Re: Slow query with big tables

From: pgsql-performance-owner(at)postgresql(dot)org [mailto:pgsql-performance-owner(at)postgresql(dot)org] On Behalf Of Tommi K
Sent: Friday, August 26, 2016 7:25 AM
To: Craig James <cjames(at)emolecules(dot)com>
Cc: andreas kretschmer <akretschmer(at)spamfence(dot)net>; pgsql-performance(at)postgresql(dot)org
Subject: Re: [PERFORM] Slow query with big tables

Ok, sorry that I did not add the original message. I thought that it would be automatically added to the message thread.

Here is the question again:

Is there way to keep query time constant as the database size grows. Should I use partitioning or partial indexes?

Thanks,

Tommi Kaksonen

> Hello,

>

> I have the following tables and query. I would like to get some help to find out why it is slow and how its performance could be improved.

>

> Thanks,

> Tommi K.

>

>

> --Table definitions---

> CREATE TABLE "Measurement"

> (

> id bigserial NOT NULL,

> product_id bigserial NOT NULL,

> nominal_data_id bigserial NOT NULL,

> description text,

> serial text,

> measurement_time timestamp without time zone,

> status smallint,

> system_description text,

> CONSTRAINT "Measurement_pkey" PRIMARY KEY (id),

> CONSTRAINT "Measurement_nominal_data_id_fkey" FOREIGN KEY (nominal_data_id)

> REFERENCES "Nominal_data" (id) MATCH SIMPLE

> ON UPDATE NO ACTION ON DELETE NO ACTION,

> CONSTRAINT "Measurement_product_id_fkey" FOREIGN KEY (product_id)

> REFERENCES "Product" (id) MATCH SIMPLE

> ON UPDATE NO ACTION ON DELETE NO ACTION

> )

> WITH (

> OIDS=FALSE

> );

>

> CREATE INDEX measurement_time_index

> ON "Measurement"

> USING btree

> (measurement_time);

> ALTER TABLE "Measurement" CLUSTER ON measurement_time_index;

>

> CREATE TABLE "Product"

> (

> id bigserial NOT NULL,

> name text,

> description text,

> info text,

> system_name text,

> CONSTRAINT "Product_pkey" PRIMARY KEY (id)

> )

> WITH (

> OIDS=FALSE

> );

>

>

> CREATE TABLE "Extra_info"

> (

> id bigserial NOT NULL,

> measurement_id bigserial NOT NULL,

> name text,

> description text,

> info text,

> type text,

> value_string text,

> value_double double precision,

> value_integer bigint,

> value_bool boolean,

> CONSTRAINT "Extra_info_pkey" PRIMARY KEY (id),

> CONSTRAINT "Extra_info_measurement_id_fkey" FOREIGN KEY (measurement_id)

> REFERENCES "Measurement" (id) MATCH SIMPLE

> ON UPDATE NO ACTION ON DELETE NO ACTION

> )

> WITH (

> OIDS=FALSE

> );

>

> CREATE INDEX extra_info_measurement_id_index

> ON "Extra_info"

> USING btree

> (measurement_id);

>

> CREATE TABLE "Feature"

> (

> id bigserial NOT NULL,

> measurement_id bigserial NOT NULL,

> name text,

> description text,

> info text,

> CONSTRAINT "Feature_pkey" PRIMARY KEY (id),

> CONSTRAINT "Feature_measurement_id_fkey" FOREIGN KEY (measurement_id)

> REFERENCES "Measurement" (id) MATCH SIMPLE

> ON UPDATE NO ACTION ON DELETE NO ACTION

> )

> WITH (

> OIDS=FALSE

> );

>

> CREATE INDEX feature_measurement_id_and_name_index

> ON "Feature"

> USING btree

> (measurement_id, name COLLATE pg_catalog."default");

>

> CREATE INDEX feature_measurement_id_index

> ON "Feature"

> USING hash

> (measurement_id);

>

>

> CREATE TABLE "Point"

> (

> id bigserial NOT NULL,

> feature_id bigserial NOT NULL,

> x double precision,

> y double precision,

> z double precision,

> status_x smallint,

> status_y smallint,

> status_z smallint,

> difference_x double precision,

> difference_y double precision,

> difference_z double precision,

> CONSTRAINT "Point_pkey" PRIMARY KEY (id),

> CONSTRAINT "Point_feature_id_fkey" FOREIGN KEY (feature_id)

