Hi Peter,

What is "large-scale" in your case? How many keys do you need to delete,
and how often?

//Daniel

On Wed, Jun 3, 2015 at 9:54 PM, Peter Herndon <tphern...@gmail.com> wrote:

> Interesting thought. It might work for us, it might not, I’ll have to
> check with our CTO to see whether the expense makes sense under our
> circumstances.
>
> Thanks!
>
> —Peter
> > On Jun 3, 2015, at 2:21 PM, Drew Kerrigan <d...@kerrigan.io> wrote:
> >
> > Another idea for a large-scale one-time removal of data, as well as an
> opportunity for a fresh start, would be to:
> >
> > 1. set up multi-data center replication between 2 clusters
> > 2. implement a recv/2 hook on the sink which refuses data from the
> buckets / keys you would like to ignore / delete
> > 3. trigger a full sync replication
> > 4. start using the sync as your new source of data sans the ignored data
> >
> > Obviously this is costly, but it should have a fairly minimal impact to
> existing production users other than the moment that you switch traffic
> from the old cluster to the new one.
> >
> > Caveats: Not all Riak features are supported with MDC (search indexes
> and strong consistency in particular).
> >
> > On Wed, Jun 3, 2015 at 2:11 PM Peter Herndon <tphern...@gmail.com>
> wrote:
> > Sadly, this is a production cluster already using leveldb as the
> backend. With that constraint in mind, and rebuilding the cluster not
> really being an option to enable multi-backends or bitcask, what would our
> best approach be?
> >
> > Thanks!
> >
> > —Peter
> >
> > > On Jun 3, 2015, at 12:09 PM, Alexander Sicular <sicul...@gmail.com>
> wrote:
> > >
> > > We are actively investigating better options for deletion of large
> amounts of keys. As Sargun mentioned, deleting the data dir for an entire
> backend via an operationalized rolling restart is probably the best
> approach right now for killing large amounts of keys.
> > >
> > > But if your key space can fit in memory the best way to kill keys is
> to use bitcask ttl if that's an option. 1. If you can even use bitcask in
> your environment due to the memory overhead and 2. If your use case allows
> for ttls which it may considering you may already be using time bound
> buckets....
> > >
> > > -Alexander
> > >
> > > @siculars
> > > http://siculars.posthaven.com
> > >
> > > Sent from my iRotaryPhone
> > >
> > > On Jun 3, 2015, at 09:54, Sargun Dhillon <sdhil...@basho.com> wrote:
> > >
> > >> You could map your keys to a given bucket, and that bucket to a given
> backend using multi_backend. There is some cost to having lots of backends
> (memory overhead, FDs, etc...). When you want to do a mass drop, you could
> down the node, and delete that given backend, and bring it up. Caveat: AAE,
> MDC, nor mutable data play well with this scenario.
> > >>
> > >> On Wed, Jun 3, 2015 at 10:43 AM, Peter Herndon <tphern...@gmail.com>
> wrote:
> > >> Hi list,
> > >>
> > >> We’re looking for the best way to handle large scale expiration of
> no-longer-useful data stored in Riak. We asked a while back, and the
> recommendation was to store the data in time-segmented buckets (bucket per
> day or per month), query on the current buckets, and use the streaming list
> keys API to handle slowly deleting the buckets that have aged out.
> > >>
> > >> Is that still the best approach for doing this kind of task? Or is
> there a better approach?
> > >>
> > >> Thanks!
> > >>
> > >> —Peter Herndon
> > >> Sr. Application Engineer
> > >> @Bitly
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