can I configure for “retry time cycle” many different interval expression for example
something like that: “R6/PT10S, R2/PT30M” - 6 times each 10 Seconds and then 2 times after 30 minutes
Thanks in Advance,
Wladi
The job executor section of the camunda user guide only shows an example of comma separated intervals without repeats.
Looking at the code it seems a repeat is only recognized if there is a single interval configured
https://github.com/camunda/camunda-bpm-platform/blob/7.13.0/engine/src/main/java/org/camunda/bpm/engine/impl/util/ParseUtil.java#L88
The lookup of which interval to apply also does not consider any repeats
https://github.com/camunda/camunda-bpm-platform/blob/7.13.0/engine/src/main/java/org/camunda/bpm/engine/impl/cmd/DefaultJobRetryCmd.java#L113
This sounds like a useful feature though, you might want to open an issue in the camunda issue tracker.
Related
I'm trying to monitor if my Lambda has been executed within the last 25 hours within New Relic. I want to alert if it hasn't.
I have the following NRQL which gives me the graph I want to see:
SELECT sum(`provider.invocations.Sum`) FROM ServerlessSample WHERE provider.resource = 'my_lambda_name'
I then just want to say that if it dips below 1 for 1500 minutes (25 hours) then alert, but NR only allows me to set an alarm for 120 minutes. Any tips on how to get around this?
Interesting question, as I have seen in New Relic discussion page, or Explorers Hub, there might be solution for your task.
Can you please review this link:
https://discuss.newrelic.com/t/relic-solution-extending-the-functionality-of-nrql-alert-conditions-beyond-a-single-minute/75441
If you think about this for a moment, you might see how NRQL queries using percentile or stddev are a lot less useful than they seem, when used in an alert condition. After all, if you calculate the standard deviation over an hour (or 24 hours), that can be meaningful. But stddev(duration), or percentile(duration,95) calculated over only 60 seconds is less meaningful.
I think that limit is 24 hours but I haven't test it yet.
Hope this will help you, I will try to give it a go as well to see will this work.
I have a dataflow job processing data from pub/sub defined like this:
read from pub/sub -> process (my function) -> group into day windows -> write to BQ
I'm using Write.Method.FILE_LOADS because of bounded input.
My job works fine, processing lots of GBs of data but it fails and tries to retry forever when it gets to create another table. The job is meant to run continuously and create day tables on its own, it does fine on the first few ones but then gives me indefinitely:
Processing stuck in step write-bq/BatchLoads/SinglePartitionWriteTables/ParMultiDo(WriteTables) for at least 05h30m00s without outputting or completing in state finish
Before this happens it also throws:
Load job <job_id> failed, will retry: {"errorResult":{"message":"Not found: Table <name_of_table> was not found in location US","reason":"notFound"}
It is indeed a right error because this table doesn't exists. Problem is that the job should create it on its own because of defined option CreateDisposition.CREATE_IF_NEEDED.
The number of day tables that it creates correctly without a problem depens on number of workers. It seems that when some worker creates one table its CreateDisposition changes to CREATE_NEVER causing the problem, but it's only my guess.
The similar problem was reported here but without any definite answer:
https://issues.apache.org/jira/browse/BEAM-3772?focusedCommentId=16387609&page=com.atlassian.jira.plugin.system.issuetabpanels%3Acomment-tabpanel#comment-16387609
ProcessElement definition here seems to give some clues but I cannot really say how it works with multiple workers: https://github.com/apache/beam/blob/master/sdks/java/io/google-cloud-platform/src/main/java/org/apache/beam/sdk/io/gcp/bigquery/WriteTables.java#L138
I use 2.15.0 Apache SDK.
