I have a job that uses the Kafka Connector Stage in order to read a Kafka queue and then load into the database. That job runs in Continuous Mode, which it has no time to conclude, since it keeps monitoring the Kafka queue in real time.
For unexpected reasons (say, server issues, job issues etc) that job may terminate with failure. In general, that happens after 300 running hours of that job. So, in order to keep the job alive I have to manually look to the job status and then to do a Reset and Run, in order to keep the job running.
The problem is that between the job termination and my manual Reset and Run can pass several hours, which is critical. So I'm looking for a way to eliminate the manual interaction and to reduce that gap by automating the job invocation.
I tried to use Control-M to daily run the job, but with no success: The first day the Control-M called the job, it ran it fine. But in the next day, when the Control-M did an attempt to instantiate the job again it failed (since it was already running). Besides, the Datastage will never tell back Control-M that a job was successfully concluded, since the job's nature won't allow that.
Said that, I would like to hear ideas from you that can light me up.
The first thing that came in mind is to create a intermediate Sequence and then schedule it in Control-M. Then, this new Sequence would call the continuous job asynchronously by using command line stage.
For the case where just this one job terminates unexpectedly and you want it to be restarted as soon as possible, have you considered calling this job from a sequence? The sequence could be setup to loop running this job.
Thus sequence starts job and waits for it to finish. When job finishes, the sequence will then loop and start the job again. You could have added conditions on job exit (for example, if the job aborted, then based on that job end status, you could reset the job before re-running it.
This would not handle the condition where the DataStage engine itself was shut down (such as for maintenance or possibly an error) in which case all jobs end including your new sequence. The same also applies for a server reboot or other situations where someone may have inadvertently stopped your sequence. For those cases (such as DataStage engine stop) your team would need to have process in place for jobs/sequences that need to be started up following a DataStage or System outage.
For the outage scenario, you could create a monitor script (regardless of whether running the job solo or from sequence) that sleeps/loops on 5-10 minute intervals and then checks the status of your job using dsjob command, and if not running can start that job/sequence (also via dsjob command). You can decide whether that script startup would occur at DataSTage startup, machine startup, or run it from Control M or other scheduler.
Related
Having read https://learn.microsoft.com/en-us/azure/data-factory/v1/data-factory-scheduling-and-execution, it is unclear to me if:
A schedule is made every hr for a job to run,
can we stop the concurrent execution of the next job at hr+1 if the job for hr+0 is still running?
It looks if concurrency = 1 means this,
But is that invocation simply not start until concurrent execution is finished?
Or will it be discarded?
When we set the concurrency 1, only one instance will be allowed to run at a time. When the scheduled trigger runs again and tries to run the pipeline, If the pipeline is already running, the next invocation will be queued. It will start after finishing the current instance.
For your question, the following invocation will be queued. After the first run finishes, the next run will start.
I am using an Azure batch account to run sqlpackage.exe in order to move databases from a server to another. A task that has started 6 days ago has suddenly been restarted and started from the beginning after 4 days of running (extremely large databases). The task run uninterruptedly up until then and should have continued to run for about 1-2 days.
The PowerShell script that contains all the logic handles all the exceptions that could occur during the execution. Also, the retry count for the task was set to 0 in case it fails.
Unfortunately, I did not have diagnostics settings configured and I could only look at the metrics and there was a short period when there wasn't any node.
What can be the causes for this behavior? Restarting while the node is still running
Thanks
Unfortunately, there is no way to give a definitive answer to this question. You will need to dig into the compute node (interactively log in) and check system logs to give you details on why the node restarted. There is no guarantee that a compute node will have 100% uptime as there may be hardware faults or other service interruptions.
In general, it's best practice to have long running tasks checkpoint progress combined with a retry policy. Programs that can reload state can pick up at the time of the checkpoint when the Batch service automatically reschedules the task execution. Please see the Batch best practices guide for more information.
I have a scheduled parallel Datastage (11.7) job.
This job has a Hive Connector with a Before and After Statement.
The before statement run ok but After statement remains in running state for several hours (on Hue Log i see this job finished in 1hour) and i have to manually abort it on Datastage Director.
Is there the way to "program an abort"?
For example i want schedule the interruption of the running job every morning at 6.
I hope I was clear :)
Even though you can kill the job - as per other responses - using dsjob to stop the job, this may have no effect because the After statement has been issued synchronously; the job is waiting for it to finish, and (probably) not processing kill signals and the like in the meantime. You would be better advised to work out why the After command is taking too long, and addressing that.
I am new to spring-batch, got few questions:-
I have got a question about the restart. As per documentation, the restart feature is enabled by default. What I am not clear is do I need to do any extra code for a restart? If so, I am thinking of adding a scheduled job that looks at failed processes and restarts them?
I understand spring-batch-admin is deprecated. However, we cannot use spring-cloud-data-flow right now. Is there any other alternative to monitor and restart jobs on demand?
The restart that you mention only means if a job is restartable or not .It doesn't mean Spring Batch will help you to restart the failed job automatically.
Instead, it provides the following building blocks for developers for achieving this task on their own :
JobExplorer to find out the id of the job execution that you want to restart
JobOperator to restart a job execution given a job execution id
Also , a restartable job can only be restarted if its status is FAILED. So if you want to restart a running job that was stop running because of the server breakdown , you have to first find out this running job and update its job execution status and all of its task execution status to FAILED first in order to restart it. (See this for more information). One of the solution is to implement a SmartLifecycle which use the above building blocks to achieve this goal.
When we run multiple concurrent jobs with different parameters, how can we control (stop, restart) the appropriate jobs? Our internal code provides the jobExecution object, but under the covers The jobOperator uses the job name to get the job instance.
In our case all of the jobs are from "do-stuff.xml" (okay, it's sanitized and not very original). After looking at the spring-batch source code, our concern is that if there is more then one job running and we stop a job it will take the most recently submitted job and stop it.
The JobOperator will allow you to fetch all running executions of the job using getRunningExecutions(String jobName). You should be able to iterate over that list to find the one you want. Then, just call stop(long executionId) on the one you want.
Alternatively, we've also implemented listeners (both at step and chunk level) to check an outage status table. When we want to implement a system-wide outage, we add the outage there and have our listener throw an exception to bring our jobs down. once the outage is lifted, all "failed" executions may be restarted.