How do you analyze and interpret performance metrics in SQL queries?

When analyzing statistics in SQL queries (for example, using EXPLAIN or EXPLAIN ANALYZE in PostgreSQL), I pay attention to several key indicators:

• Query execution plan — the sequence of operations the DBMS performs to obtain the result.
• Execution time of each operation — helps identify bottlenecks.
• Number of rows processed at each step — a large number may indicate inefficient operations.
• Use of indexes — I check whether indexes are used to avoid full table scans.
• Join types — such as Nested Loop, Hash Join, Merge Join, to understand efficiency.

I interpret these indicators to optimize the query: adding or adjusting indexes, rewriting the query, reducing the amount of data processed, avoiding unnecessary joins.

Example analysis:

EXPLAIN ANALYZE SELECT * FROM orders o JOIN customers c ON o.customer_id = c.id WHERE c.country = 'USA';

If I see that a sequential scan of the orders table occurs and no index on customer_id is used, it means I should add an index to speed up the query.