> REFERENCES "Feature" (id) MATCH SIMPLE

> ON UPDATE NO ACTION ON DELETE NO ACTION

> )

> WITH (

> OIDS=FALSE

> );

>

> CREATE INDEX point_feature_id_index

> ON "Point"

> USING btree

> (feature_id);

>

> CREATE TABLE "Warning"

> (

> id bigserial NOT NULL,

> feature_id bigserial NOT NULL,

> "number" smallint,

> info text,

> CONSTRAINT "Warning_pkey" PRIMARY KEY (id),

> CONSTRAINT "Warning_feature_id_fkey" FOREIGN KEY (feature_id)

> REFERENCES "Feature" (id) MATCH SIMPLE

> ON UPDATE NO ACTION ON DELETE NO ACTION

> )

> WITH (

> OIDS=FALSE

> );

>

> CREATE INDEX warning_feature_id_index

> ON "Warning"

> USING btree

> (feature_id);

>

>

> ---Query---

> SELECT

> f.name <http://f.name> ,

> f.description,

> SUM(CASE WHEN p.status_x = 0 AND p.status_y = 0 AND p.status_z = 0 AND warning.id <http://warning.id> IS NULL THEN 1 ELSE 0 END) AS green_count,

> SUM(CASE WHEN p.status_x = 0 AND p.status_y = 0 AND p.status_z = 0 AND warning.id <http://warning.id> IS NOT NULL THEN 1 ELSE 0 END) AS green_warned_count,

> SUM(CASE WHEN NOT (p.status_x = 0 AND p.status_y = 0 AND p.status_z = 0) AND NOT (p.status_x = 2 OR p.status_y = 2 OR p.status_z = 2) AND warning.id <http://warning.id> IS NULL THEN 1 ELSE 0 END) AS yellow_count,

> SUM(CASE WHEN NOT (p.status_x = 0 AND p.status_y = 0 AND p.status_z = 0) AND NOT (p.status_x = 2 OR p.status_y = 2 OR p.status_z = 2) AND warning.id <http://warning.id> IS NOT NULL THEN 1 ELSE 0 END) AS yellow_warned_count,

> SUM(CASE WHEN (p.status_x = 2 OR p.status_y = 2 OR p.status_z = 2) AND warning.id <http://warning.id> IS NULL THEN 1 ELSE 0 END) AS red_count,

> SUM(CASE WHEN (p.status_x = 2 OR p.status_y = 2 OR p.status_z = 2) AND warning.id <http://warning.id> IS NOT NULL THEN 1 ELSE 0 END) AS red_warned_count,

> SUM(CASE WHEN (p.status_x = 1000 OR p.status_y = 1000 OR p.status_z = 1000) AND warning.id <http://warning.id> IS NOT NULL THEN 1 ELSE 0 END) AS unable_to_measure_count

> FROM "Point" p

> JOIN "Feature" f ON f.id <http://f.id> = p.feature_id

> JOIN "Measurement" measurement ON measurement.id <http://measurement.id> = f.measurement_id

> JOIN "Product" product ON product.id <http://product.id> = measurement.product_id

> LEFT JOIN "Warning" warning ON f.id <http://f.id> = warning.feature_id

> WHERE (product.name <http://product.name> ILIKE 'Part 1') AND

> measurement.measurement_start_time >= '2015-06-18 17:00:00' AND

> measurement.measurement_start_time <= '2015-06-18 18:00:00' AND

> measurement.id <http://measurement.id> NOT IN(SELECT measurement_id FROM "Extra_info" e

> WHERE e.measurement_id = measurement.id <http://measurement.id> AND e.description = 'Clamp' AND e.value_string ILIKE 'Clamped%')

> GROUP BY f.name <http://f.name> , f.description;

>

>

> ---Explain Analyze---

> GroupAggregate (cost=1336999.08..1337569.18 rows=5562 width=33) (actual time=6223.622..6272.321 rows=255 loops=1)

> Buffers: shared hit=263552 read=996, temp read=119 written=119

> -> Sort (cost=1336999.08..1337012.98 rows=5562 width=33) (actual time=6223.262..6231.106 rows=26265 loops=1)

