ADF Dataflow cluster start time

Søren Callesen 1 Reputation point
2022-08-31T21:32:38.103+00:00

I have a rather complex dataflow, which takes around 4 minutes to complete - but the start up time of the spark cluster, can range from minutes to hours(Seems random)
Example: 236722-image.png

Can understand that it usually takes 4-5 minutes... whats going on with a 156 minutes startup time?
Its run in debug mode, on a medium cluster size and have up to 10 parrallel dataflows running.

Azure Data Factory
Azure Data Factory
An Azure service for ingesting, preparing, and transforming data at scale.
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  1. Søren Callesen 1 Reputation point
    2022-09-06T07:41:01.927+00:00

    Hello KranthiPakala,

    Thanks for your response.
    I dont have any administrative privileges in our Azure environment, so cant create any ticket.
    But maybe you can answer my question regardless, since its properly down to me not understanding the logging information provided in adf.

    The platform administrators believes its due to the sink not being able to deliver data to the database.
    The log/debug view of the dataflow is getting weird to me, since Im not certain what to look after and I cant explain why I dont believe its down to the sink, based on the other logging information provided in the dataflow.

    When the dataflow is running, it goes into the queue as the first thing.
    Now and then the dataflow doesnt seems to get past this state and times out before the Queue status changes in the initial sink logging view and the acquiring compute doesnt seem to end, before the timeout in this scenario. This offcourse never happens when I try to showcase the issue.

    When/if a dataflow completes, all the transformations have time spend, but its doesnt add up to the dataflow execution time in the pipeline.
    When looking specific at the sink, the time is longer than any other of the logging information in the dataflow, but matches the time logged in the pipeline calling the dataflow.
    The dataflow seems to be able to timeout, if the database operation takes longer, than the cluster inactivity time.

    To recap - what does the 156 minutes cluster start up time actually mean, based on the not so clear overview logging information - is it how far the dataflow have gotten before timing out to a database issue or is it really only the wait time before the cluster has been started up.

    Is the overview logging information based on anything or do you have to go through each transformation group in order to see execution times?
    It seems counter intuitive to me, that the sink group in the stages logging shows 8 secs and the initial sink overview show all success and the same time as in the stages.
    But when clicking on the end sink, its shows 20 minutes processing time, way longer than any time in the overview logging information in the dataflow.


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