Finding the Row Count in PostgreSQL: Accuracy vs. Speed

1. SELECT count(*) FROM table_name:

   • This is the standard SQL way to get an exact count of all rows in a table.
   • It's generally reliable, but for very large tables, it might take a while as PostgreSQL examines every row to ensure visibility due to its Multi-Version Concurrency Control (MVCC) mechanism.

2. SELECT reltuples::bigint AS estimate FROM pg_class WHERE oid = 'schema_name.table_name'::regclass:

   • This method leverages the pg_class system catalog table, which stores metadata about tables.
   • The reltuples column provides an estimated row count based on PostgreSQL's internal statistics.
   • It's significantly faster than SELECT count(*) for large tables because it retrieves the estimate directly from the catalog.
   • However, this estimate might not be perfectly accurate, especially if the table has recently undergone significant data modifications (inserts, deletes, updates).

Choosing the Right Method:

• If you need an absolutely precise count, SELECT count(*) is the way to go.
• If you prioritize speed and an approximate idea of the row count is sufficient (e.g., for monitoring or quick checks), SELECT reltuples::bigint AS estimate is the better option.

Additional Considerations:

• Automatic Statistics Collection: PostgreSQL gathers statistics on tables periodically to keep the reltuples estimate reasonably up-to-date. However, manual updates using ANALYZE might be necessary if the table has undergone substantial changes.
• VACUUM: If your table has a lot of deleted rows, running VACUUM can reclaim the space and potentially improve the accuracy of the reltuples estimate.

SELECT count(*) AS exact_count
FROM your_schema.your_table_name;

This code will return the exact number of rows in the table your_table_name located in the schema your_schema.

Method 2: Using SELECT reltuples::bigint AS estimate

SELECT reltuples::bigint AS estimate
FROM pg_class
WHERE oid = 'your_schema.your_table_name'::regclass;

• If your PostgreSQL server has the pg_stat_all_tables extension enabled (which collects statistics automatically), you can use this method:

SELECT n_live_tup AS estimate
FROM pg_stat_all_tables
WHERE relname = 'your_schema.your_table_name';

This retrieves an estimate similar to reltuples but might be updated more frequently based on the extension's configuration.

Sampling for Very Large Tables (with caution):

• For extremely large tables where even SELECT count(*) might be slow, consider sampling with a tool like pg_sample_stats. This approach involves taking a statistically significant sample of rows and extrapolating the count based on the sample size. However, exercise caution as sampling introduces a margin of error.

Monitoring Tools:

• Some database monitoring tools might provide row count information for your PostgreSQL tables. These tools often collect statistics and offer visualizations to track changes over time.

The best approach depends on your specific requirements:

• Exact count: Use SELECT count(*) if precision is paramount.
• Fast estimate: Use SELECT reltuples or pg_stat_all_tables (if enabled) for a quick approximation.
• Very large tables (cautious): Consider sampling with pg_sample_stats if speed is critical and an exact count isn't essential.
• Monitoring: Utilize database monitoring tools if you need historical row count data and visualizations.