How Does Indexing Improve Performance in SQL?
💡 Concept Name
Indexing in SQL – A data structure that helps the database find rows faster, reducing query time and improving performance.
📘 Quick Intro
Indexes function like a table of contents for your database, letting the SQL engine quickly locate the rows it needs without scanning every row. Proper indexing drastically improves query performance for large datasets.
🧠 Analogy / Short Story
Imagine looking for a word in a 500-page dictionary without the index—you’d flip every page until you find it. With an index, you jump directly to the page. SQL indexing works the same way—it tells the database exactly where to find the relevant rows without a full scan.
🔧 Technical Explanation
- Clustered Index – Sorts and stores the data rows in the table based on the key.
- Non-Clustered Index – Contains a copy of selected columns with pointers to the actual data rows.
- Indexes improve SELECT performance but can slow down INSERT, UPDATE, DELETE operations due to maintenance overhead.
- Useful on columns involved in WHERE, JOIN, ORDER BY, or GROUP BY clauses.
- Too many indexes can degrade performance and increase storage usage.
💻 Real Code Example
-- Create an index on the email column
CREATE INDEX idx_users_email
ON users (email);
-- Query benefits from the index
SELECT * FROM users
WHERE email = 'user@example.com';
❓ Interview Q&A
Q1: What is an index in SQL?
A: It’s a data structure that speeds up data retrieval operations on a table.
Q2: What is the difference between clustered and non-clustered indexes?
A: A clustered index defines the physical order of data in a table; a non-clustered index does not.
Q3: How does indexing improve query speed?
A: It allows the DBMS to find rows quickly without scanning the entire table.
Q4: Does indexing always improve performance?
A: Not always—it improves reads but can slow down writes.
Q5: When should you use an index?
A: On columns used in WHERE, JOIN, or ORDER BY clauses frequently.
Q6: Can too many indexes hurt performance?
A: Yes, they increase maintenance time and storage requirements.
Q7: Can indexes be used for composite columns?
A: Yes, composite indexes include multiple columns to optimize specific queries.
Q8: What is a covering index?
A: An index that includes all the columns needed by a query, avoiding lookups.
Q9: How do you view existing indexes?
A: Use system catalog views like sys.indexes or pg_indexes.
Q10: What’s the downside of indexing every column?
A: Increased overhead on write operations and wasted storage.
📝 MCQs
Q1. What does a SQL index do?
- Encrypts data
- Slows down queries
- Speeds up data retrieval
- Adds new constraints
Q2. What is a clustered index?
- Indexes BLOBs only
- Indexes views
- Physically sorts data rows
- Replaces foreign keys
Q3. When should you use an index?
- Always index all columns
- On columns used in WHERE or JOIN clauses
- Only on numeric fields
- On primary key only
Q4. What is a downside of too many indexes?
- More RAM usage
- Slower SELECTs
- Slower insert/update performance
- Incompatible joins
Q5. Which index type doesn’t change data order?
- Clustered index
- Bitmap index
- Non-clustered index
- Hash index
Q6. Can indexes affect DELETE performance?
- No
- Only on big tables
- Yes, they can slow it down
- Only foreign keys matter
Q7. What is a covering index?
- Partial index
- Default index
- An index with all queried columns
- Multi-index
Q8. What command creates an index?
- MAKE INDEX
- ADD INDEX
- CREATE INDEX
- INSERT INDEX
Q9. What happens if the index isn’t used by the query?
- Query fails
- Query crashes
- Query performs full table scan
- Index gets auto-deleted
Q10. Which clause benefits most from indexes?
- GROUP BY
- HAVING
- WHERE
- UNION
💡 Bonus Insight
Use database tools like execution plans and query analyzers to verify if your indexes are effective. Also, periodically review unused or duplicate indexes to avoid bloat and write slowdowns.
📄 PDF Download
Need a handy summary for your notes? Download this topic as a PDF!