Why filtering is essential in SQL - Challenge Your Understanding

Challenge - 5 Problems

❓ query_result

intermediate

Filtering rows with WHERE clause

Given the table Employees with columns id, name, and department, what will be the output of this query?

SELECT name FROM Employees WHERE department = 'Sales';

SQL

SELECT name FROM Employees WHERE department = 'Sales';

A [{"name": "Alice"}, {"name": "Bob"}, {"name": "Charlie"}]

B [{"name": "Alice"}, {"name": "Bob"}]

C []

D SyntaxError

💡 Hint

Filtering with WHERE limits rows to those matching the condition.

The WHERE clause filters rows to only those where department is 'Sales'. Only Alice and Bob belong to Sales.

🧠 Conceptual

intermediate

Why filtering improves query performance

Why is filtering data using conditions important in database queries?

A It reduces the amount of data processed and returned, improving speed and resource use.

B It increases the number of rows returned to show more data.

C It automatically creates indexes on columns.

D It changes the structure of the database tables.

💡 Hint

Think about how less data means faster work.

Filtering limits data to only what is needed, so queries run faster and use fewer resources.

📝 Syntax

advanced

Identify the correct filtering syntax

Which of the following SQL queries correctly filters employees with salary greater than 50000?

A SELECT * FROM Employees HAVING salary > 50000;

B SELECT * FROM Employees FILTER salary > 50000;

C SELECT * FROM Employees WHERE salary > 50000;

D SELECT * FROM Employees WHERE salary >= 50000;

💡 Hint

The WHERE clause is used for filtering rows before grouping.

Option C uses correct WHERE syntax. A uses invalid FILTER keyword. C uses HAVING which is for groups. D has wrong operator => instead of >=.

❓ optimization

advanced

Effect of filtering on query optimization

Consider a large table Orders. Which filtering approach helps the database optimize query performance best?

A Filtering after retrieving all rows without WHERE clause.

B Filtering on non-indexed columns with broad conditions.

C Filtering using OR conditions on multiple columns without indexes.

D Filtering on indexed columns with selective conditions.

💡 Hint

Indexes help the database find rows faster when filtering.

Filtering on indexed columns with selective conditions allows the database to quickly locate relevant rows, improving performance.

🔧 Debug

expert

Why does this filtering query return no rows?

Given the query:

SELECT * FROM Products WHERE price < 0;

Why might this query return an empty result set?

A Because prices are never negative, so no rows match the condition.

B Because the WHERE clause syntax is incorrect.

C Because the Products table is empty.

D Because the price column is not numeric.

💡 Hint

Think about what values prices usually have.

Prices are typically zero or positive, so filtering for price < 0 returns no rows.