如果你用group 命令的话可能会遇到下面两种错误：

a.)命令：db.flogsamplelog.group({cond:{datetimes":20111027},key:{"pid":"1"},initial:{"count":0},reduce:function(doc,prev){if(doc.pid==prev.pid)prev.count++;}})

error:

Mon Oct 31 12:00:00uncaught exception: group command failed: { 
"errmsg" : "exception: group() can't handle more than 10000 unique keys", 
"code" : 10043, 
"ok" : 0 
} 直接访问shard server端口

b.)命令：db.flogsamplelog.group({cond:{"pid":322963713,"datetimes":20111027},key:{"worktype":"1"},initial:{"count":0},reduce:function(doc,prev){if(doc.worktype==prev.worktype)prev.count++;}})

error：
Mon Oct 31 12:00:09 uncaught exception: group command failed: { "ok" : 0, "errmsg" : "can't do command: group on sharded collection" } 直接访问route server端口

其次我们在mongodb权威指南上也能发现这样的语句:

The price of using MapReduce is speed: group is not particularly speedy, but
MapReduce is slower and is not supposed to be used in “real time.” You run
MapReduce as a background job, it creates a collection of results, and then 
you can query that collection in real time.

经过测试发现group by效率在建立索引之后也没有实质性提高。

具体命令中涉及到的字段以及表定义，这里就不在敷衍。