Finding Row Counts for All Tables in PostgreSQL

Concepts:

• PostgreSQL: An open-source relational database management system (RDBMS) used for storing and managing data.
• Count: A function or operation that calculates the number of items (rows) in a database table.
• Database Table: A structured collection of data in a database, consisting of rows (records) and columns (attributes).

Methods:

There are two primary methods to achieve this in PostgreSQL:

Method 1: Using pg_stat_user_tables System View

2. Query: The following SQL query retrieves the table name (relname) and the estimated row count (n_live_tup):

   SELECT relname, n_live_tup
   FROM pg_stat_user_tables;
   

   • This query is efficient because it leverages pre-gathered information by the PostgreSQL optimizer.

Method 2: Using information_schema.tables and count(*)

3. Query: Here's the corresponding SQL query:

   SELECT table_name, (SELECT count(*) FROM information_schema.tables WHERE table_name = t.table_name) AS row_count
   FROM information_schema.tables t;
   

   • This method iterates through each table, executing a separate count(*) query, which can be slower than Method 1 for a large number of tables.

Choosing the Right Method:

• Performance: Generally, Method 1 using pg_stat_user_tables is preferred due to its efficiency in retrieving row count estimates.
• Accuracy: If you require exact row counts, consider Method 2 using information_schema.tables and count(*). However, this might be less performant.

Additional Considerations:

• Filtering Tables: You can modify the queries to filter specific tables based on schema or table name patterns.
• Regular Updates: The row counts in pg_stat_user_tables are estimates and may not reflect real-time changes. Consider refreshing statistics periodically (e.g., using VACUUM FULL or ANALYZE) for more accurate counts.

Example Codes for Finding Row Counts in PostgreSQL

Method 1: Using pg_stat_user_tables (Recommended for Efficiency)

SELECT relname, n_live_tup
FROM pg_stat_user_tables;

This code retrieves the table name (relname) and the estimated row count (n_live_tup) from the pg_stat_user_tables system view.

SELECT table_name, (SELECT count(*) FROM information_schema.tables WHERE table_name = t.table_name) AS row_count
FROM information_schema.tables t;

Using pg_class system view:

• This method offers an estimate similar to pg_stat_user_tables but with more details.
• Query:

SELECT relname, reltuples AS estimate
FROM pg_class
WHERE relkind='r'  -- Filter for tables only
ORDER BY reltuples DESC;  -- Sort by estimated row count (descending)

• Explanation:
  • pg_class stores general information about all database objects.
  • reltuples provides an estimate of the total number of rows in the table.
  • relkind='r' filters for relations (tables) only.
  • Ordering by reltuples DESC helps prioritize tables with potentially higher row counts.

Using EXPLAIN with parsing (Advanced):

• This method offers an estimate without actually executing a full COUNT(*) query.
• It's suitable for situations where even the overhead of pg_stat_user_tables might be noticeable (very large databases).

CREATE OR REPLACE FUNCTION count_estimate(query text) RETURNS integer AS $$
DECLARE
  rec record;
  rows integer;
BEGIN
  EXECUTE EXPLAIN (analyze, verbose) INTO rec $query;
  -- Parse the EXPLAIN output to find the estimated row count
  -- (implementation details omitted for brevity)
  rows := extract_rows(rec.query_plan);
  RETURN rows;
END;
$$ LANGUAGE plpgsql;

SELECT table_name, count_estimate('SELECT * FROM ' || table_name) AS estimated_rows
FROM information_schema.tables
WHERE table_schema = 'public'  -- Specify your schema name
ORDER BY estimated_rows DESC;

• Explanation:
  • This method defines a custom function count_estimate that takes a SQL query as input.
  • It uses EXPLAIN with analyze and verbose options to analyze the query plan without actually executing it.
  • The function parses the EXPLAIN output (implementation details omitted for brevity) to extract an estimated row count.
  • The main query then iterates through tables in the specified schema (public in this example) and calls count_estimate for each table.

• For a balance of efficiency and accuracy, consider pg_class if pg_stat_user_tables isn't sufficient.
• Use EXPLAIN with parsing only for very large databases where even pg_class might impact performance significantly. Be aware that parsing the output requires advanced knowledge.