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 > >> _______________________________________________ > >> riak-users mailing list > >> riak-users@lists.basho.com > >> http://lists.basho.com/mailman/listinfo/riak-users_lists.basho.com > >> > >> _______________________________________________ > >> riak-users mailing list > >> riak-users@lists.basho.com > >> http://lists.basho.com/mailman/listinfo/riak-users_lists.basho.com > > > _______________________________________________ > riak-users mailing list > riak-users@lists.basho.com > http://lists.basho.com/mailman/listinfo/riak-users_lists.basho.com >
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