๐๐ฃ๐ฉ๐ง๐ค๐๐ช๐๐ฉ๐๐ค๐ฃ
SQL query optimization is crucial for improving the performance of database applications. Slow queries can lead to performance bottlenecks, affecting user experience and system efficiency
1. ๐๐จ๐ ๐๐ฃ๐๐๐ญ๐๐จ
๐๐ฉ๐บ?
Indexes speed up data retrieval by reducing the number of rows that need to be scanned.
Example
— ๐๐ณ๐ฆ๐ข๐ต๐ฆ ๐ข๐ฏ ๐ช๐ฏ๐ฅ๐ฆ๐น ๐ฐ๐ฏ ๐ต๐ฉ๐ฆ ‘๐ฆ๐ฎ๐ข๐ช๐ญ’ ๐ค๐ฐ๐ญ๐ถ๐ฎ๐ฏ ๐ช๐ฏ ๐ต๐ฉ๐ฆ ‘๐ถ๐ด๐ฆ๐ณ๐ด’ ๐ต๐ข๐ฃ๐ญ๐ฆ
๐๐๐๐๐๐ ๐๐๐๐๐ ๐ช๐ฅ๐น_๐ถ๐ด๐ฆ๐ณ๐ด_๐ฆ๐ฎ๐ข๐ช๐ญ ๐๐ ๐ถ๐ด๐ฆ๐ณ๐ด(๐ฆ๐ฎ๐ข๐ช๐ญ);
Without an index, queries like the one below will require a full table scan:
๐๐๐๐๐๐ * ๐๐๐๐ ๐ถ๐ด๐ฆ๐ณ๐ด ๐๐๐๐๐ ๐ฆ๐ฎ๐ข๐ช๐ญ = ‘๐ซ๐ฐ๐ฉ๐ฏ.๐ฅ๐ฐ๐ฆ@๐ฆ๐น๐ข๐ฎ๐ฑ๐ญ๐ฆ.๐ค๐ฐ๐ฎ’;
With an index, the database can quickly locate the required row, improving query performance.
2. ๐ผ๐ซ๐ค๐๐ ๐๐๐๐๐พ๐ * (๐๐จ๐ ๐๐ฅ๐๐๐๐๐๐ ๐พ๐ค๐ก๐ช๐ข๐ฃ๐จ)
๐๐ฉ๐บ?
Fetching only required columns reduces data transfer and processing time.
Example
Instead of:
๐๐๐๐๐๐ * ๐๐๐๐ ๐ฐ๐ณ๐ฅ๐ฆ๐ณ๐ด;
Use:
SELECT order_id, order_date FROM orders;
This reduces the amount of data processed and retrieved.
3. ๐๐จ๐ ๐๐๐๐๐ผ๐๐ ๐ฉ๐ค ๐ผ๐ฃ๐๐ก๐ฎ๐ฏ๐ ๐๐ช๐๐ง๐๐๐จ
๐๐ฉ๐บ?
EXPLAIN helps understand query execution plans and identify performance bottlenecks.
Example
๐๐๐๐๐๐๐ ๐๐๐๐๐๐ * ๐๐๐๐ ๐ถ๐ด๐ฆ๐ณ๐ด ๐๐๐๐๐ ๐ฆ๐ฎ๐ข๐ช๐ญ = ‘๐ซ๐ฐ๐ฉ๐ฏ.๐ฅ๐ฐ๐ฆ@๐ฆ๐น๐ข๐ฎ๐ฑ๐ญ๐ฆ.๐ค๐ฐ๐ฎ’;
This command shows whether the query is using an index or performing a full table scan.
4. ๐๐ฅ๐ฉ๐๐ข๐๐ฏ๐ ๐
๐ค๐๐ฃ๐จ
๐๐ฉ๐บ?
Joins can be expensive, so optimizing them improves query speed.