I encountered the same issue, which is still not fixed in BEAM 2.27.0 of january 2021. Therefore I had to develop a workaround: a custom PTransform which checks if the target table exist before the the BigQueryIO stage. It uses the bigquery java client for this and a Guava cache, as well as a windowing strategy (fixed, check every 15s) to sustain a heavy traffic of about 5000 elements per second. Here is the code: https://gist.github.com/matthieucham/85459eff5fdea8d115be520e2dd5ccc1
There was a bug in the past that caused this error, but that particular one was fixed in commit https://github.com/apache/beam/commit/d6b4dcec5f297f5c1bd08f345f0e1e5c756775c2#diff-3f40fd931c8b8b972772724369cea310 Can you check to see if the version of Beam you are running includes this commit?
I'm importing text items to Google's AutoML. Each row contains around 5000 characters and I'm adding 70K of these rows. This is a multi-label data set. There is no progress bar or indication of how long this process will take. Its been running for a couple of hours. Is there any way to calculate time remaining or total estimated time. I'd like to add additional data sets, but I'm worried that this will be a very long process before the training even begins. Any sort of formula to create even a semi-wild guess would be great.
-Thanks!
I don't think that's possible today, but I filed a feature request [1] that you can follow for updates. I asked for both training and importing data, as for training it could be useful too.
I tried training with 50K records (~ 300 bytes/record) and the load took more than 20 mins after which I killed it. I retried with 1K, which ran for 20 mins and then emailed me an error message saying I had multiple labels per input (yes, so what? training data is going to have some of those) and I had >100 labels. I simplified the classification buckets and re-ran. It took another 20 mins and was successful. Then I ran 'training' which took 3 hours and billed me $11. That maps to $550 for 50K recs, assuming linear behavior. The prediction results were not bad for a first pass, but I got the feeling that it is throwing a super large neural net at the problem. Would help if they said what NN it was and its dimensions. They do say "beta" :)
don't wast your time trying to using google for text classification. I am a GCP hard user but microsoft LUIS is far better, precise and so much faster that I can't believe that both products are trying to solve same problem.
Luis has a much better documentation, support more languages, has a much better test interface, way faster.. I don't know if is cheaper yet because the pricing model is different but we are willing to pay more.
I am running tests that take many hours to complete on ADW and the amount of SQL involved rolls off the 10,000 row limit of sys.dm_pdw_exec_requests (as documented at https://learn.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-service-capacity-limits ) in less than 30 minutes.
Is my only option to create a process to capture into a table in my database the data on sys.dm_pdw_exec_requests every N minutes (where N << 30 )?
I'm not sure what your use case is, but perhaps you can get the same useful information out of the audit logs?
https://learn.microsoft.com/en-us/azure/sql-data-warehouse/sql-data-warehouse-auditing-overview
You might be able to use something that was already built for that purpose, instead of reinventing the wheel:
https://github.com/andrealibero/Azure_SQL_DWH_Perf_Stats
the PowerShell script can collect output of DMVs (configured in an XML file) in a loop or for a number of specified iterations.
Given how quickly the DMVs roll out for you this might help in your scenario.
I created a schedule in IBM OPL:
dvar sequence schedule in all(j in Jobs) job[j];
If the CP-Module generates a solution, the solution is sometimes not a non-delay solution. This is however not allowed and thus I want to enforce a non-delay schedule.
I tried different solutions in the subject to-Section...
forall(t in Jobs)
if (t > 1)
startOf(job[t]) == endOf(job[t-1]);
... but these fail (obviously) when job t-1 is not followed by job t.
Anyone who can give me a hint on how to solve this problem?
Kind regards,
Franz
you should try to use endAtStart.
(OPL constraint to restrict the relative positions of interval variables.)
regards
endAtStart will only work if your Jobs are always ready to start when the preceding Job finishes. If this is not the case, you will receive an error.
A better solution would be to regard the no-delay in the objective. What you are trying to achieve is to start every new job as soon as possible. So you can for example use the staticLex function:
minimize staticLex(startOf(job[1]), startOf(job[2]),...);
However, this expression can become very long and you would need to hardcode the number of intervals.
A little workaround would be to assign the intervals decreasing weighting factors:
minimize sum(j in Jobs) startOf(job[j])*100^-ord(Jobs,j);
I hope this works for you!
Regards
Jan