Postgresql index is not used for slow queries >30s - postgresql

Question

POSTGRESQL VERSION: 10
HARDWARE: 4 workers / 16GBRAM / 50% used
I'm not a Postgresql expert. I have just read a lot of documentation and did a lot of tests.
I have some postgresql queries whick take a lot of times > 30s because of 10 millions of rows on a table.
Column | Type | Collation | Nullable | Default
------------------------------+--------------------------+-----------+----------+----------------------------------------------------------
id | integer | | not null |
cveid | character varying(50) | | |
summary | text | | not null |
published | timestamp with time zone | | |
modified | timestamp with time zone | | |
assigner | character varying(128) | | |
vulnerable_products | character varying(250)[] | | |
cvss | double precision | | |
cvss_time | timestamp with time zone | | |
cvss_vector | character varying(250) | | |
access | jsonb | | not null |
impact | jsonb | | not null |
score | integer | | not null |
is_exploitable | boolean | | not null |
is_confirmed | boolean | | not null |
is_in_the_news | boolean | | not null |
is_in_the_wild | boolean | | not null |
reflinks | jsonb | | not null |
reflinkids | jsonb | | not null |
created_at | timestamp with time zone | | |
history_id | integer | | not null | nextval('vulns_historicalvuln_history_id_seq'::regclass)
history_date | timestamp with time zone | | not null |
history_change_reason | character varying(100) | | |
history_type | character varying(1) | | not null |
Indexes:
"vulns_historicalvuln_pkey" PRIMARY KEY, btree (history_id)
"btree_varchar" btree (history_type varchar_pattern_ops)
"vulns_historicalvuln_cve_id_850876bb" btree (cve_id)
"vulns_historicalvuln_cwe_id_2013d697" btree (cwe_id)
"vulns_historicalvuln_history_user_id_9e25ebf5" btree (history_user_id)
"vulns_historicalvuln_id_773f2af7" btree (id)
--- TRUNCATE
Foreign-key constraints:
"vulns_historicalvuln_history_user_id_9e25ebf5_fk_custusers" FOREIGN KEY (history_user_id) REFERENCES custusers_user(id) DEFERRABLE INITIALLY DEFERRED
Example of queries:
SELECT * FROM vulns_historicalvuln WHERE history_type <> '+' order by id desc fetch first 10000 rows only; -> 30s without cache
QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit (cost=0.43..31878.33 rows=10000 width=1736) (actual time=0.173..32839.474 rows=10000 loops=1)
-> Index Scan Backward using vulns_historicalvuln_id_773f2af7 on vulns_historicalvuln (cost=0.43..26346955.92 rows=8264960 width=1736) (actual time=0.172..32830.958 rows=10000 loops=1)
Filter: ((history_type)::text <> '+'::text)
Rows Removed by Filter: 296
Planning time: 19.514 ms
Execution time: 32845.015 ms
SELECT DISTINCT "vulns"."id", "vulns"."uuid", "vulns"."feedid", "vulns"."cve_id", "vulns"."cveid", "vulns"."summary", "vulns"."published", "vulns"."modified", "vulns"."assigner", "vulns"."cwe_id", "vulns"."vulnerable_packages_versions", "vulns"."vulnerable_products", "vulns"."vulnerable_product_versions", "vulns"."cvss", "vulns"."cvss_time", "vulns"."cvss_version", "vulns"."cvss_vector", "vulns"."cvss_metrics", "vulns"."access", "vulns"."impact", "vulns"."cvss3", "vulns"."cvss3_vector", "vulns"."cvss3_version", "vulns"."cvss3_metrics", "vulns"."score", "vulns"."is_exploitable", "vulns"."is_confirmed", "vulns"."is_in_the_news", "vulns"."is_in_the_wild", "vulns"."reflinks", "vulns"."reflinkids", "vulns"."created_at", "vulns"."updated_at", "vulns"."id" AS "exploit_count", false AS "monitored", '42' AS "org" FROM "vulns" WHERE ("vulns"."score" >= 0 AND "vulns"."score" <= 100) ORDER BY "vulns"."updated_at" DESC LIMIT 10
QUERY PLAN
----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------
Limit (cost=315191.32..315192.17 rows=10 width=1691) (actual time=3013.964..3013.990 rows=10 loops=1)
-> Unique (cost=315191.32..329642.42 rows=170013 width=1691) (actual time=3013.962..3013.986 rows=10 loops=1)
-> Sort (cost=315191.32..315616.35 rows=170013 width=1691) (actual time=3013.961..3013.970 rows=10 loops=1)
Sort Key: updated_at DESC, id, uuid, feedid, cve_id, cveid, summary, published, modified, assigner, cwe_id, vulnerable_packages_versions, vulnerable_products, vulnerable_product_versions, cvss, cvss_time, cvss_version, cvss_vector, cvss_metrics, access, impact, cvss3, cvss3_vector, cvss3_version, cvss3_metrics, score, is_exploitable, is_confirmed, is_in_the_news, is_in_the_wild, reflinks, reflinkids, created_at
Sort Method: external merge Disk: 277648kB
-> Seq Scan on vulns (cost=0.00..50542.19 rows=170013 width=1691) (actual time=0.044..836.597 rows=169846 loops=1)
Filter: ((score >= 0) AND (score <= 100))
Planning time: 3.183 ms
Execution time: 3070.346 ms
I have created a btree varchar index btree_varchar" btree (history_type varchar_pattern_ops) like this:
CREATE INDEX CONCURRENTLY btree_varchar ON vulns_historicalvuln (history_type varchar_pattern_ops);
I have also created a index for vulns score for my second queries:
CREATE INDEX CONCURRENTLY ON vulns (score);
I read a lot of post and documentation about slow queries and index. I'am sure it's the solution about slow queries but the query plan of Postgresql doesn't use the index I have created. It estimates that it processes faster with seq scan than using the index...
SELECT relname, indexrelname, idx_scan FROM pg_catalog.pg_stat_user_indexes;
relname | indexrelname | idx_scan
-------------------------------------+-----------------------------------------------------------------+------------
vulns_historicalvuln | btree_varchar | 0
Could you tell me if my index is well designed ? How I can debug this, feel free to ask more information if needed.
Thanks

Answer 1

After some research, I understand that index is not the solution of my problem here.
Low_cardinality (repeated value) of this field make the index useless.
The time of the query postgresql here is normal because of 30M rows matched.
I close this issue because there is no problem with index here.