Thread: SQL With Dates

BETWEEN X AND Y

On Mon, Apr 20, 2009 at 2:55 PM, Rafael Domiciano
<rafael.domiciano@gmail.com> wrote:
> Hello People,
>
> I have initiated a work to review the sqls of our internal software.
> Lot of them he problem are about sql logic, or join with table unecessary,
> and so on.
> But software has lot of sql with date, doing thinks like:
> [..]
>   date >= '2009-04-01' AND
>   date <= '2009-04-15'
> [..]
>
> Redoing the SQL with fix date (date = '2009-04-01') o cost in explain always
> still about 200 or less. But with a period the cost is high, about 6000 or
> more.
>
> Select is using Index and the date is using index too.
>
> There is some way to use date period with less cost?
>
> Rafael Domiciano
>



--
GJ

On Mon, Apr 20, 2009 at 7:55 AM, Rafael Domiciano
<rafael.domiciano@gmail.com> wrote:
> Hello People,
>
> I have initiated a work to review the sqls of our internal software.
> Lot of them he problem are about sql logic, or join with table unecessary,
> and so on.
> But software has lot of sql with date, doing thinks like:
> [..]
>   date >= '2009-04-01' AND
>   date <= '2009-04-15'
> [..]
>
> Redoing the SQL with fix date (date = '2009-04-01') o cost in explain always
> still about 200 or less. But with a period the cost is high, about 6000 or
> more.

Yep.  Because you'll be getting more rows. More rows == more cost.  TANSTAAFL.

It sounds like what you're doing is comparing the planner's cost
estimate from running EXPLAIN on a few different queries.  The planner's
cost estimate was never intended to do what you're trying to do; it's
not an absolute scale of cost, it's just a tool that the planner uses to
get relative comparisons of logically equivalent plans.

The actual number that the planner spits out is meaningless in an
absolute sense.  It's entirely possible that one query with an estimated
cost of 10000 will run faster than a query with an estimated cost of
100.  What you actually need to do is compare the real running time of
the queries in order to see which ones are actually problematic.

For that, you'd do better using a tool like pgFouine to look at actual
performance trends.

-- Mark


On Mon, 2009-04-20 at 10:55 -0300, Rafael Domiciano wrote:
> Hello People,
>
> I have initiated a work to review the sqls of our internal software.
> Lot of them he problem are about sql logic, or join with table
> unecessary, and so on.
> But software has lot of sql with date, doing thinks like:
> [..]
>   date >= '2009-04-01' AND
>   date <= '2009-04-15'
> [..]
>
> Redoing the SQL with fix date (date = '2009-04-01') o cost in explain
> always still about 200 or less. But with a period the cost is high,
> about 6000 or more.
>
> Select is using Index and the date is using index too.
>
> There is some way to use date period with less cost?
>
> Rafael Domiciano

On Mon, Apr 20, 2009 at 9:55 AM, Rafael Domiciano
<rafael.domiciano@gmail.com> wrote:
> Hello People,
>
> I have initiated a work to review the sqls of our internal software.
> Lot of them he problem are about sql logic, or join with table unecessary,
> and so on.
> But software has lot of sql with date, doing thinks like:
> [..]
>   date >= '2009-04-01' AND
>   date <= '2009-04-15'
> [..]
>
> Redoing the SQL with fix date (date = '2009-04-01') o cost in explain always
> still about 200 or less. But with a period the cost is high, about 6000 or
> more.
>
> Select is using Index and the date is using index too.
>
> There is some way to use date period with less cost?

If you have an actual performance problem (as opposed to a big number
in EXPLAIN), then it's possible that the planner isn't estimating the
number of rows that will be in that range very accurately.  In that
case, you might need to increase the statistics target for that
column, or your default_statistics_target.

In 8.3, the default default_statistics_target = 10.  In 8.4, it will
be 100, so you might try that for a starting point.  But date columns
can sometimes have highly skewed data, so you might find that you need
an even higher value for that particular column.  I wouldn't recommend
raising the database-wide setting above 100 though (though I know some
people have used 200 or 400 without too much pain, especially on
Really Big Databases where longer planning time isn't a big deal
because the execution times are measured in minutes - it doesn't sound
like that's your situation though).

The first thing, to do, is see how fast the query actually runs.  Try
setting \timing in psql and running the query to see how long it
actually takes.  If it's fast enough, you're done.  If not, run
EXPLAIN ANALYZE and compare the estimated row counts to t he actual
row counts.  If they're pretty close, you're out of luck - as others
have already said, TANSTAAFL.  If they're way off, the try the above.

...Robert