Re: Performance issues with large amounts of time-series data
От
Tom Lane
Тема
Re: Performance issues with large amounts of time-series data
Дата
Msg-id
18555.1251312734@sss.pgh.pa.us
Ответ на
Re: Performance issues with large amounts of time-series
data (Hrishikesh (हृषीकेश मेहेंदळे))
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Performance issues with large amounts of time-series data Hrishikesh (हृषीकेश मेहेंदळे) <hashinclude@gmail.com>
Re: Performance issues with large amounts of time-series data Tom Lane <tgl@sss.pgh.pa.us>
Re: Performance issues with large amounts of time-series
data Hrishikesh (हृषीकेश मेहेंदळे) <hashinclude@gmail.com>
Re: Performance issues with large amounts of time-series data Tom Lane <tgl@sss.pgh.pa.us>
Re: Performance issues with large amounts of time-series data Greg Stark <gsstark@mit.edu>
Re: Performance issues with large amounts of time-series
data Greg Smith <gsmith@gregsmith.com>
Re: Performance issues with large amounts of time-series
data Hrishikesh (हृषीकेश मेहेंदळे) <hashinclude@gmail.com>
=?UTF-8?B?SHJpc2hpa2VzaCAo4KS54KWD4KS34KWA4KSV4KWH4KS2IOCkruClh+CkueClh+CkguCkpuCksw==?= =?UTF-8?B?4KWHKQ==?= writes:
> 2009/8/26 Tom Lane
>> Do the data columns have to be bigint, or would int be enough to hold
>> the expected range?
> For the 300-sec tables I probably can drop it to an integer, but for
> 3600 and 86400 tables (1 hr, 1 day) will probably need to be BIGINTs.
> However, given that I'm on a 64-bit platform (sorry if I didn't
> mention it earlier), does it make that much of a difference?
Even more so.
> How does a float ("REAL") compare in terms of SUM()s ?
Casting to float or float8 is certainly a useful alternative if you
don't mind the potential for roundoff error. On any non-ancient
platform those will be considerably faster than numeric. BTW,
I think that 8.4 might be noticeably faster than 8.3 for summing
floats, because of the switch to pass-by-value for them.
regards, tom lane
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