Postgresql – > 30 sec slow query

optimizationperformancepostgresqlpostgresql-9.1query-performance

I've got a very slow query, running over 30 seconds:

SELECT DISTINCT id10
FROM
  (SELECT j.id AS id10,
          j.modified,
          j.n_type AS n_type5
   FROM note j
   WHERE j.modified_date >= '2016-10-01 23:12:34.000000'
     AND j.clientid = 16049
     AND j.n_type  IN ('n',
                           'n_1',
                           'n_custom',
                           'n_standard',
                           'n_status')
   ORDER BY j.id ASC) t2
ORDER BY id10 ASC LIMIT 20;

Explain Analyze: https://explain.depesz.com/s/DU4

Is there a way I can improve this query?

Created a new index on modified_date and n_type columns:

CREATE INDEX ix_n_type_modified 
ON notes (n_type, timezone('Etc/UTC'::text, modified_date)) 
WHERE n_type IN ('n_1','n_custom','n_standard','n_status');

New Explain analyze: https://explain.depesz.com/s/RsTr

Query still taking >5 seconds.

New explain analyze using the new query provided by Evan Carroll: https://explain.depesz.com/s/yP4S

Query:

SELECT id AS id10
FROM
   FROM note j
   WHERE j.modified_date >= '2015-12-07 23:12:34.000000'
     AND j.clientid = 16049
     AND j.n_type  IN ('n',
                           'n_1',
                           'n_custom',
                           'n_standard',
                           'n_status')
ORDER BY id10 ASC
LIMIT 20;

Query is taking even longer now.

note is a view. It has a join on the jobs table (note.jobid -> jobs.id)

I can't do any other join between those tables, as there is no "linked" columns between them.

\d+ note;:

Table "public.note"
Column          |           Type           |                          Modifiers                          | Storage  | Stats target |                                                                       Description                                                  
----------------+--------------------------+-------------------------------------------------------------+----------+--------------+----------------------------------------------------------------------------------------------------------------------------------------------------------
id              | bigint                   | not null default "nextval"('"note_id_seq"'::"regclass")     | plain    |              | Primary key
jobid           | bigint                   | not null default 0                                          | plain    |
description     | "text"                   | default ''::"text"                                          | extended |
modified_date   | timestamp with time zone | default "statement_timestamp"()                             | plain    |              | Modified date
n_type          | "n_type"                 |                                                             | plain    |

Indexes:
"note_pkey" PRIMARY KEY, "btree" ("id")
"ix_note_gsdi_pk" "btree" (("id"::"text"))
"ix_job_fk" "btree" ("jobid")
"ix_job_n_type" "btree" ("n_type")
"ix_note_jobid_type" "btree" ("jobid", "n_type")
"ix_note_jobid_type_2" "btree" ("jobid", "n_type", "timezone"('Etc/UTC'::"text", "modified_date"))

View note on schema note_user – This view is in a different schema than the table note:

SELECT r_30.id, r_30.jobid, 
   r_30.description,  
   timezone('Etc/UTC'::text, r_30.modified_date),  
   cj.clientid
  FROM public.note r_30
  JOIN public.jobs cj ON cj.id = r_30.jobid
  ;

Table note:

CREATE TABLE public.note
(
  id bigint NOT NULL DEFAULT nextval('note_id_seq'::regclass), -- Primary key
  jobid bigint NOT NULL DEFAULT 0,
  description text DEFAULT ''::text,
n_type n_type,
  modified_date timestamp with time zone DEFAULT statement_timestamp(),
  CONSTRAINT note_pkey PRIMARY KEY (id)
  );

Table jobs:

CREATE TABLE public.jobs
(
  id bigint NOT NULL DEFAULT nextval('jobs_id_seq'::regclass),
  clientid bigint NOT NULL DEFAULT 0,
  description text NOT NULL DEFAULT ''::text,
  modified_date timestamp without time zone DEFAULT statement_timestamp(),
  CONSTRAINT jobs_pkey PRIMARY KEY (id)
);

