My batch task was triggered by end user, so I do not want to execute all batch jobs when application startup (with spring.batch.job.enabled=false).
But I hope there is a solution to deal with this below situation,
When application started spring-batch could continue the interrupted batch job caused by application restart or or exceptional interruption.
Resume of failed/interrupted job in Spring Batch is achieved by submitting same job with same job parameters.
Therefore you can do the following to resubmit failed jobs (assuming you are using DB to store job meta data)
By joining BATCH_JOB_INSTANCE and BATCH_JOB_EXECUTION table, find out all job instances with no completed job executions
find out the latest BATCH_JOB_EXECUTIONS for each of the above incomplete job instance, and lookup the corresponding job parameters from BATCH_JOB_EXECUTION_PARAMS
Resubmit the job using job name from BATCH_JOB_INSTANCE, and job parameters from BATCH_JOB_EXECUTION_PARAMS
Related
I have a requirement where i need to watch for the arrival of a particular file. I am planning to use Autosys file trigger job. But i need to kick start a dependent job once FT job finds the occurrence of a file. But as per the autosys manual, when a file is detected only an alarm is triggered .is there a way to kick start a script once a FT job detects a file???
I have 5 instances of an application using quartz in cluster mode both having the quartz scheduler running. (with postgresql)
org.quartz.jobStore.isClustered:true
org.quartz.scheduler.instanceName: myInstanceName
org.quartz.scheduler.instanceId: AUTO
So I have a job which starts and do some operations, update itself if necessary with new scheduled time or else deletes itself. (One job can contain only one trigger.)
The application has a UI interface to allow the user to cancel the job.
When the interrupt command is send from the UI;
If job is not currently working; I can pause the job or cancel.
If my job is currently working at that time, how can I stop the job with the correct instance and get the current state of the job? Basically I want to catch at that moment and save that data at that time, which user is actually interrupt moment
Does scheduler.interrupt(jobKey) interrupt my job which implements InterruptableJob correctly ?
Is scheduler.interrupt() exactly knows which instance should currently running the job and find the correct instance and get the right state of the job ?
Can u correct me, or which way should I go with ?
interrupt method implementations and getCurrentlyExecutingJobs() in quartz are not cluster aware,
which means the method has to be run on the instance which is executing that job, in other words only jobs with specified job key running in the current instance will be interrupted.
An interrupt request can be broadcasted to all running instances of quartz to cancel all instances of running jobs.
from: https://www.quartz-scheduler.org/api/2.1.7/org/quartz/Scheduler.html#interrupt(org.quartz.JobKey)
This method is not cluster aware. That is, it will only interrupt
instances of the identified InterruptableJob currently executing in
this Scheduler instance, not across the entire cluster.
I have a spring scheduler task configured with either of fixedDelay or cron, and have multiple instances of this app running on multiple JVMs.
The default behavior is all the instances are executing the scheduler task.
Is there a way by which we can control this behavior so that only one instance will execute the scheduler task and others don't.
Please let me know if you know any approaches.
Thank you
We had similar problem. We fixed it like this:
Removed all #Scheduled beans from our Spring Boot services.
Created AWS Lambda function scheduled with desired schedule.
Lambda function hits our top level domain with scheduling request.
Load balancer forwards this request to one of the service instances.
This way we are sure that scheduled task is executed only once across the cluster of our services.
I have faced similar problem where same scheduled batch job was running on two server where it was intended to be running on one node at a time. But later on I found a solution to not to execute the job if it is already running on other server.
Job someJob = ...
Set<JobExecution> jobs = jobExplorer.findRunningJobExecutions("someJobName");
if (jobs == null || jobs.isEmpty()) {
jobLauncher.run(someJob, jobParametersBuilder.toJobParameters());
}
}
So before launching the job, a check is needed if the job is already in execution on other node.
Please note that this approach will work only with DB based job repository.
