Ok didnt know if the sheer number of gets would be a limiting factor. Thanks

On Tue, Apr 29, 2014 at 7:57 PM, Ted Yu <[email protected]> wrote:
> As I said this afternoon:
> See the following API in HTable for batching Get's :
>
>   public Result[] get(List<Get> gets) throws IOException {
>
> Cheers
>
>
> On Tue, Apr 29, 2014 at 7:45 PM, Software Dev 
> <[email protected]>wrote:
>
>> Nothing against your code. I just meant that if we are doing a scan
>> say for hourly metrics across a 6 month period we are talking about
>> 4K+ gets. Is that something that can easily be handled?
>>
>> On Tue, Apr 29, 2014 at 5:08 PM, Rendon, Carlos (KBB) <[email protected]>
>> wrote:
>> >> Gets a bit hairy when doing say a shitload of gets thought.. no?
>> >
>> > If you by "hairy" you mean the code is ugly, it was written for maximal
>> clarity.
>> > I think you'll find a few sensible loops makes it fairly clean.
>> > Otherwise I'm not sure what you mean.
>> >
>> > -----Original Message-----
>> > From: Software Dev [mailto:[email protected]]
>> > Sent: Tuesday, April 29, 2014 5:02 PM
>> > To: [email protected]
>> > Subject: Re: Help with row and column design
>> >
>> >> Yes. See total_usa vs. total_female_usa above. Basically you have to
>> pre-store every level of aggregation you care about.
>> >
>> > Ok I think this makes sense. Gets a bit hairy when doing say a shitload
>> of gets thought.. no?
>> >
>> > On Tue, Apr 29, 2014 at 4:43 PM, Rendon, Carlos (KBB) <[email protected]>
>> wrote:
>> >> You don't do a scan, you do a series of gets, which I believe you can
>> batch into one call.
>> >>
>> >> last 5 days query in pseudocode
>> >> res1 = Get( hash("2014-04-29") + "2014-04-29")
>> >> res2 = Get( hash("2014-04-28") + "2014-04-28")
>> >> res3 = Get( hash("2014-04-27") + "2014-04-27")
>> >> res4 = Get( hash("2014-04-26") + "2014-04-26")
>> >> res5 = Get( hash("2014-04-25") + "2014-04-25")
>> >>
>> >> For each result you look for the particular column or columns you are
>> >> interested in Total_usa = res1.get("c:usa") + res2.get("c:usa") +
>> res3.get("c:usa") + ...
>> >> Total_female_usa = res1.get("c:usa:sex:f") + ...
>> >>
>> >> "What happens when we add more fields? Do we just keep adding in more
>> column qualifiers? If so, how would we filter across columns to get an
>> aggregate total?"
>> >>
>> >> Yes. See total_usa vs. total_female_usa above. Basically you have to
>> pre-store every level of aggregation you care about.
>> >>
>> >> -----Original Message-----
>> >> From: Software Dev [mailto:[email protected]]
>> >> Sent: Tuesday, April 29, 2014 4:36 PM
>> >> To: [email protected]
>> >> Subject: Re: Help with row and column design
>> >>
>> >>> The downside is it still has a hotspot when inserting, but when
>> >>> reading a range of time it does not
>> >>
>> >> How can you do a scan query between dates when you hash the date?
>> >>
>> >>> Column qualifiers are just the collection of items you are
>> >>> aggregating on. Values are increments. In your case qualifiers might
>> >>> look like c:usa, c:usa:sex:m, c:usa:sex:f, c:italy:sex:m,
>> >>> c:italy:sex:f, c:italy,
>> >>
>> >> What happens when we add more fields? Do we just keep adding in more
>> column qualifiers? If so, how would we filter across columns to get an
>> aggregate total?
>>

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