Thread: Improving GEQO

Hello, my partner and me are working with the goal of improve the GEQO's performance, we tried with Ant Colony Optimization, but it does not improve, actually we are trying with a new variant of Genetic Algorithm, specifically Micro-GA. This algorithm finds a better solution than GEQO in less time, however the total query execution time is higher. The fitness is calculated by geqo_eval function. Does anybody know why this happens?

We attach the patch made with the changes in postgresql-9.2.0.
Regards.

boix <boix@uclv.cu> writes:
> Hello, my partner and me are working with the goal of improve the GEQO's 
> performance, we tried with Ant Colony Optimization, but it does not 
> improve, actually we are trying with a new variant of Genetic Algorithm, 
> specifically Micro-GA. This algorithm finds a better solution than GEQO 
> in less time, however the total query execution time is higher. The 
> fitness is calculated by geqo_eval function. Does anybody know why this 
> happens?

Well, for one thing, you can't just do this:

+                    aux = aux1;

without totally confusing all your subsequent steps.

You'd want to copy the pointed-to data, likely, not the pointer.
        regards, tom lane

boix <boix@uclv.cu> writes:

Hello, my partner and me are working with the goal of improve the GEQO's

performance, we tried with Ant Colony Optimization, but it does not 
improve, actually we are trying with a new variant of Genetic Algorithm,

specifically Micro-GA. This algorithm finds a better solution than GEQO 
in less time, however the total query execution time is higher. The 
fitness is calculated by geqo_eval function. Does anybody know why this 
happens?

Well, for one thing, you can't just do this:

+					aux = aux1;

without totally confusing all your subsequent steps.

You'd want to copy the pointed-to data, likely, not the pointer.
		regards, tom lane

On Wed, May 27, 2015 at 3:06 PM, boix <boix@uclv.cu> wrote:
> Hello, my partner and me are working with the goal of improve the GEQO's
> performance, we tried with Ant Colony Optimization, but it does not improve,
> actually we are trying with a new variant of Genetic Algorithm, specifically
> Micro-GA. This algorithm finds a better solution than GEQO in less time,
> however the total query execution time is higher. The fitness is calculated
> by geqo_eval function. Does anybody know why this happens?
>
> We attach the patch made with the changes in postgresql-9.2.0.

can you submit more details?  for example 'explain analyze' (perhaps
here: http://explain.depesz.com/) of the plans generated GEQO vs GA vs
stock?  It sounds like you might be facing an estimation miss which is
not really an issue a better planner could solve.

That said, assuming you're getting 'better' plans in less time suggest
you might be on to something.

merlin