Re: Help with tuning this query (with explain analyze finally)

>it might help the planner estimate better the number of cs rows
>affected. whether this improves performance depends on whether
>the best plans are sensitive to this.

I managed to try this and see if it did anything.  Unfortunately, it made no
difference.  It's still 250 milliseconds.  It was a good suggestion though.
I believed it work too.

> an EXPLAIN ANALYSE might reduce the guessing.

Okay, here is the explain analyze I managed to get from work.  It came out
to 312ms here, but without the analyze it actually runs at ~250ms.  It is
using indexes, so my guess is that there are too many joins or it's not
driving on person fast enough.  Release code is such a small table that I
dont think that sequencial scan matters.  Thanks for taking the time to
analyze this.

Sort  (cost=1902.27..1902.31 rows=17 width=91) (actual time=312.000..312.000
rows=39 loops=1)
  Sort Key: ss.date
  ->  Hash Join  (cost=617.07..1901.92 rows=17 width=91) (actual
time=234.000..312.000 rows=39 loops=1)
        Hash Cond: ("outer".carrier_code_id = "inner".id)
        ->  Merge Join  (cost=602.54..1882.73 rows=870 width=91) (actual
time=234.000..312.000 rows=310 loops=1)
              Merge Cond: ("outer".current_status_id = "inner".id)
              ->  Index Scan using shipment_current_status_id_idx on
shipment s  (cost=0.00..2552.13 rows=60327 width=66) (actual
time=0.000..61.000 rows=27711 loops=1)
                    Filter: (is_purged = false)
              ->  Sort  (cost=602.54..607.21 rows=1866 width=25) (actual
time=125.000..125.000 rows=6934 loops=1)
                    Sort Key: ss.id
                    ->  Hash Join  (cost=1.11..501.17 rows=1866 width=25)
(actual time=0.000..78.000 rows=6934 loops=1)
                          Hash Cond: ("outer".release_code_id = "inner".id)
                          ->  Index Scan using current_status_date_idx on
shipment_status ss  (cost=0.00..406.78 rows=14924 width=25) (actual
time=0.000..47.000 rows=15053 loops=1)
                                Index Cond: (date >= (('now'::text)::date -
31))
                                Filter: (id IS NOT NULL)
                          ->  Hash  (cost=1.10..1.10 rows=1 width=4) (actual
time=0.000..0.000 rows=0 loops=1)
                                ->  Seq Scan on release_code rc
(cost=0.00..1.10 rows=1 width=4) (actual time=0.000..0.000 rows=1 loops=1)
                                      Filter: ((number)::text = '9'::text)
        ->  Hash  (cost=14.53..14.53 rows=2 width=4) (actual
time=0.000..0.000 rows=0 loops=1)
              ->  Nested Loop  (cost=4.92..14.53 rows=2 width=4) (actual
time=0.000..0.000 rows=2 loops=1)
                    ->  Index Scan using person_pkey on person p
(cost=0.00..5.75 rows=1 width=4) (actual time=0.000..0.000 rows=1 loops=1)
                          Index Cond: (id = 355)
                    ->  Hash Join  (cost=4.92..8.75 rows=2 width=8) (actual
time=0.000..0.000 rows=2 loops=1)
                          Hash Cond: ("outer".id = "inner".carrier_id)
                          ->  Seq Scan on carrier c  (cost=0.00..3.54
rows=54 width=4) (actual time=0.000..0.000 rows=54 loops=1)
                          ->  Hash  (cost=4.92..4.92 rows=2 width=16)
(actual time=0.000..0.000 rows=0 loops=1)
                                ->  Hash Join  (cost=3.04..4.92 rows=2
width=16) (actual time=0.000..0.000 rows=2 loops=1)
                                      Hash Cond: ("outer".carrier_id =
"inner".carrier_id)
                                      ->  Seq Scan on carrier_code cc
(cost=0.00..1.57 rows=57 width=8) (actual time=0.000..0.000 rows=57 loops=1)
                                      ->  Hash  (cost=3.04..3.04 rows=1
width=8) (actual time=0.000..0.000 rows=0 loops=1)
                                            ->  Index Scan using
carrier_to_person_person_id_idx on carrier_to_person ctp  (cost=0.00..3.04
rows=1 width=8) (actual time=0.000..0.000 rows=1 loops=1)
                                                  Index Cond: (355 =
person_id)
Total runtime: 312.000 ms

Ken