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From lars hofhansl <la...@apache.org>
Subject Re: Efficiently wiping out random data?
Date Thu, 20 Jun 2013 09:35:35 GMT
IMHO the "proper" of doing such things is encryption.

0-ing the values or even overwriting with a pattern typically leaves traces of the old data
on a magnetic platter that can be retrieved with proper forensics. (Secure erase of SSD is
typically pretty secure, though).


For such use cases, files (HFiles) should be encrypted and the decryption keys should just
be forgotten at the appropriate times.
I realize that for J-D's specific use case doing this at the HFile level would be very difficult.

Maybe the KVs' values could be stored encrypted with a user specific key. Deleting the user's
data then means to forget that users key.


-- Lars

________________________________
From: Matt Corgan <mcorgan@hotpads.com>
To: dev <dev@hbase.apache.org> 
Sent: Wednesday, June 19, 2013 2:15 PM
Subject: Re: Efficiently wiping out random data?


Would it be possible to zero-out all the value bytes for cells in existing
HFiles?  They keys would remain, but if you knew that ahead of time you
could design your keys so they don't contain important info.


On Wed, Jun 19, 2013 at 11:28 AM, Ian Varley <ivarley@salesforce.com> wrote:

> At least in some cases, the answer to that question ("do you even have to
> destroy your tapes?") is a resounding "yes". For some extreme cases (think
> health care, privacy, etc), companies do all RDBMS backups to disk instead
> of tape for that reason. (Transaction logs are considered different, I
> guess because they're inherently transient? Who knows.)
>
> The "no time travel" fix doesn't work, because you could still change that
> code or ACL in the future and get back to the data. In these cases, one
> must provably destroy the data.
>
> That said, forcing full compactions (especially if they can be targeted
> via stripes or levels or something) is an OK way to handle it, maybe
> eventually with more ways to nice it down so it doesn't hose your cluster.
>
> Ian
>
> On Jun 19, 2013, at 11:27 AM, Todd Lipcon wrote:
>
> I'd also question what exactly the regulatory requirements for deletion
> are. For example, if you had tape backups of your Oracle DB, would you have
> to drive to your off-site storage facility, grab every tape you ever made,
> and zero out the user's data as well? I doubt it, considering tapes have
> basically the same storage characteristics as HDFS in terms of inability to
> random write.
>
> Another example: deletes work the same way in most databases -- eg in
> postgres, deletion of a record just consists of setting a record's "xmax"
> column to the current transaction ID. This is equivalent to a tombstone,
> and you have to wait for a VACUUM process to come along and actually delete
> the record entry. In Oracle, the record will persist in a rollback segment
> for a configurable amount of time, and you can use a Flashback query to
> time travel and see it again. In Vertica, you also set an "xmax" entry and
> wait until the next merge-out (like a major compaction).
>
> Even in a filesystem, deletion doesn't typically remove data, unless you
> use a tool like srm. It just unlinks the inode from the directory tree.
>
> So, if any of the above systems satisfy their use case, then HBase ought to
> as well. Perhaps there's an ACL we could add which would allow/disallow
> users from doing time travel more than N seconds in the past..  maybe that
> would help allay fears?
>
> -Todd
>
> On Wed, Jun 19, 2013 at 8:12 AM, Jesse Yates <jesse.k.yates@gmail.com
> <mailto:jesse.k.yates@gmail.com>>wrote:
>
> Chances are that date isn't completely "random". For instance, with a user
> they are likely to have an id in their row key, so doing a filtering (with
> a custom scanner) major compaction would clean that up. With Sergey's
> compaction stuff coming in you could break that out even further and only
> have to compact a small set of files to get that removal.
>
> So it's hard, but as its not our direct use case, it's gonna be a few extra
> hoops.
>
> On Wednesday, June 19, 2013, Kevin O'dell wrote:
>
> Yeah, the immutable nature of HDFS is biting us here.
>
>
> On Wed, Jun 19, 2013 at 8:46 AM, Jean-Daniel Cryans <jdcryans@apache.org
> <mailto:jdcryans@apache.org>
> <javascript:;>
> wrote:
>
> That sounds like a very effective way for developers to kill clusters
> with compactions :)
>
> J-D
>
> On Wed, Jun 19, 2013 at 2:39 PM, Kevin O'dell <
> kevin.odell@cloudera.com<javascript:;>
>
> wrote:
> JD,
>
>   What about adding a flag for the delete, something like -full or
> -true(it is early).  Once we issue the delete to the proper
> row/region
> we
> run a flush, then execute a single region major compaction.  That
> way,
> if
> it is a single record, or a subset of data the impact is minimal.  If
> the
> delete happens to hit every region we will compact every region(not
> ideal).
> Another thought would be an overwrite, but with versions this logic
> becomes more complicated.
>
>
> On Wed, Jun 19, 2013 at 8:31 AM, Jean-Daniel Cryans <
> jdcryans@apache.org<mailto:jdcryans@apache.org> <javascript:;>
> wrote:
>
> Hey devs,
>
> I was presenting at GOTO Amsterdam yesterday and I got a question
> about a scenario that I've never thought about before. I'm wondering
> what others think.
>
> How do you efficiently wipe out random data in HBase?
>
> For example, you have a website and a user asks you to close their
> account and get rid of the data.
>
> Would you say "sure can do, lemme just issue a couple of Deletes!"
> and
> call it a day? What if you really have to delete the data, not just
> mask it, because of contractual obligations or local laws?
>
> Major compacting is the obvious solution but it seems really
> inefficient. Let's say you've got some truly random data to delete
> and
> it happens so that you have at least one row per region to get rid
> of... then you need to basically rewrite the whole table?
>
> My answer was such, and I told the attendee that it's not an easy
> use
> case to manage in HBase.
>
> Thoughts?
>
> J-D
>
>
>
>
> --
> Kevin O'Dell
> Systems Engineer, Cloudera
>
>
>
>
> --
> Kevin O'Dell
> Systems Engineer, Cloudera
>
>
>
> --
> -------------------
> Jesse Yates
> @jesse_yates
> jyates.github.com<http://jyates.github.com>
>
>
>
>
> --
> Todd Lipcon
> Software Engineer, Cloudera
>
>

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