Mongo DB Map-Reduce for Group-By w/ extra fields

So, I was trying to do a query similar to the following:

select field_a, max(field_b) as maxb from tableA group by field_a

But, when I found field_a, I needed another field from that record. This would be straightforward in SQL with a subselect or join, but MongoDB on a sharded DB requires some Map-Reduce foo.

The problem is that reduce only allows you to return one value. But, I needed both the accumulation value AND another field to come back. Solved via this test program:

from pprint import pprint, pformat
from pymongo.code import Code
from pymongo import Connection

conn = Connection()
db  = conn["test"]
db.testcol.remove() 
db.testcol.insert({  "name" : "bob",  "val" : 5, "host":"blah1"})
db.testcol.insert({  "name" : "bob",  "val" : 3, "host":"blah2"})
db.testcol.insert({  "name" : "bob",  "val" : 7, "host":"blah3"})
db.testcol.insert({  "name" : "john", "val" : 2, "host":"blah4"})
db.testcol.insert({  "name" : "john", "val" : 4, "host":"blah5"})
db.testcol.insert({  "name" : "john", "val" : 8, "host":"blah6"})
db.testcol.insert({  "name" : "john", "val" : 6, "host":"blah7"})
#print "Data: "
#print pformat(list(db.testcol.find()))

mapfunc = Code(''' function() { emit( this.name, { name : this.name, val: this.val, host: this.host }); } ''')

redfunc = Code(''' function(key, values) { 
    var latestRec  = { val: 0, host: "", name: ""};
    for (var i=1; i < values.length; i++) {
        thisName = values[i].name
        thisVal  = values[i].val; 
        thisHost = values[i].host;
        if (thisVal > latestRec.val) { 
            latestRec.name = thisName
            latestRec.val  = thisVal;
            latestRec.host = thisHost;
            }
        }
    return latestRec
    } ''')

res = db.testcol.map_reduce(mapfunc, redfunc, "myresults")
for doc in res.find():
    print doc

print "*" * 80
conn.close()