I'm implementing a service that would reject job requests from being processed if an existing job is running. Unfortunately, I'm not sure if there is a way to tell the difference between a job that is actively running and a job that ended due to an unexpected shutdown like turning Tomcat off. The statuses in the tables are the same with status = STARTED and exit_code = UNKNOWN.
Set<JobExecution> jobExecutions = jobExplorer.findRunningJobExecutions("MY_JOB");
Is there a way to tell the two apart or implementation that would change active job statuses to maybe ABANDONED?
There is indeed no way, by just looking at the database, to distinguish between a job that is effectively running and a job that has been abruptly killed (in both cases, the status is STARTED).
What you need to do is, in addition to checking status in the database, find a way to see if a job is effectively running. This really depends on how you run your jobs. For example, if you run your jobs in separate JVMs, you can write some code that checks if there is a JVM currently running your job. If you deploy your jobs to Kubernetes, you could ask Kubernetes if there is a pod currently running your job, etc.
However, if you can identify the execution that has been abruptly stopped for which the status has been stuck at STARTED (because Spring Batch did not have a chance to update its status to FAILED with a graceful shutdown), then you can update the status manually to ABONDONED and set its END_TIME to a non null value. This way, JobExplorer#findRunningExecutions will not return it anymore as a running execution.
Related
I'm currently building cd pipeline that replace existing Google Cloud Dataflow streaming pipeline with the new one with bash command. The old and new has the same name job. And I write bash command like this
gcloud dataflow jobs drain "${JOB_ID}" --region asia-southeast2 && \
gcloud dataflow jobs run NAME --other-flags
The problem with this command is that the first command doesn't wait until the job finish draining so that the second command throw error because duplicated job name.
Is there a way to wait until dataflow job finish draining? Or is there any better way?
Thanks!
Seeing as this post hasn't garnered any attention, I will be posting my comment as a post:
Dataflow jobs are asynchronous to the command gcloud dataflow jobs run, so when you use && the only thing that you'll be waiting on will be for the command to finish and since that command is just to get the process started (be it draining a job or running one) it finishes earlier than the job/drain does.
There are a couple of ways you could wait for the job/drain to finish, both having some added cost:
You could use a Pub/Sub step as part of a larger Dataflow job (think of it as a parent to the jobs you are draining and running, with the jobs you are draining or running sending a message to Pub/Sub about their status once it changes) - you may find the cost of Pub/Sub [here].
You could set up some kind of loop to repeatedly check the status of the job you're draining/running, likely inside of a bash script, though that can be a bit more tedious and isn't as neat as a listener, and it would require one's own computer/connection to be maintained or a GCE instance.
So I have 2 yml pipelines currently... one starts running the server and after server is up and running I start the other pipeline that runs tests in one job and once that's completed starts a job that shuts down the server from first pipeline.
I'm kinda new to yml and wondering if there is a way to run all this in a single pipeline...
The problem I came across is that if I put server to run in a first job I do not know how to condition the second job to kick off after server is running. This job doesn't have succeeded of failed condition because it's still in progress as the server has to run in order for tests to be run.
I tried adding a variable that I set to true after server is running but it still never jumps to the next job?
I looked into templates too but those are not very clear to me so any suggestion or documentation or tutorial would be very helpful on how to achive putting this in one pipeline...
I already googled a bunch and will keep googling but figured someone here might have an answer already.
Each agent can run only one job at a time. To run multiple jobs in parallel you must configure multiple agents. You also need sufficient parallel jobs.
You can specify the conditions under which each job runs. By default, a job runs if it does not depend on any other job, or if all of the jobs that it depends on have completed and succeeded. You can customize this behavior by forcing a job to run even if a previous job fails or by specifying a custom condition.
Since you have added a variable that you set to true after server is running. Then try to enable a custom condition, set that job run if a variable is xxx.
More details please kindly check official doc here:
Specify jobs in your pipeline
Specify conditions
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.
Is there a similar event scheduler from MySQL available in PostgreSQL?
While a lot of people just use cron, the closest thing to a built-in scheduler is PgAgent. It's a component to the pgAdmin GUI management tool. A good intro to it can be found at Setting up PgAgent and doing scheduled backups.
pg_cron is a simple, cron-based job scheduler for PostgreSQL that runs
inside the database as an extension. A background worker initiates
commands according to their schedule by connecting to the local
database as the user that scheduled the job.
pg_cron can run multiple jobs in parallel, but it runs at most one
instance of a job at a time. If a second run is supposed to start
before the first one finishes, then the second run is queued and
started as soon as the first run completes. This ensures that jobs run
exactly as many times as scheduled and don’t run concurrently with
themselves.
If you set up pg_cron on a hot standby, then it will start running the
cron jobs, which are stored in a table and thus replicated to the hot
standby, as soon as the server is promoted. This means your periodic
jobs automatically fail over with your PostgreSQL server.
Source: citusdata.com