
at org.quartz.impl.jdbcjobstore.StdJDBCDelegate.insertSchedulerState(StdJDBCDelegate.java:3227)
at org.quartz.impl.jdbcjobstore.JobStoreSupport.clusterCheckIn(JobStoreSupport.java:3368)
... 46 more
My configuration quartz is:
#==============================================================
# Configure Main Scheduler Properties
#==============================================================
org.quartz.scheduler.instanceName = Sched1
org.quartz.scheduler.instanceId = AUTO
org.quartz.scheduler.skipUpdateCheck = true
org.quartz.scheduler.userTransactionURL = jta/usertransaction
#==============================================================
# Configure ThreadPool
#==============================================================
org.quartz.threadPool.class = org.quartz.simpl.SimpleThreadPool
org.quartz.threadPool.threadCount = 5
org.quartz.threadPool.threadPriority = 5
org.quartz.threadPool.threadsInheritContextClassLoaderOfInitializingThread = true
#==============================================================
# Configure JobStore
#==============================================================
org.quartz.jobStore.misfireThreshold = 60000
org.quartz.jobStore.class = org.quartz.impl.jdbcjobstore.JobStoreTX
org.quartz.jobStore.driverDelegateClass = org.quartz.impl.jdbcjobstore.oracle.OracleDelegate
org.quartz.jobStore.useProperties = false
org.quartz.jobStore.dataSource = quartzDS
#org.quartz.jobStore.nonManagedTXDataSource = quartzDSNoTx
org.quartz.jobStore.tablePrefix = QRTZ_
org.quartz.jobStore.isClustered = true
org.quartz.jobStore.clusterCheckinInterval = 15000
#============================================================================
# Configure Datasources
#============================================================================
org.quartz.dataSource.quartzDS.jndiURL= jdc
#org.quartz.dataSource.quartzDSNoTx.jndiURL= java:/jdcNoTX
#org.quartz.plugin.jobInitializer.class = org.quartz.plugins.xml.XMLSchedulingDataProcessorPlugin
#org.quartz.plugin.jobInitializer.fileNames = jobSchedule.xml
Show your QuartzJobs config file and tell when en error occurs? While compile or when the job should execute?