Hi Thomas,

Your solution sounds interesting (looks like postgres hstore). But we are
(very) happy with our current stack, so we will not test it.

Jan-Marc

Op di 26 jan. 2016 om 12:40 schreef Thomas Beale <thomas.be...@openehr.org>:

>
> I have not performance tested my own implementation (although I did
> actually build one over a decade ago). But the Informix path system was
> real and performant (they used a hierachical number node code approach e.g.
> 1.2.3, 1.2.3.1.2 etc). There are others I have read about as well, but I'd
> have to spend a bit of time to track them down, not having looked at it for
> a few years.
>
> The reason why it can be fast is that you don't have many columns and
> essentially no joins, and you can do extremely efficient matching on number
> spaces to determine the 'type' of something (i.e. whether it is a systolic
> BP or whatever) *before* you decompress the value (a DV_QUANTITY). Then
> you do value comparison (e.g. bp > 160 or whatever) as a second step.
>
> Before doing any of this, you apply basic AQL logic that cuts out whole
> parts of the DB because their values are not inside (AQL CONTAINS; XML
> '//') the required kind of Composition.
>
> If you have run an actual study of path-based performance and found it not
> to be working, it would be very interesting to know the details. It may be
> that with some adjustments you can significantly change the performance
> characteristic.
>
>
> - thomas
>
>
> On 26/01/2016 10:43, Jan-Marc Verlinden wrote:
>
> Hi Thomas,
>
> *this is also what I would expect. Path-based storage does rely on very
> smart ways to figure match terms in a query to paths of course.*
>
> Did you test, or is this theoretical?
>
> Jan-Marc
>
>
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Jan-Marc Verlinden
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