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From Chris Anderson <jch...@apache.org>
Subject Re: multi-level views
Date Wed, 03 Jun 2009 19:29:53 GMT
On Wed, Jun 3, 2009 at 12:03 PM, Justin Balthrop <justin@geni.com> wrote:
> Nice! That sounds like exactly what I'm looking for. I don't think it will
> address the performance issues with reduce, but it's definitely a start.
>
> Do you mind sending a diff of your changes to couch_view_updater.erl? I
> diffed your file with trunk and there are a bunch of unrelated changes, of
> course.

There's also a Paul Davis's Cascade:
http://github.com/davisp/cascade/tree/master

I'm planning on writing something with Hovercraft that takes a group
reduce query and copies it to another database on demand. It wouldn't
try to be incremental, just provide for easy chaining.

I think chaining by copying to a db is a good way to work, because it
lets you experiment with other views on top of your reduce rows,
without regenerating the whole thing.

Chris

>
> Thanks
>
>
> On Jun 3, 2009, at 1:42 AM, Viacheslav Seledkin wrote:
>
>> Justin Balthrop wrote:
>>>
>>> Hi everyone,
>>>
>>> I've been reading the dev and user mailing lists for the past month or
>>> so, but haven't posted yet. I've fallen in love with couchdb, its
>>> power and simplicity, and I tell everyone who will listen why it is so
>>> much better than a relational db for most applications. I now have
>>> most of the engineering team at our company on board, and I'm in the
>>> process of converting our rails site from postgres to couchdb.
>>>
>>> So, after spending a few weeks converting models over to using
>>> couchdb, there is one feature that we are desperately missing:
>>>
>>> Multi-level map-reduce in views.
>>>
>>> We need a way to take the output of reduce and pass it back through
>>> another map-reduce step (multiple times in some cases). This way, we
>>> could build map-reduce flows that compute (and cache) any complex data
>>> computation we need.
>>>
>>> Our specific use case isn't incredibly important, because multi-level
>>> map-reduce could be useful in countless ways, but I'll include it
>>> anyway just as illustration. The specific need for us arose from the
>>> desire to slice up certain very large documents to make concurrent
>>> editing by a huge number of users feasible. Then we started to use a
>>> view step to combine the data back into whole documents. This worked
>>> really well at first, but we soon found that we needed to run
>>> additional queries on those documents. So we were stuck with either:
>>>
>>> 1) do the queries in the client - meaning we lose all the power and
>>> caching of couchdb views; or
>>> 2) reinsert the combined documents into another database - meaning we
>>> are storing the data twice, and we still have to deal with contention
>>> when modifying the compound documents in that database.
>>>
>>> Multi-level map-reduce would solve this problem perfectly!
>>>
>>> Multi-level views could also simplify and improve performance for
>>> reduce grouping. The reduce itself would work just like Google's map-
>>> reduce by only reducing values that have the exact same map key. Then
>>> if you want to reduce further, you can just use another map-reduce
>>> step on top of that with the map emitting a different key so the
>>> reduce data will be grouped differently. For example, if you wanted a
>>> count of posts per user and total posts, you would implement it as a
>>> two-level map-reduce with the key=user_id for map1 and the key=null
>>> for map2.
>>>
>>> This way, you only calculate reduce values for groupings you care
>>> about, and any particular reduce value is immediately available from
>>> the cached B+tree values without further computation. There is more
>>> burden on the user to specify ahead of time which groupings they need,
>>> but the performance and flexibility would be well worth it. This
>>> eliminates the need to store reduce values internally in the map B
>>> +tree. But it does mean that you would need a B+tree for each reduce
>>> grouping to keep incremental reduce updates fast. The improved
>>> performance comes from the fact that view queries would never need to
>>> aggregate reduce values across multiple nodes or do any re-reducing.
>>>
>>> Does this make sense? What do you guys think? Have you discussed the
>>> possibility of such a feature?
>>>
>>> I'd be happy to discuss it further and even help with the
>>> implementation, though I've only done a little bit of coding in
>>> Erlang. I'm pretty sure this would mean big changes to the couchdb
>>> internals, so I want to get your opinions and criticisms before I get
>>> my hopes up or dive into any coding.
>>>
>>> Cheers,
>>> Justin Balthrop
>>>
>>> .
>>>
>>>
>> Possible solution, I use it in my production ...
>> https://issues.apache.org/jira/browse/COUCHDB-249
>
>



-- 
Chris Anderson
http://jchrisa.net
http://couch.io

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