Optimizing queries over date ranges in MongoDb (with other fields) -

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i'm building scheduling/booking system bunch of providers serve customers @ bunch of locations on times.

my appointment object looks this:

{     "providername" : {"type": "string"},     "location" : {"type": "string"},     "starttime" : {"type": "tba"},     "endtime" : {"type": "tba"}, }

the appointments stored in mongodb , i'll need run lot of searches 4 fields set (there 10-20 searches each insertion, i'm optimizing reads here).

i'm thinking store start , end times in milliseconds, , set compound index on these two, set 2 separate indices on provider name , location.

but i'm wondering whether can improve performance (end reduce load on server) using optimizations:

  • what's more efficient range queries - storing start/end time milliseconds/long or java.util.date or maybe string?

  • if i'm interested in searches date only, perhaps should represent time string (e.g. 2015/10/11) , search lexicographic range? , in case, if i'm looking range of 10 days, better off single range query or running 10 threads each 1 hashed key search each date?

  • do want use compound index , whether can optimize mongodb search strategy (e.g. want minimize number of documents scanned)?

thanks!


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