On Mar 28, 2012, at 12:50 AM, Simon wrote:
> - Look at sqlite's source code and try to implement analytical functions
> in a way that leads to an optimization better than log(n^2) and contribute
> my findings on this topic back to the community.
Enhancing SQLite with analytics would be a
Simon Slavin wrote:
On 27 Mar 2012, at 11:50pm, Simon wrote:
Thank you all very much for all your answers, they have been most useful.
You're welcome. Something else to consider is whether you should be doing this
in C. C++ can do everything, but it's not ideally
On 27 Mar 2012, at 11:50pm, Simon wrote:
> Thank you all very much for all your answers, they have been most useful.
You're welcome. Something else to consider is whether you should be doing this
in C. C++ can do everything, but it's not ideally suited to heavy
>
> I would love to do an sql query that would look like the following
> ones. I wonder if they are possible and valid applications for SQL and
> what would be the proper implementation for these. I know I can calculate
> all this using C, but it would be most useful (to my later projects) to
> I think it is possible to create a custom aggregate function which would
> work on a cross-join of the data to analyse. The cross-join makes all the
> data available to each bucket (group by Date, for example), and each
bucket
> is basically one row of the whole data. The aggregate function
On 27 Mar 2012, at 9:47pm, Simon wrote:
> But I don't think aggregates is the key here... Basically, the kind of
> function I need is something like this:
> For each row, in this column, calculate the foobar result on all (or a
> group of) the values of another column.
> I
>
> A DBMS is a good way to keep your raw data. But I highly doubt that a
> majority of your analysis algorithms are going to be expressible in SQL
> without going way beyond the intended purpose of the language.
I think you are right, but the cases where it can be expressed in SQL means
it can
> Generally speaking, analytical functions (aka windowing functions [1])
> would appear to be the most useful for your endeavor.
>
> Sadly, SQLite doesn't provide anything like this out-of-the-box.
>
I wasn't aware of the term. Thanks! I'll be able to google on that now!
;)
And here are
On Tue, Mar 27, 2012 at 3:02 PM, Simon wrote:
> select closing_price, moving_average( funky_oscillator( closing_price ) )...
There is a moving average calculation in SQLite here but given the
complexity you might prefer to do the analytical portion in your
program:
On Mar 27, 2012, at 3:46 PM, Larry Brasfield wrote:
> A DBMS is a good way to keep your raw data. But I highly doubt that a
> majority of your analysis algorithms are going to be expressible in SQL
> without going way beyond the intended purpose of the language. You will
> either find
Hi there,
I'm about to start a project I have been thinking about for a long
while. I basically wish to analyse stock market data. I already have the
data in a table and I'm now in the process of writing my own indicators and
oscillators. I hope to learn while re-inventing this wheel and
On Mar 27, 2012, at 9:02 PM, Simon wrote:
> I would love to do an sql query that would look like the following ones.
> I wonder if they are possible and valid applications for SQL and what would
> be the proper implementation for these.
Generally speaking, analytical functions (aka windowing
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