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[gaborgsomogyi]

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@tdas @zsxwing @koeninger @tedyu do you think it makes sense to make 
similar step in the DStream area like this and then later follow with the 
mentioned Apache Common Pool?


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[tdas]

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Just to be clear, I am not saying that we *have to* move to this pool 
stuff. I am just saying that if we want to make this more robust, then we 
should try to use existing tools (after careful evaluation), rather than trying 
to reinvent the wheel.


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[tedyu]

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Interesting.


https://commons.apache.org/proper/commons-pool/apidocs/org/apache/commons/pool2/impl/BaseGenericObjectPool.html#getBorrowedCount()


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[tdas]

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@tedyu It was indeed hard to find :) But apache commons pool does expose 
metrics on idle/active counts. See 
https://commons.apache.org/proper/commons-pool/apidocs/org/apache/commons/pool2/impl/BaseGenericObjectPool.html



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[tedyu]

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I did a quick search for 'apache commons pool metrics' which didn't show up 
directly related links.


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[tdas]

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@tedyu @zsxwing My thoughts on this is that we should consider migrating to 
something like Apache Common Pool (assuming it does not require additional 
maven libraries), which might be less maintenance load. It could be that it 
already has metrics, etc. that we can leverage.


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[zsxwing]

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@tedyu that's a good idea. Could you create a ticket? Thanks!


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[tedyu]

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@tdas 
Do you think a follow on JIRA can be logged for adding metrics for the 
cache operations ?

Thanks


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[zsxwing]

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@tdas this is much simpler!!! LGTM. Merging to master.


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[tdas]

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The idea is good. But how do you propose exposing that information?
Periodic print out in the log?

From a different angle, I would rather not do feature creep in this PR that
is intended to be backported to 2.3.

On Mar 15, 2018 7:31 PM, "tedyu"  wrote:

> *@tedyu* commented on this pull request.
> --
>
> In external/kafka-0-10-sql/src/main/scala/org/apache/spark/sql/kafka010/
> KafkaDataConsumer.scala
> :
>
> >CachedKafkaDataConsumer(newInternalConsumer)
>
> -} else if (existingInternalConsumer.inuse) {
> +} else if (existingInternalConsumer.inUse) {
>// If consumer is already cached but is currently in use, then 
return a new consumer
>NonCachedKafkaDataConsumer(newInternalConsumer)
>
> Maybe keep an internal counter for how many times the non cached consumer
> is created.
> This would give us information on how effective the cache is
>
> —
> You are receiving this because you authored the thread.
> Reply to this email directly, view it on GitHub
> ,
> or mute the thread
> 

> .
>



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[tdas]

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@tedyu @zsxwing thank you very much for catching the bugs. I have 
simplified the logic quite a bit. Note that I removed the invariant that I had 
introduced earlier. Additionally, I locally ran the stress test with 100 
threads and 1 read attempts, which ran for 2 mins. It passed. 


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[tdas]

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@koeninger good question Cody! I think we should fix this limitation 
eventually. The only reason I am not doing that in this PR is to keep the 
changes minimum for backporting to 2.3.x. Eventually, we should not do such 
cache management, and rather use something like [Apache Common 
Pool](https://commons.apache.org/proper/commons-pool/index.html).


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[koeninger]

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Can you clarify why you want to allow only 1 cached consumer per 
topicpartition, closing any others at task end?

It seems like opening and closing consumers would be less efficient than 
allowing a pool of more than one consumer per topicpartition.


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 * This patch **fails Scala style tests**.
 * This patch merges cleanly.
 * This patch adds no public classes.


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[GitHub] spark issue #20767: [SPARK-23623] [SS] Avoid concurrent use of cached consum...

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@zsxwing @brkyvz PTAL.


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