Custom n_type data type:

live_database=> \dT+ n_type
                                                     List of data types
 Schema |      Name       |  Internal name  | Size |      Elements       | Access privileges |         Description          
--------+-----------------+-----------------+------+---------------------+-------------------+------------------------------
 public | n_type          | n_type          | 4    | n_1                +|                   |
        |                 |                 |      | n_custom           +|                   | 
        |                 |                 |      | n_standard         +|                   | 
        |                 |                 |      | n_status           +|                   | 
(1 row)

Best Answer

Instead of what you've got, remove the virtual table and try to query directly.

SELECT DISTINCT id AS id10
FROM note j
WHERE j.modified_date >= '2016-10-01 23:12:34.000000'
  AND j.clientid = 16049
  AND j.n_type  IN ('n',
    'n_1',
    'n_custom',
    'n_standard',
    'n_status')
ORDER BY id10 ASC
LIMIT 20;

Related Solutions

Postgresql – Postgres multiple joins slow query, how to store default child record

You write:

Each customer can have multiple sites, but only one should be displayed in this list.

Yet, your query retrieves all rows. That would be a point to optimize. But you also do not define which site is to be picked.

Either way, it does not matter much here. Your EXPLAIN shows only 5026 rows for the site scan (5018 for the customer scan). So hardly any customer actually has more than one site. Did you ANALYZE your tables before running EXPLAIN?

From the numbers I see in your EXPLAIN, indexes will give you nothing for this query. Sequential table scans will be the fastest possible way. Half a second is rather slow for 5000 rows, though. Maybe your database needs some general performance tuning?

Maybe the query itself is faster, but "half a second" includes network transfer? EXPLAIN ANALYZE would tell us more.

If this query is your bottleneck, I would suggest you implement a materialized view.

After you provided more information I find that my diagnosis pretty much holds.

The query itself needs 27 ms. Not much of a problem there. "Half a second" was the kind of misunderstanding I had suspected. The slow part is the network transfer (plus ssh encoding / decoding, possibly rendering). You should only retrieve 100 rows, that would solve most of it, even if it means to execute the whole query every time.

If you go the route with a materialized view like I proposed you could add a serial number without gaps to the table plus index on it - by adding a column row_number() OVER (<your sort citeria here>) AS mv_id.

Then you can query:

SELECT *
FROM   materialized_view
WHERE  mv_id >= 2700
AND    mv_id <  2800;

This will perform very fast. LIMIT / OFFSET cannot compete, that needs to compute the whole table before it can sort and pick 100 rows.

pgAdmin timing

When you execute a query from the query tool, the message pane shows something like:

Total query runtime: 62 ms.

And the status line shows the same time. I quote pgAdmin help about that:

The status line will show how long the last query took to complete. If a dataset was returned, not only the elapsed time for server execution is displayed, but also the time to retrieve the data from the server to the Data Output page.

If you want to see the time on the server you need to use SQL EXPLAIN ANALYZE or the built in Shift + F7keyboard shortcut or Query -> Explain analyze. Then, at the bottom of the explain output you get something like this:

Total runtime: 0.269 ms

Postgresql – Simple PostgreSQL lookup table is inexplicably slow

Rather than "VARCHAR(40000)" why not use "TEXT"?
HASH index use is discouraged (see docs at http://www.postgresql.org/docs/current/static/indexes-types.html).
Have you run "ANALYZE" on your tables before running the query?
Giant IN lists can be performance killers.

How do the following queries perform?

SELECT e.entityId
FROM entities e
INNER JOIN triples t ON (t.object = e.entityId)
LIMIT 10000;

SELECT e.entityId
FROM entities e
WHERE EXISTS (SELECT 1 FROM triples t WHERE t.object = e.entityId LIMIT 10000);

Best Answer

Related Solutions

Postgresql – Postgres multiple joins slow query, how to store default child record

pgAdmin timing

Postgresql – Simple PostgreSQL lookup table is inexplicably slow

Related Question