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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