Goal This query identifies base tables with a FILLFACTOR setting below 90, flagging them for potentially inefficient storage utilization. While a low FILLFACTOR is intended to accommodate UPDATEs, an excessively low value can lead to wasted disk space and reduced data density, negatively impacting the performance of operations like full table scans.
Notes The query assumes that the FILLFACTOR reloption is specified only in case of the base tables where it is not default, i.e., 100. Although currently FILLFACTOR is the only reloption this may change in the future. Thus, instead of using the condition reloptions IS NOT NULL, the query filters out reloptions that specify a new FILLFACTOR value.
Type Problem detection (Each row in the result could represent a flaw in the design)
Reliability Medium (Medium number of false-positive results)
License MIT (opens in new tab)
Fixing Suggestion Change FILLFACTOR to 90 or 95. It does not have to be smaller because old versions of rows will be soon deleted from blocks by the vacuum process, i.e., it frees space. After changing the FILLFACTOR of an existing table, one has to VACUUM FULL the table to reorganize its internal storage.
Data Source INFORMATION_SCHEMA+system catalog
SQL Query 
WITH base_tables AS (SELECT 
  pg_class.relname AS table_name, 
  pg_namespace.nspname AS table_schema,
  unnest(reloptions) AS reloptions
FROM 
  pg_catalog.pg_class, 
  pg_catalog.pg_namespace
WHERE 
  pg_class.relnamespace = pg_namespace.oid AND relkind='r'),
base_tables_fillfactor AS (SELECT table_schema, table_name, regexp_replace(reloptions,'[^0-9]','','g')::int AS fillfactor
FROM base_tables
WHERE table_schema NOT IN (SELECT schema_name
FROM INFORMATION_SCHEMA.schemata
WHERE schema_name<>'public' AND
schema_owner='postgres' AND schema_name IS NOT NULL)
AND reloptions ILIKE 'fillfactor%')
SELECT table_schema, table_name, fillfactor
FROM base_tables_fillfactor
WHERE fillfactor<90
ORDER BY table_schema, table_name;

SQL statements that help generate fixes for the identified problem.

Fix Action #1
WITH base_tables AS (SELECT 
  pg_class.relname AS table_name, 
  pg_namespace.nspname AS table_schema,
  unnest(reloptions) AS reloptions
FROM 
  pg_catalog.pg_class, 
  pg_catalog.pg_namespace
WHERE 
  pg_class.relnamespace = pg_namespace.oid AND relkind='r'),
base_tables_fillfactor AS (SELECT table_schema, table_name, regexp_replace(reloptions,'[^0-9]','','g')::int AS fillfactor
FROM base_tables
WHERE table_schema NOT IN (SELECT schema_name
FROM INFORMATION_SCHEMA.schemata
WHERE schema_name<>'public' AND
schema_owner='postgres' AND schema_name IS NOT NULL)
AND reloptions ILIKE 'fillfactor%')
SELECT format('ALTER TABLE %1$I.%2$I SET (FILLFACTOR=90); VACUUM FULL %1$I.%2$I', table_schema, table_name) AS statements
FROM base_tables_fillfactor
WHERE fillfactor<90
ORDER BY table_schema, table_name;

Change the fillfactor to 90.

SQL Query to Generate FixDescription
WITH base_tables AS (SELECT 
  pg_class.relname AS table_name, 
  pg_namespace.nspname AS table_schema,
  unnest(reloptions) AS reloptions
FROM 
  pg_catalog.pg_class, 
  pg_catalog.pg_namespace
WHERE 
  pg_class.relnamespace = pg_namespace.oid AND relkind='r'),
base_tables_fillfactor AS (SELECT table_schema, table_name, regexp_replace(reloptions,'[^0-9]','','g')::int AS fillfactor
FROM base_tables
WHERE table_schema NOT IN (SELECT schema_name
FROM INFORMATION_SCHEMA.schemata
WHERE schema_name<>'public' AND
schema_owner='postgres' AND schema_name IS NOT NULL)
AND reloptions ILIKE 'fillfactor%')
SELECT format('ALTER TABLE %1$I.%2$I SET (FILLFACTOR=90); VACUUM FULL %1$I.%2$I', table_schema, table_name) AS statements
FROM base_tables_fillfactor
WHERE fillfactor<90
ORDER BY table_schema, table_name;
Change the fillfactor to 90.

Collections

This query belongs to the following collections:

Find problems automatically

Queries, that results point to problems in the database. Each query in the collection produces an initial assessment. However, a human reviewer has the final say as to whether there is a problem or not .

NameDescription
Find problems automaticallyQueries, that results point to problems in the database. Each query in the collection produces an initial assessment. However, a human reviewer has the final say as to whether there is a problem or not .

Categories

This query is classified under the following categories:

Data at the database physical level

Queries of this category provide information about the disk usage.

Performance

Queries of this category provide information about indexes in a database.

NameDescription
Data at the database physical levelQueries of this category provide information about the disk usage.
PerformanceQueries of this category provide information about indexes in a database.