We had the same problem our three instance were running same job and doing the tasks three times every day. We solved it by making use of Spring batch. Spring batch can have only unique job id so if you start the job with a job id like date it will restricts duplicate jobs to start with same id. In our case we used date like '2020-1-1' (since it runs only once a day) . All three instance tries to start the job with id '2020-1-1' but spring rejects two duplicate job stating already job '2020-1-1' is running.
If my understanding is correct on your question, that you want to run this scheduled job on a single instance, then i think you should look at ShedLock
ShedLock makes sure that your scheduled tasks are executed at most once at the same time. If a task is being executed on one node, it acquires a lock which prevents execution of the same task from another node (or thread). Please note, that if one task is already being executed on one node, execution on other nodes does not wait, it is simply skipped.
I am trying to run pyspark on yarn with oozie, after submitting the workflow, there are 2 jobs in the hadoop job queue, one is the oozie job , which is with the application type "map reduce", and another job triggered by the previous one, with application type "Spark", while the first job is running, the second job remains in 'accepted" status. here comes the problem, while the first job is waiting for the second job to finish to proceed, the second is waiting for the first one to finish to run, I may be stuck in a dead lock, how could I get rid of this trouble, is there anyway the hadoop job with application type "mapreduce" run parallel with other jobs of different application type?
Any advice is appreciated, thanks!
Please check the value for property into Yarn scheduler configuration. I guess you need to increase it to something like .9 or so.
Property: yarn.scheduler.capacity.maximum-am-resource-percent
You would need to start Yarn, MapReduce and Oozie after updating the property.
More info: Setting Application Limits.
I can't get the information out of the documentation. Can anyone tell me how Spring-XD executes jobs? Does it assign a job to a certain container and is this job only executed on the container it is deployed to, or is each job execution assigned to another container? Can I somehow control that a certain job may be executed in parallel (with different arguments) and others may not ?
Thanks!
Peter
I am sure you would have seen some of the documentation here:
https://github.com/spring-projects/spring-xd/wiki/Batch-Jobs
To answer your questions:
Can anyone tell me how Spring-XD executes jobs? Does it assign a job to a certain container and is this job only executed on the container it is deployed to, or is each job execution assigned to another container?
After you create a new job definition using this:
xd>job create dailyfeedjob --definition "myfeedjobmodule" --deploy
the batch job module myfeedjobmodule gets deployed into the XD container. Once deployed, there is a job launching queue setup in the message broker: redis, rabbit or local. The name of the queue is job:dailyfeedjob in the message broker. Since this queue is bound to the job module deployed in the XD container, a request message sent to this queue is picked by the job module deployed inside that specific container.
Now, you can send the job launching request message (with job parameters) into the job:dailyfeedjob queue by simply setting up a stream that sends a message into this queue. For example: a trigger (fixed-delay, cron, date triggers) could do that. This also a job launch command from the shell which launches job only once.
This section would explain it more: https://github.com/spring-projects/spring-xd/wiki/Batch-Jobs#launching-a-job
Hence, the job is launched (every time it receives the job launching request) only inside the container where the job module is deployed and you can expect original the spring batch flow when the job is executed. (refer to shell doc for all the job related commands)
Can I somehow control that a certain job may be executed in parallel (with different arguments) and others may not ?
If it is for the different job parameters for the same job definition, then it would go to the same container where the job module is deployed.
But, you can still create a new job definition with the same batch job module.
xd>job create myotherdailyfeedjob --definition "myfeedjobmodule" --deploy
The only difference being it will be under that namespace. and, the job launching queue name would job:myotherdailyfeedjob. It all depends on how do you want to organize running your batch jobs.
Also, for parallel processing batch jobs you can use:
http://docs.spring.io/spring-batch/reference/html/scalability.html
and, XD provides single step partitioning support for running batch jobs:
Include this in your job module:
<import resource="classpath:/META-INF/spring-xd/batch/singlestep-partition-support.xml"/>
with partitioner and tasklet beans defined.
You can try out some of the XD batch samples from here:
https://github.com/spring-projects/spring-xd-samples