> Sort Key: f.name <http://f.name> , f.description

> Sort Method: external merge Disk: 936kB

> Buffers: shared hit=263552 read=996, temp read=119 written=119

> -> Nested Loop Left Join (cost=0.00..1336653.08 rows=5562 width=33) (actual time=55.792..6128.875 rows=26265 loops=1)

> Buffers: shared hit=263552 read=996

> -> Nested Loop (cost=0.00..1220487.17 rows=5562 width=33) (actual time=55.773..5910.852 rows=26265 loops=1)

> Buffers: shared hit=182401 read=954

> -> Nested Loop (cost=0.00..22593.53 rows=8272 width=27) (actual time=30.980..3252.869 rows=38831 loops=1)

> Buffers: shared hit=972 read=528

> -> Nested Loop (cost=0.00..657.24 rows=22 width=8) (actual time=0.102..109.577 rows=103 loops=1)

> Join Filter: (measurement.product_id = product.id <http://product.id> )

> Rows Removed by Join Filter: 18

> Buffers: shared hit=484 read=9

> -> Seq Scan on "Product" product (cost=0.00..1.04 rows=1 width=8) (actual time=0.010..0.019 rows=1 loops=1)

> Filter: (name ~~* 'Part 1'::text)

> Rows Removed by Filter: 2

> Buffers: shared hit=1

> -> Index Scan using measurement_start_time_index on "Measurement" measurement (cost=0.00..655.37 rows=67 width=16) (actual time=0.042..109.416 rows=121 loops=1)

> Index Cond: ((measurement_start_time >= '2015-06-18 17:00:00'::timestamp without time zone) AND (measurement_start_time <= '2015-06-18 18:00:00'::timestamp without time zone))

> Filter: (NOT (SubPlan 1))

> Buffers: shared hit=483 read=9

> SubPlan 1

> -> Index Scan using extra_info_measurement_id_index on "Extra_info" e (cost=0.00..9.66 rows=1 width=8) (actual time=0.900..0.900 rows=0 loops=121)

> Index Cond: (measurement_id = measurement.id <http://measurement.id> )

> Filter: ((value_string ~~* 'Clamped%'::text) AND (description = 'Clamp'::text))

> Rows Removed by Filter: 2

> Buffers: shared hit=479 read=7

> -> Index Scan using feature_measurement_id_and_name_index on "Feature" rf (cost=0.00..993.40 rows=370 width=35) (actual time=28.152..30.407 rows=377 loops=103)

> Index Cond: (measurement_id = measurement.id <http://measurement.id> )

> Buffers: shared hit=488 read=519

> -> Index Scan using point_feature_id_index on "Point" p (cost=0.00..144.80 rows=1 width=14) (actual time=0.067..0.067 rows=1 loops=38831)

> Index Cond: (feature_id = f.id <http://f.id> )

> Buffers: shared hit=181429 read=426

> -> Index Scan using warning_feature_id_index on "Warning" warning (cost=0.00..20.88 rows=1 width=16) (actual time=0.007..0.007 rows=0 loops=26265)

> Index Cond: (f.id <http://f.id> = feature_id)

> Buffers: shared hit=81151 read=42

> Total runtime: 6273.312 ms

>

>

> ---Version---

> PostgreSQL 9.2.1, compiled by Visual C++ build 1600, 64-bit

>

>

> ---Table sizes---

> Extra_info 1223400 rows

> Feature 185436000 rows

> Measurement 500000 rows

> Point 124681000 rows

> Warning 11766800 rows

>

> ---Hardware---

> Intel Core i5-2320 CPU 3.00GHz (4 CPUs)

> 6GB Memory

> 64-bit Operating System (Windows 7 Professional)

> WD Blue 500GB HDD - 7200 RPM SATA 6 Gb/s 16MB Cache

>

> ---History---

> Query gets slower as more data is added to the database

>

> ---Maintenance---

> Autovacuum is used with default settings

>

> Tommi Kaksonen <t2nn2t(at)gmail(dot)com> wrote:

I don’t see a reason to partition such small data. What I do see is you attempting to run a big query on what looks like a small desktop pc. 6GB of ram, especially under Windows 7, isn’t enough ram for a database server. Run the query on a normal small server of say 16gb and it should perform fine. IMO.

Mike