Here are the top 238 SQL_Queries. Practice daily for three hours. Sure, this will help crack your interviews. On top of that, I have provided Nine SQL query optimization ideas for your read.
9 SQL Optimization Techniques With Before and After Queries
1. The SQL query becomes faster if you use the actual column names in the SELECT statement instead of ‘*’.
SELECT id, first_name, last_name, age, subject FROM student_details; Instead: SELECT * FROM student_details;
2. HAVING clause is used to filter the rows after all the rows are selected. It is just like a filter.
Do not use the HAVING clause for any other purposes.
For Example: Write the query as
SELECT subject, count(subject) FROM student_details WHERE subject != 'English' AND subject != 'Maths' GROUP BY subject; Instead: SELECT subject, count(subject) FROM student_details GROUP BY subject HAVING subject!= 'Vancouver' AND subject!= 'Toronto';
3. Minimize sub queries:
SELECT name FROM employee WHERE (salary, age ) = (SELECT MAX (salary), MAX (age) FROM employee_details) AND dept = 'engineering'; Instead: SELECT name FROM employee WHERE salary = (SELECT MAX(salary) FROM employee_details) AND age = (SELECT MAX(age) FROM employee_details) AND emp_dept = 'engineering';
4. Use operator EXISTS, IN and table joins appropriately in your query.
a) Usually IN has the slowest performance.
b) IN is efficient when most of the filter criteria are in the sub-query.
c) EXISTS is efficient when most of the filter criteria are in the main query.
For Example: Write the query as
Select * from product p
where EXISTS (select * from order_items o
where o.product_id = p.product_id)
Instead:
Select * from product p
where product_id IN
(select product_id from order_items)
5. Use EXISTS instead of DISTINCT when using joins which involves tables having a one-to-many relationship.
For Example: Write the query as
SELECT d.dept_id, d.dept FROM dept d WHERE EXISTS ( SELECT 'X' FROM employee e WHERE e.dept = d.dept); Instead: SELECT DISTINCT d.dept_id, d.dept FROM dept d,employee e WHERE e.dept = e.dept;
6. Try to use UNION ALL in place of UNION.
For Example: Write the query as
SELECT id, first_name FROM student_details_class10 UNION ALL SELECT id, first_name FROM sports_team; Instead: SELECT id, first_name, subject FROM student_details_class10 UNION SELECT id, first_name FROM sports_team;
7. Be careful while using conditions in WHERE clause.
For Example: Write the query as SELECT id, first_name, age FROM student_details WHERE age > 10; Instead: SELECT id, first_name, age FROM student_details WHERE age != 10;
Write the query as
SELECT id, first_name, age FROM student_details WHERE first_name LIKE 'Chan%'; Instead: SELECT id, first_name, age FROM student_details WHERE SUBSTR(first_name,1,3) = 'Cha';
Write the query as
SELECT id, first_name, age FROM student_details WHERE first_name LIKE NVL ( :name, '%'); Instead: SELECT id, first_name, age FROM student_details WHERE first_name = NVL ( :name, first_name);
Write the query as
SELECT product_id, product_name FROM product WHERE unit_price BETWEEN MAX(unit_price) and MIN(unit_price) Instead: SELECT product_id, product_name FROM product WHERE unit_price >= MAX(unit_price) and unit_price <= MIN(unit_price)
Write the query as
SELECT id, name, salary FROM employee WHERE dept = 'Electronics' AND location = 'Bangalore'; Instead: SELECT id, name, salary FROM employee WHERE dept || location= 'ElectronicsBangalore';
8. Use non-column expression on one side of the query because it will be processed earlier.
Write the query as
SELECT id, name, salary FROM employee WHERE salary < 25000; Instead: SELECT id, name, salary FROM employee WHERE salary + 10000 < 35000;
Write the query as
SELECT id, first_name, age FROM student_details WHERE age > 10; Instead: SELECT id, first_name, age FROM student_details WHERE age NOT = 10;
9. Use DECODE to avoid the scanning of the same rows or joining the same table repetitively. DECODE can also be made used in place of the GROUP BY or ORDER BY clause.
For Example: Write the query as
SELECT id FROM employee WHERE name LIKE 'Srini%' and location = 'Bangalore'; Instead: SELECT DECODE(location,'Bangalore',id,NULL) id FROM employee WHERE name LIKE 'Srini%';
- To store large binary objects, first, place them in the file system and add the file path in the database.
- To write queries that provide efficient performance follows the general SQL standard rules.
a) Use single case for all SQL verbs
b) Begin all SQL verbs on a new line
c) Separate all words with a single space
d) Right or left aligning verbs within the initial SQL verb
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