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From Jan Lehnardt <>
Subject Re: view index build time
Date Wed, 02 Jul 2008 14:50:48 GMT

On Jul 2, 2008, at 16:17, Brad King wrote:

> Just to post some results here of working with around 300K docs. I
> changed the view to emit only the doc ID and index time went down to
> about 25 minutes vs. an hour for the same dataset.
> I then converted the largest text field to an attachment and things
> went down hill from there. I deleted the db and started the upload,
> but repeatedly got random 500 server errors with no real way to know
> what is happening or why. Also the DB size as reported by Futon seemed
> to fluctuate wildly as I was adding documents. And I mean wildly like
> anywhere from 1.2G then back down to 144M. Weird. I don't get a very
> warm fuzzy feeling about the stability of using attachments right now.
> Ideally, I don't want to use them anyway, I'd prefer to have the
> fields all inline and have the database handle these docs as-is. I
> don't see these as huge documents (2 to 5K) as compared to what I
> would store in something like Berkeley DB XML, just for comparison
> sake, so I'm hoping its a goal of the project to handle these
> effectively, even when several million documents are added.

This doesn't sound right at all. Can you make sure you use the
very latest SVN version or the 0.8 release and completely
new databases? Also, just to clarify, do you emit the doc into
the view payload? As in emit(doc._id, doc); are you just doing
emit(null, null); to only get the docIds that matter to you and
then fetch the documents later? I have had the later setup running
without any problems across ~2mio documents in a database.

> As always, thanks for the help.

Thanks for the problem report.


> On Tue, Jul 1, 2008 at 9:26 AM, Brad King <> wrote:
>> Thanks for the tips. I'll start scaling back the data I'm returning
>> and see if it improves. The largest field is an html description of  
>> an
>> inventory item, which seems like a good candidate for a binary
>> attachment, but I need to be able to do full text searches on this
>> data eventually (hopefully with the Lucene integration) so I'll
>> probably try just not including the document data in the views first.
>> We've had some success with Lucene independent of couchdb, so I'm
>> pleased you guys are integrating this.
>> On Sat, Jun 21, 2008 at 8:39 AM, Damien Katz <>  
>> wrote:
>>> Part of the problem is you are storing copies of the documents  
>>> into the
>>> btree. If the documents are big, it takes longer to compute on  
>>> them, and if
>>> the results (emit(...)) are big or numerous, then you'll be  
>>> spending most of
>>> your time in I/O.
>>> My advice is to not emit the document into the view, and if you  
>>> can, get the
>>> documents smaller in general. If the data can stored as an binary
>>> attachment, then that too will give you a performance improvement.
>>> -Damien
>>> On Jun 20, 2008, at 4:51 PM, Brad King wrote:
>>>> Thanks, yes its currently at 357M and growing!
>>>> On Fri, Jun 20, 2008 at 4:49 PM, Chris Anderson <> 

>>>> wrote:
>>>>> Brad,
>>>>> You can look at
>>>>> ls -lha /usr/local/var/lib/couchdb/.my-dbname_design/
>>>>> to see the view size growing...
>>>>> It won't tell you when it's done but it will give you hope that  
>>>>> the
>>>>> progress is happening.
>>>>> Chris
>>>>> On Fri, Jun 20, 2008 at 1:45 PM, Brad King <> 

>>>>> wrote:
>>>>>> I have about 350K documents in a database. typically around 5K  
>>>>>> each. I
>>>>>> created and saved a view which simply looks at one field in the
>>>>>> document. I called the view for the first time with a key that  
>>>>>> should
>>>>>> only match one document, and its been awaiting a response for  
>>>>>> about 45
>>>>>> minutes now.
>>>>>> {
>>>>>> "sku": {
>>>>>>    "map": "function(doc) { emit(doc.entityobject.SKU, doc); }"
>>>>>> }
>>>>>> }
>>>>>> Is this typical, or is there some optimizing to be done on  
>>>>>> either my
>>>>>> view or the server? I'm also running on a VM so this may have  
>>>>>> some
>>>>>> effects, but smaller databases seem to be performing pretty well.
>>>>>> Insert times to set this up were actually really good I  
>>>>>> thought, at
>>>>>> 4000 to 5000 documents per minute running from my laptop.
>>>>> --
>>>>> Chris Anderson

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