Describe a specific case of PostgreSQL optimization with chunking: what was before and what changed after?

Let's consider a case of optimizing queries to a large table in PostgreSQL using chunking technique (breaking into parts).

Before optimization:

• Data retrieval queries were executed on the entire table, for example, with millions of rows.
• This led to long response times and high load on the database.

Optimization:

• The table was divided into chunks (for example, by ID ranges or date) using filtering in WHERE.
• Instead of one large query, several small queries were executed on parts of the data.
• Chunks could be processed in parallel, which improved performance.

After optimization:

• Query execution time significantly decreased.
• Memory and CPU load on the database reduced.
• Application responsiveness improved.

Example:

-- Before: one large query
SELECT * FROM big_table WHERE condition;

-- After: split into chunks by ID
SELECT * FROM big_table WHERE id BETWEEN 1 AND 10000;
SELECT * FROM big_table WHERE id BETWEEN 10001 AND 20000;
-- and so on

This approach is especially useful when processing large volumes of data, migrations, backups, or batch processing.