You could define access in Sentry and enable permissions sync with HDFS, so
you could just grant access on Hive per-database or per-table basis. It
should work for Spark too, as Sentry will propage "grants" to HDFS acls.

http://www.cloudera.com/content/cloudera/en/documentation/core/latest/topics/sg_hdfs_sentry_sync.html




-- 
Ruslan Dautkhanov

On Thu, Sep 3, 2015 at 1:46 PM, Daniel Schulz <danielschulz2...@hotmail.com>
wrote:

> Hi Matei,
>
> Thanks for your answer.
>
> My question is regarding simple authenticated Spark-on-YARN only, without
> Kerberos. So when I run Spark on YARN and HDFS, Spark will pass through my
> HDFS user and only be able to access files I am entitled to read/write?
> Will it enforce HDFS ACLs and Ranger policies as well?
>
> Best regards, Daniel.
>
> > On 03 Sep 2015, at 21:16, Matei Zaharia <matei.zaha...@gmail.com> wrote:
> >
> > If you run on YARN, you can use Kerberos, be authenticated as the right
> user, etc in the same way as MapReduce jobs.
> >
> > Matei
> >
> >> On Sep 3, 2015, at 1:37 PM, Daniel Schulz <danielschulz2...@hotmail.com>
> wrote:
> >>
> >> Hi,
> >>
> >> I really enjoy using Spark. An obstacle to sell it to our clients
> currently is the missing Kerberos-like security on a Hadoop with simple
> authentication. Are there plans, a proposal, or a project to deliver a
> Ranger plugin or something similar to Spark. The target is to differentiate
> users and their privileges when reading and writing data to HDFS? Is
> Kerberos my only option then?
> >>
> >> Kind regards, Daniel.
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