Example
Avoid:
๐๐๐๐๐๐ * ๐๐๐๐ ๐ฐ๐ณ๐ฅ๐ฆ๐ณ๐ด
๐๐๐๐ ๐ค๐ถ๐ด๐ต๐ฐ๐ฎ๐ฆ๐ณ๐ด ๐๐ ๐ฐ๐ณ๐ฅ๐ฆ๐ณ๐ด.๐ค๐ถ๐ด๐ต๐ฐ๐ฎ๐ฆ๐ณ_๐ช๐ฅ = ๐ค๐ถ๐ด๐ต๐ฐ๐ฎ๐ฆ๐ณ๐ด.๐ช๐ฅ;
Use indexed columns for joining:
๐๐๐๐๐๐ ๐๐๐๐๐ ๐ช๐ฅ๐น_๐ฐ๐ณ๐ฅ๐ฆ๐ณ๐ด_๐ค๐ถ๐ด๐ต๐ฐ๐ฎ๐ฆ๐ณ_๐ช๐ฅ ๐๐ ๐ฐ๐ณ๐ฅ๐ฆ๐ณ๐ด(๐ค๐ถ๐ด๐ต๐ฐ๐ฎ๐ฆ๐ณ_๐ช๐ฅ);
Then execute:
๐๐๐๐๐๐ ๐ฐ๐ณ๐ฅ๐ฆ๐ณ๐ด.๐ฐ๐ณ๐ฅ๐ฆ๐ณ_๐ช๐ฅ, ๐ค๐ถ๐ด๐ต๐ฐ๐ฎ๐ฆ๐ณ๐ด.๐ฏ๐ข๐ฎ๐ฆ ๐๐๐๐ ๐ฐ๐ณ๐ฅ๐ฆ๐ณ๐ด
๐๐๐๐ ๐ค๐ถ๐ด๐ต๐ฐ๐ฎ๐ฆ๐ณ๐ด ๐๐ ๐ฐ๐ณ๐ฅ๐ฆ๐ณ๐ด.๐ค๐ถ๐ด๐ต๐ฐ๐ฎ๐ฆ๐ณ_๐ช๐ฅ = ๐ค๐ถ๐ด๐ต๐ฐ๐ฎ๐ฆ๐ณ๐ด.๐ช๐ฅ;
๐ฑ. ๐จ๐๐ฒ ๐๐๐ ๐๐ง ๐ณ๐ผ๐ฟ ๐๐ฎ๐ฟ๐ด๐ฒ ๐๐ฎ๐๐ฎ ๐ฆ๐ฒ๐๐
๐๐ฉ๐บ?
Limiting results improves performance by reducing the number of rows processed.
Example
๐๐๐๐๐๐ * ๐๐๐๐ ๐ฑ๐ณ๐ฐ๐ฅ๐ถ๐ค๐ต๐ด ๐๐๐๐๐ ๐๐ ๐ฑ๐ณ๐ช๐ค๐ฆ ๐๐๐๐ ๐๐๐๐๐ 10;
This ensures only the top 10 records are fetched instead of the entire dataset.
๐ฒ. ๐จ๐๐ฒ ๐๐ซ๐๐ฆ๐ง๐ฆ ๐๐ป๐๐๐ฒ๐ฎ๐ฑ ๐ผ๐ณ ๐๐ก
๐๐ฉ๐บ?
EXISTS is more efficient than IN for checking the existence of a value in a subquery.
Example
Instead of:
๐๐๐๐๐๐ * ๐๐๐๐ ๐ถ๐ด๐ฆ๐ณ๐ด ๐๐๐๐๐ ๐ช๐ฅ ๐๐ (๐๐๐๐๐๐ ๐ถ๐ด๐ฆ๐ณ_๐ช๐ฅ ๐๐๐๐ ๐ฐ๐ณ๐ฅ๐ฆ๐ณ๐ด);
Use:
๐๐๐๐๐๐ * ๐๐๐๐ ๐ถ๐ด๐ฆ๐ณ๐ด ๐๐๐๐๐ ๐๐๐๐๐๐ (๐๐๐๐๐๐ 1 ๐๐๐๐ ๐ฐ๐ณ๐ฅ๐ฆ๐ณ๐ด ๐๐๐๐๐ ๐ถ๐ด๐ฆ๐ณ๐ด.๐ช๐ฅ = ๐ฐ๐ณ๐ฅ๐ฆ๐ณ๐ด.๐ถ๐ด๐ฆ๐ณ_๐ช๐ฅ);
Conclusion
Effective SQL query optimization is key to faster database performance and better user experience. By applying best practices like indexing, selective columns, query analysis, and optimized joins, you reduce execution time and ensure smooth app performance.
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