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From Abhishek Somani <abhisheksoman...@gmail.com>
Subject Re: Custom datasource: when acquire and release a lock?
Date Mon, 27 May 2019 04:05:10 GMT
Hi experts,

I'll be very grateful if someone could help.

Thanks,
Abhishek

On Fri, May 24, 2019 at 7:06 PM Abhishek Somani <abhisheksomani88@gmail.com>
wrote:

> Hi experts,
>
> I am trying to create a custom Spark Datasource(v1) to read from a
> transactional data endpoint, and I need to acquire a lock with the endpoint
> before fetching data and release the lock after reading. Note that the lock
> acquisition and release needs to happen in the Driver JVM.
>
> I have created a custom RDD for this purpose, and tried acquiring the lock
> in MyRDD.getPartitions(), and releasing the lock at the end of the job by
> registering a QueryExecutionListener.
>
> Now as I have learnt, this is not the right approach as the RDD can get
> reused on further actions WITHOUT calling getPartitions() again(as the
> partitions of an RDD get cached). For example, if someone calls
> Dataset.collect() twice, the first time MyRDD.getPartitions() will get
> invoked, I will acquire a lock and release the lock at the end. However the
> second time collect() is called, getPartitions will NOT be called again as
> the RDD would be reused and the partitions would have gotten cached in the
> RDD.
>
> Can someone advice me on where would be the right places to acquire and
> release a lock with my data endpoint in this scenario.
>
> Thanks a lot,
> Abhishek Somani
>

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