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Hive >> mail # user >> Hive Authorization and Views


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Re: Hive Authorization and Views
Also we have all external tables to ensure that accidental dropping of tables does not delete data…Plus the good part of HDFS architecture is data is immutable….which means u cannot update rows….u can move partitions or delete/insert data from hdfs which IMHO is very cool….but may not solve all use cases
Regards
sanjay

From: Edward Capriolo <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>>
Reply-To: "[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>" <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>>
Date: Thursday, May 16, 2013 2:05 PM
To: "[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>" <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>>
Subject: Re: Hive Authorization and Views

The largest issue is that the RDBMS security model does not match with hive. Hive/Hadoop has file permissions, RDMBS have column and sometimes row level permissions.

When you physically have access to the underlying file (row level) permissions are not enforceable. The only way to enforce this type of security is to force users through a "turnstyle" that changes how hive currently works.
On Thu, May 16, 2013 at 4:42 PM, John Omernik <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>> wrote:
I am curious on the thoughts of the community here, this seems like something many enterprises would drool over with Hive... I am not a coder so the level coding involved something like this is unknown.
On Sat, May 4, 2013 at 8:31 AM, John Omernik <[EMAIL PROTECTED]<mailto:[EMAIL PROTECTED]>> wrote:
We were doing some tests this past week with hive authorization, one of our current use "challenges" is when we have an underlying, well managed and partitioned table, and we want to allow access to certain columns in that table.  Our first thoughts went to VIEWs as that's a common use case with Relational Databases, (i.e. setup a view with only the columns you want the user to access) and set the permissions appropriately.

In testing, and this is not surprising given the the "newness" of Hive Authorization, a VIEW can not be created as to allow access to to a table without granting access to the underlying table, defeating the idea of the view as tool to manage that access.

So I wanted to put to the user group: I've done some JIRA searching and didn't find anything (I will admit my JIRA search Foo is not stellar), but is there an option that could be thrown together in Hive that would allow that use case?  Perhaps a configuration setting that would allow views to execute as a specific user (perhaps a global user, or perhaps a user specified as view creation).  This could allow the "view" to have access to underlying table, but since the view is created, and it couldn't be changed by the user, and thus you could set view "read" permissions to your user or group of users you want access.

I suppose this has challenges "i.e. can a user just create a view to bypass table level restrictions? Perhaps if this model was taken, the privilege for CREATING/MODIFYING views could be created and granted only to a superuser of some sort.  I am really just walking through ideas here as this is the one last stumbling blocks we have with Hive from an "Enterprise ready" point of view. Heck, if done right, you could almost do data masking at the view level. You have a column in your source data that is sensitive, so instead of returning that column you do a MD5 (can we have a native MD5 function? :) of that column or you blank that column. If we put in strong security on the creation, modification of views, and allow views to execute as a different user that has access to source data, you have a powerful way to represent your data to all levels within your org.

Also: Since I am just brain storming here, I'd love to hear what others maybe doing around this area. Perhaps the Hive User Community can come up with a strategic plan, while at the same time share some shorter term workarounds.

Thanks!

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NEW: Monitor These Apps!
elasticsearch, apache solr, apache hbase, hadoop, redis, casssandra, amazon cloudwatch, mysql, memcached, apache kafka, apache zookeeper, apache storm, ubuntu, centOS, red hat, debian, puppet labs, java, senseiDB