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From Ravi Kanth <ravikanth....@gmail.com>
Subject Re: Spark Streaming + Kudu
Date Mon, 05 Mar 2018 21:59:36 GMT
Hi Mike,

Thanks for the reply. Yes, I am using AUTO_FLUSH_BACKGROUND.

So, I am trying to use Kudu Client API to perform UPSERT into Kudu and I
integrated this with Spark. I am trying to test a case where in if any of
Kudu server fails. So, in this case, if there is any problem in writing,
getPendingErrors() should give me a way to handle these errors so that I
can successfully terminate my Spark Job. This is what I am trying to do.

But, I am not able to get a hold of the exceptions being thrown from with
in the KuduClient when retrying to connect to Tablet Server. My
getPendingErrors is not getting ahold of these exceptions.

Let me know if you need more clarification. I can post some Snippets.

Thanks,
Ravi

On 5 March 2018 at 13:18, Mike Percy <mpercy@apache.org> wrote:

> Hi Ravi, are you using AUTO_FLUSH_BACKGROUND
> <https://kudu.apache.org/releases/1.6.0/apidocs/org/apache/kudu/client/SessionConfiguration.FlushMode.html>?
> You mention that you are trying to use getPendingErrors()
> <https://kudu.apache.org/releases/1.6.0/apidocs/org/apache/kudu/client/KuduSession.html#getPendingErrors-->
but
> it sounds like it's not working for you -- can you be more specific about
> what you expect and what you are observing?
>
> Thanks,
> Mike
>
>
>
> On Mon, Feb 26, 2018 at 8:04 PM, Ravi Kanth <ravikanth.4b0@gmail.com>
> wrote:
>
>> Thank Clifford. We are running Kudu 1.4 version. Till date we didn't see
>> any issues in production and we are not losing tablet servers. But, as part
>> of testing I have to generate few unforeseen cases to analyse the
>> application performance. One among that is bringing down the tablet server
>> or master server intentionally during which I observed the loss of records.
>> Just wanted to test cases out of the happy path here. Once again thanks for
>> taking time to respond to me.
>>
>> - Ravi
>>
>> On 26 February 2018 at 19:58, Clifford Resnick <cresnick@mediamath.com>
>> wrote:
>>
>>> I'll have to get back to you on the code bits, but I'm pretty sure we're
>>> doing simple sync batching. We're not in production yet, but after some
>>> months of development I haven't seen any failures, even when pushing load
>>> doing multiple years' backfill. I think the real question is why are you
>>> losing tablet servers? The only instability we ever had with Kudu was when
>>> it had that weird ntp sync issue that was fixed I think for 1.6. What
>>> version are you running?
>>>
>>> Anyway I would think that infinite loop should be catchable somewhere.
>>> Our pipeline is set to fail/retry with Flink snapshots. I imagine there is
>>> similar with Spark. Sorry I cant be of more help!
>>>
>>>
>>>
>>> On Feb 26, 2018 9:10 PM, Ravi Kanth <ravikanth.4b0@gmail.com> wrote:
>>>
>>> Cliff,
>>>
>>> Thanks for the response. Well, I do agree that its simple and seamless.
>>> In my case, I am able to upsert ~25000 events/sec into Kudu. But, I am
>>> facing the problem when any of the Kudu Tablet or master server is down. I
>>> am not able to get a hold of the exception from client. The client is going
>>> into an infinite loop trying to connect to Kudu. Meanwhile, I am loosing my
>>> records. I tried handling the errors through getPendingErrors() but still
>>> it is helpless. I am using AsyncKuduClient to establish the connection and
>>> retrieving the syncClient from the Async to open the session and table. Any
>>> help?
>>>
>>> Thanks,
>>> Ravi
>>>
>>> On 26 February 2018 at 18:00, Cliff Resnick <cresny@gmail.com> wrote:
>>>
>>> While I can't speak for Spark, we do use the client API from Flink
>>> streaming and it's simple and seamless. It's especially nice if you require
>>> an Upsert semantic.
>>>
>>> On Feb 26, 2018 7:51 PM, "Ravi Kanth" <ravikanth.4b0@gmail.com> wrote:
>>>
>>> Hi,
>>>
>>> Anyone using Spark Streaming to ingest data into Kudu and using Kudu
>>> Client API to do so rather than the traditional KuduContext API? I am stuck
>>> at a point and couldn't find a solution.
>>>
>>> Thanks,
>>> Ravi
>>>
>>>
>>>
>>>
>>
>

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