How to fine tune an SQL Query

This article provides guidance to help you resolve issues encountered during SQL queries and offers insights on fine-tuning SQL queries effectively.

1. Aliasing Issue in Query

At times, when executing SQL queries containing aliases in an SQL Integrated Development Environment (IDE), users may encounter challenges. This often occurs as depicted in the example below:

In such instances, the recommended approach is to run the query without aliasing, as illustrated below. Removing the aliases can enhance the query's compatibility and ensure smooth execution.

SELECT
    pp.username ,
    pp.pagename ,
    pp.id,
    COUNT(pc.portalpage) AS dataplane_gadgets
FROM
    portletconfiguration pc
LEFT JOIN
    portalpage pp ON pc.portalpage = pp.id
WHERE
    pc.gadget_xml LIKE '%dataplane%'
GROUP BY
    pp.username, pp.pagename, pp.id
ORDER BY
    pp.username, dataplane_gadgets DESC;

2. Query not executing in a database or taking longer time to execute

When faced with issues related to SQL queries not executing or taking significantly longer to execute than usual, employing the 'Explain Analyze' keyword before the query can provide invaluable insights. This method offers detailed runtime statistics, including the total elapsed time spent within each plan node (in milliseconds) and the total number of rows returned.

Additionally, optimizing query execution often involves creating appropriate indexes, especially for tables or columns housing millions of records. Proper indexing significantly improves the efficiency of query processing, ultimately enhancing overall database performance

2.1. Indexing

You have the option to create the index manually or utilize the 'REINDEX' command to automatically generate the index on the specified table.

CREATE INDEX index_name ON table_name (column_name);

REINDEX TABLE <table> ;

The distinction between the two operations lies in their core functionalities. The REINDEX command is employed to rebuild existing indexes, a process designed to eliminate fragmentation or corruption within the database. Although this procedure can be resource-intensive, it significantly enhances query performance on the reconstructed index. On the other hand, the CREATE INDEX command is utilized to establish new indexes tailored for specific search conditions. While the creation of an index demands resources during its initialization, it offers a lasting improvement in query performance for the designated columns, optimizing database operations in the long term.

2.2. Dead Tuple

Another factor that can contribute to prolonged query execution in a database is the presence of a significant number of dead tuples, particularly when dealing with tables containing millions of records. You can assess the ratio of live to dead tuples using the following query.

SELECT schemaname,relname,n_live_tup,n_dead_tup FROM pg_stat_user_tables ORDER BY n_dead_tup DESC limit 10;

To eliminate dead tuples from tables and optimize the database, it is advisable to perform database vacuuming. This can be accomplished using the following commands, which can be applied to individual tables or the entire database.

VACUUM (VERBOSE, ANALYZE) <table_name>;

\c <database_name>
VACUUM (VERBOSE, ANALYZE);

This article is tailored for PostgreSQL databases.
While the specific query syntax may vary for other database systems, the underlying concept remains consistent across different platforms.