Rainer Mager wrote:
I'm looking for some help in speeding up searches. My table is pretty simple
(see below), but somewhat large, and continuously growing. Currently it has
about 50 million rows.
Regarding your use of LIKE:
(1)If you are able to specify the beginning character(s) of the
statement you are searching for, you will have a better chance of your
statement using an index. If you specify a wildcard(%) before the search
string, the entire string in the column must be searched therefore no
index will be used.
(2) Reorder your where clause to reduce the size of the set that LIKE
operates on. In your example below, put the BETWEEN before the LIKE.
(3) Consider the use of trigrams instead of LIKE. I have not used it but
I notice that postgres supports trigrams:
The pg_trgm module provides functions and operators for determining the
similarity of text based on trigram matching, as well as index operator
classes that support fast searching for similar strings.
Here is the link: http://www.postgresql.org/docs/current/static/pgtrgm.html
--cheers
HH
The table is (I know I have excessive indexes, I'm trying to get the
appropriate ones and drop the extras):
Table "public.ad_log"
Column | Type |
Modifiers
--------------+-----------------------------+-------------------------------
-----------------------------
ad_log_id | integer | not null default
nextval('ad_log_ad_log_id_seq'::regclass)
channel_name | text | not null
player_name | text | not null
ad_name | text | not null
start_time | timestamp without time zone | not null
end_time | timestamp without time zone | not null
Indexes:
"ad_log_pkey" PRIMARY KEY, btree (ad_log_id)
"ad_log_channel_name_key" UNIQUE, btree (channel_name, player_name,
ad_name, start_time, end_time)
"ad_log_ad_and_start" btree (ad_name, start_time)
"ad_log_ad_name" btree (ad_name)
"ad_log_all" btree (channel_name, player_name, start_time, ad_name)
"ad_log_channel_name" btree (channel_name)
"ad_log_end_time" btree (end_time)
"ad_log_player_and_start" btree (player_name, start_time)
"ad_log_player_name" btree (player_name)
"ad_log_start_time" btree (start_time)
The query I'm trying to speed up is below. In it the <field> tag can be one
of channel_name, player_name, or ad_name. I'm actually trying to return the
distinct values and I found GROUP BY to be slightly faster than using
DISTINCT. Also, any of those fields may be unspecified in the WHERE clauses
in which case we use '%', but it seems Postgres optimizes that pretty well.
SELECT <field> FROM ad_log
WHERE channel_name LIKE :channel_name
AND player_name LIKE :player_name
AND ad_name LIKE :ad_name
AND start_time BETWEEN :start_date AND (date(:end_date) + 1)
GROUP BY <field> ORDER BY <field>
A typical query is:
explain analyze SELECT channel_name FROM ad_log WHERE channel_name LIKE '%'
AND ad_name LIKE '%' AND start_time BETWEEN '2008-07-01' AND
(date('2008-07-28') + 1) GROUP BY channel_name ORDER BY channel_name;
with the result being:
QUERY PLAN
----------------------------------------------------------------------------
----------------------------------------------------------------------------
-------
Sort (cost=1163169.02..1163169.03 rows=5 width=10) (actual
time=75460.187..75460.192 rows=15 loops=1)
Sort Key: channel_name
Sort Method: quicksort Memory: 17kB
-> HashAggregate (cost=1163168.91..1163168.96 rows=5 width=10) (actual
time=75460.107..75460.114 rows=15 loops=1)
-> Bitmap Heap Scan on ad_log (cost=285064.30..1129582.84
rows=13434427 width=10) (actual time=8506.250..65771.597 rows=13701296
loops=1)
Recheck Cond: ((start_time >= '2008-07-01
00:00:00'::timestamp without time zone) AND (start_time <=
'2008-07-29'::date))
Filter: ((channel_name ~~ '%'::text) AND (ad_name ~~
'%'::text))
-> Bitmap Index Scan on ad_log_start_time
(cost=0.00..281705.70 rows=13434427 width=0) (actual time=8488.443..8488.443
rows=13701296 loops=1)
Index Cond: ((start_time >= '2008-07-01
00:00:00'::timestamp without time zone) AND (start_time <=
'2008-07-29'::date))
Total runtime: 75460.361 ms
It seems to me there should be some way to create an index to speed this up,
but the various ones I've tried so far haven't helped. Any suggestions would
be greatly appreciated.
--
H. Hall
ReedyRiver Group LLC
http://www.reedyriver.com
