Re: Query optimization

On Thu, Mar 13, 2025 at 11:25 PM Durgamahesh Manne <
maheshpostgres9(at)gmail(dot)com> wrote:

> On Fri, Mar 14, 2025 at 8:19 AM Ron Johnson <ronljohnsonjr(at)gmail(dot)com>
> wrote:
>
>> On Thu, Mar 13, 2025 at 10:16 PM Durgamahesh Manne <
>> maheshpostgres9(at)gmail(dot)com> wrote:
>> [snip]
>>
>>> Hi Adrian Klaver
>>>
>>> 1) Postgres version.
>>> select version();
>>> version
>>>
>>> ---------------------------------------------------------------------------------------------------------------
>>> PostgreSQL 14.12 on aarch64-unknown-linux-gnu, compiled by gcc (GCC)
>>> 7.3.1 20180712 (Red Hat 7.3.1-6), 64-bit
>>>
>>> 2) Complete(including indexes) table schema.
>>>
>>> Table
>>> "liveaggregations.cachekeys"
>>> Column | Type | Collation | Nullable | Default
>>> | Storage | Compression
>>>
>>> ---------------+------------------------+-----------+----------+---------+----------+------------
>>> cachetype | character varying(255) | | |
>>> | extended |
>>> trsid | character varying(255) | | |
>>> | extended |
>>> brandid | character varying(255) | | |
>>> | extended |
>>> sportid | character varying(255) | | |
>>> | extended |
>>> competitionid | character varying(255) | | |
>>> | extended |
>>> eventid | character varying(255) | | |
>>> | extended |
>>> marketid | character varying(255) | | |
>>> | extended |
>>> selectionid | character varying(255) | | |
>>> | extended |
>>> keytype | character varying(255) | | |
>>> | extended |
>>> key | character varying(255) | | not null |
>>> | extended |
>>> Indexes:
>>> "cachekeys_key_pk" PRIMARY KEY, btree (key)
>>> "idx_cachekeys" btree (cachetype, trsid, brandid, sportid,
>>> competitionid, eventid, marketid)
>>> "idx_marketid" btree (marketid)
>>>
>>> 3) Output of EXPLAIN ANALYZE of query.
>>>
>>> Result (cost=2.80..2.83 rows=1 width=1) (actual time=0.030..0.030
>>> rows=1 loops=1)
>>> InitPlan 1 (returns $0)
>>> -> Index Only Scan using idx_cachekeys on cachekeys
>>> (cost=0.55..2.80 rows=1 width=0) (actual time=0.029..0.029 rows=1 loops=1)
>>> Index Cond: ((cachetype = 'BoMatrix'::text) AND (trsid =
>>> 'daznbetuk'::text) AND (brandid = 'daznbet'::text) AND (sportid =
>>> 'BOX'::text) AND (competitionid = 'U-1998'::text) AND (eventid =
>>> 'U-523596'::text))
>>> Heap Fetches: 0
>>> Planning Time: 0.221 ms
>>> Execution Time: 0.046 ms
>>>
>>
>> That looks pretty reasonable.
>>
>> 1. Now show what happens with the LIMIT clause.
>> 2. How many rows does it return?
>> 3. Do you keep the table regularly vacuumed and analyzed?
>>
>> Hey Ron
>
> 1. Now show what happens with the LIMIT clause.
> and result set of query and *Size of the table 287MB*
> exists
> --------
> t
> (1 row)
>
> --------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
> Result (cost=2.80..2.83 rows=1 width=1) (actual time=0.029..0.030 rows=1
> loops=1)
> InitPlan 1 (returns $0)
> -> Index Only Scan using idx_cachekeys on cachekeys
> (cost=0.55..2.80 rows=1 width=0) (actual time=0.028..0.028 rows=1 loops=1)
> Index Cond: ((cachetype = 'BoMatrix'::text) AND (trsid =
> 'daznbetuk'::text) AND (brandid = 'daznbet'::text) AND (sportid =
> 'BOX'::text) AND (competitionid = 'U-1998'::text) AND (eventid =
> 'U-523596'::text))
> Heap Fetches: 1
> Planning Time: 0.084 ms
> Execution Time: 0.043 ms
>

This might be due to caching. Run the query with LIMIT three times, and
then remove the LIMIT and run three times.

Honestly, though, the execution timings seem pretty good. What exactly is
the problem?

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