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| From | Ian Kelly <ian.g.kelly@gmail.com> |
| Date | Fri, 20 Jul 2012 12:14:30 -0600 |
| Subject | Re: best way to handle this in Python |
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On Fri, Jul 20, 2012 at 4:34 AM, Rita <rmorgan466@gmail.com> wrote: > Thats an interesting data structure Dennis. I will actually be running this > type of query many times preferable in an ad-hoc environment. That makes it > tough for sqlite3 since there will be several hundred thousand tuples. Several hundred thousand is not an enormous number. I think you're underestimating sqlite3. I just tried a test with one million tuples, six colors per tuple (six million rows altogether). Each row contains a primary key, a timestamp, a color, and a count, with an index on the timestamp column. Building the database from scratch took about a minute; adding the index took about another minute. Incremental updates would of course be much faster. Queries like "select * from data where timestamp between 500000 and 600000" return instantly (from a user perspective). Cheers, Ian
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Re: best way to handle this in Python Ian Kelly <ian.g.kelly@gmail.com> - 2012-07-20 12:14 -0600 Re: best way to handle this in Python Steven D'Aprano <steve+comp.lang.python@pearwood.info> - 2012-07-21 00:43 +0000
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