agreed

 

Dr Mich Talebzadeh

 

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From: Russell Jurney [mailto:russell.jur...@gmail.com] 
Sent: 19 February 2016 16:49
To: Jörn Franke <jornfra...@gmail.com>
Cc: Divya Gehlot <divya.htco...@gmail.com>; user @spark <user@spark.apache.org>
Subject: Re: Spark JDBC connection - data writing success or failure cases

 

Oracle is a perfectly reasonable endpoint for publishing data processed in 
Spark. I've got to assume he's using it that way and not as a stand in for HDFS?

On Friday, February 19, 2016, Jörn Franke <jornfra...@gmail.com 
<mailto:jornfra...@gmail.com> > wrote:

Generally oracle db should not be used as a storage layer for spark due to 
performance reasons. You should consider HDFS. This will help you also with 
fault - tolerance.

> On 19 Feb 2016, at 03:35, Divya Gehlot <divya.htco...@gmail.com 
> <javascript:;> > wrote:
>
> Hi,
> I am a Spark job which connects to RDBMS (in mycase its Oracle).
> How can we check that complete data writing is successful?
> Can I use commit in case of success or rollback in case of failure ?
>
>
>
> Thanks,
> Divya

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