Map_reduce () * and * find () in the same query

Question

I found some map_reduce tutorials, but none of them seem to have a where clause or any other way to exclude documents / records from what is being considered. I am working on a seemingly easy request. I have a main event log file with timestamps, IP addresses, and campaign IDs. I want to get the number of unique users within a given time range for this campaign. It sounds easy!

I built a request object that looks something like this:

{'ts': {'$gt': 1345840456, '$lt': 2345762454}, 'cid': '2636518'}

With this I tried two things: one using different ones, and the other with map_reduce:

Distinct

db.alpha2.find(query).distinct('ip').count()

In the mongo shell, you can put the request as the second parameter of a separate function, and it works there, but I read that you cannot do this in pymongo.

Map_reduce

 map = Code("function () {" " emit(this.ip, 1);" "}") reduce = Code("function (key, values) {" " var total = 0;" " for (var i = 0; i < values.length; i++) {" " total += values[i];" " }" " return total;" "}") totaluniqueimp = db.alpha2.map_reduce(map, reduce, "myresults").count(); 

(I understand that the reduction function does things that I don’t need, I took this from the demo). This works great, but does not use my "where" options. I try this:

 totaluniqueimp = db.alpha2.find(query).map_reduce(map, reduce, "myresults").count();` 

And I get this error:

 AttributeError: 'Cursor' object has no attribute 'map_reduce' 

Conclusion

Basically, this is what I am trying to do in mysql:

 select count(*) from records where ts<1000 and ts>900 and campaignid=234 group by ipaddress 

It seems so simple! How do you do this in mongo?

UPDATE: ANSWER

Based on Dmitry's answer below, I was able to solve (and simplify) my solution (is it as simple as how can I do this?):

 #query is an object that was built above this map = Code("function () { emit(this.ip, 1);}") reduce = Code("function (key, values) {return 1;}") totaluniqueimp = collection.map_reduce(map, reduce, "myresults", query=query).count(); 

Thank you Dmitry!

Answer 1

You can try:

 totaluniqueimp = db.alpha2.map_reduce(map, reduce, { out: "myresults", query: {'ts': {'$gt': 1345840456, '$lt': 2345762454}, 'cid': '2636518'} }).count(); 

UPDATE: the above statement works in mongo shell. In pymongo you should add the query as the fourth parameter:

 totaluniqueimp = db.alpha2.map_reduce(map, reduce, "myresults", query={'ts': {'$gt': 1345840456, '$lt': 2345762454}, 'cid': '2636518'}) 

Detailed documentation can be found here .

Answer 2

Not sure if this is possible with pymongo, the manual indicates what it should be, but in the mongoDB shell you have a group () function that will easily allow you to rewrite SQL into your question:

 select count(*) from records where ts<1000 and ts>900 and campaignid=234 group by ipaddress; 

how

 db. alpha2.group( { cond: { 'ts': {'$gt': 900, '$lt': 1000}, 'campaignid': '234' } , key: { "ipaddress" : 1 } , initial: {count : 0} , reduce: function(doc, out){ out.count++} } );