Maybe related: a typical reduce function I use to sum on objects:
function (keys, values, rereduce) {
var sums = {};
for (var i in values) {
for (var k in values[i]) {
sums[k] = (sums[k]||0)+values[i][k];
}
}
return sums;
}
which sums emited keys as follows:
emit("somekey",{"A":1});
emit("somekey",{"B":2});
emit("somekey",{"A":1,"C":1});
emit("somekey",{"A":1,"B":2});
reduced output:
"somekey": {"A":3,"B":4,"C":1}
but, I guess the array approach is more efficient, as it uses less space by
using indexes instead of keys...
- Mathias
On 31.01.2011, at 12:07, John wrote:
> That's perfect, thanks Robert. Funny how something so simple can be so
> confusing if the concept is new to you.......
>
> For anyone who searches for how to do a reduce over an array in the future,
> here's the code:
>
> function(keys, values, rereduce){
>
> var total = [0,0];
> values.forEach(function(value){
> total[0] += value[0];
> total[1] += value[1];
> }
>
> )
> return total;
> }
>
> Looks like I might get to add reporting to my successful use cases for
> Couchdb!
>
> John
>
>
> On 31 Jan 2011, at 09:01, Robert Newson wrote:
>
>> in 1.1, _sum will work for arrays of numbers too (rather than
>> concatenating them as above). for now, just loop over the array of
>> arrays and do the sum yourself.
>>
>> On Mon, Jan 31, 2011 at 1:02 AM, Keith Gable <[email protected]>
>> wrote:
>>> It sounds like you need a new view for each piece of data.
>>>
>>> by_answered, by_busy, by_time_to_answer, etc.
>>>
>>> Then you'd query each view to get the reduction, and the reduce would be as
>>> simple as _sum.
>>>
>>>
>>>
>>> On Jan 30, 2011, at 5:55 PM, John <[email protected]> wrote:
>>>
>>>> Hi
>>>>
>>>> I'm looking to extend our usage of couchdb by replacing our mysql
>>>> reporting db.
>>>> Whilst using couchdb successfully for a number of varied use cases I've
>>>> never had to do much with reduce so I'm unsure on how to use it to reduce
>>>> an
>>>> array of values.
>>>>
>>>> Basically I want to be able to search a database using a composite key and
>>>> retrieving some aggregated information about number of calls, call status,
>>>> avg time to answer and avg duration
>>>>
>>>>
>>>> The following view shows how I'd like it to work:
>>>>
>>>> Key = <Application, Account, Subscription>
>>>> Value = <1, answered, busy, noreply, time to answer, duration>
>>>>
>>>> e.g.
>>>>
>>>> ["NTS", "NetDev", "MySub1"], [1,1,0,0,100,200]
>>>> ["NTS", "NetDev", "MySub1"], [1,1,0,0,150,400]
>>>> ["NTS", "NetDev", "MySub1"], [1,1,0,0,170,500]
>>>> ["NTS", "NetDev", "MySub1"], [1,0,1,0,0,0]
>>>> ["NTS", "NetDev", "MySub1"], [1,0,1,0,0,0]
>>>> ["NTS", "NetDev", "MySub1"], [1,0,0,2,0,0]
>>>> ["NTS", "NetDev", "MySub1"], [1,0,0,2,0,0]
>>>>
>>>> My Reduced output should look like this:
>>>>
>>>> [7,3,2,2,420,1100]
>>>> i.e. 7 calls in total, 3 answered, 2 busy, 2 no reply, the total time for
>>>> time to answer is 420 and the total time for call duration is 1100.
>>>>
>>>> I can then compute the two averages after getting the data back from couch
>>>> i.e. 420/no. of answered calls(3) and 1100/no. of answered calls(3)
>>>>
>>>> I thought that sum(values) would do this for me but it just upsets couch:
>>>>
>>>> Reduce output must shrink more rapidly: Current output:
>>>> '["001,11,11,11,11,11,11,11,11,11,11,101,11,11,11,11,11,11,11,11,11,11,11,101,11,11,11,11,11,11,11,11'...
>>>> (first 100 of 277 bytes)
>>>>
>>>> What should my reduce function look like?
>>>>
>>>> Thanks
>>>>
>>>> John
>>>
>
