Why indexing strategy matters in PostgreSQL - Test Your Understanding

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create an index on the column 'username' in the 'users' table.

PostgreSQL

CREATE INDEX idx_username ON users([1]);

Drag options to blanks, or click blank then click option'

Ausername

Buser_id

Cemail

Dpassword

Attempts:

3 left

💡 Hint

Common Mistakes

Choosing a column that is not used in queries often.

Trying to create an index on a non-existent column.

The index should be created on the 'username' column to speed up queries filtering by username.

2fill in blank

medium

Complete the query to find users with the email '[e-mail]' using the index.

PostgreSQL

SELECT * FROM users WHERE [1] = '[e-mail]';

Drag options to blanks, or click blank then click option'

Ausername

Bemail

Cuser_id

Dcreated_at

Attempts:

3 left

💡 Hint

Common Mistakes

Using a column that is not indexed.

Using a column unrelated to the filter condition.

The query filters by the 'email' column, so the index on 'email' would speed this up.

3fill in blank

hard

Fix the error in the index creation statement by completing the blank.

PostgreSQL

CREATE INDEX idx_created [1] users (created_at);

Drag options to blanks, or click blank then click option'

AON

BINDEX

CUNIQUE

DTABLE

Attempts:

3 left

💡 Hint

Common Mistakes

Omitting the 'ON' keyword.

Using 'TABLE' instead of 'ON'.

The correct syntax is CREATE INDEX index_name ON table_name (column); 'ON' is required before the table name.

4fill in blank

hard

Fill both blanks to create a unique index on the 'email' column in the 'customers' table.

PostgreSQL

CREATE [1] INDEX idx_email_unique [2] customers (email);

Drag options to blanks, or click blank then click option'

AUNIQUE

BTEMPORARY

CON

DTABLE

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'TABLE' instead of 'ON'.

Forgetting 'UNIQUE' for unique indexes.

To create a unique index, use 'UNIQUE' before 'INDEX' and 'ON' before the table name.

5fill in blank

hard

Fill the blanks to drop an index named 'idx_username' from the 'users' table.

PostgreSQL

DROP [1] IF EXISTS [2];

Drag options to blanks, or click blank then click option'

AINDEX

BTABLE

Cidx_username

Dusers

Attempts:

3 left

💡 Hint

Common Mistakes

Using DROP TABLE instead of DROP INDEX.

Omitting the index name.

The correct command to drop an index is DROP INDEX IF EXISTS index_name;

Practice

1. Why is having a good indexing strategy important in PostgreSQL?

easy

A. It helps the database find data faster, improving query speed.

B. It increases the size of the database without benefits.

C. It makes the database ignore queries.

D. It automatically fixes data errors.

Solution

1. Step 1: Understand what indexes do

   Indexes act like shortcuts to quickly locate data without scanning the whole table.

2. Step 2: Connect indexing to query speed

   Good indexes reduce the time to find data, making queries faster and more efficient.

3. Final Answer:

   It helps the database find data faster, improving query speed. -> Option A

4. Quick Check:

   Index = Faster data search [OK]

Hint: Indexes speed up searches by acting like shortcuts [OK]

Common Mistakes:

• Thinking indexes slow down queries
• Believing indexes fix data errors
• Assuming indexes increase query ignoring

2. Which of the following is the correct syntax to create a basic index on column email in PostgreSQL?

easy

A. CREATE INDEX ON users email;

B. CREATE INDEX idx_email ON users (email);

C. MAKE INDEX idx_email ON users email;

D. INDEX CREATE idx_email users (email);

Solution

1. Step 1: Recall PostgreSQL index creation syntax

   The correct syntax starts with CREATE INDEX, followed by index name, ON table name, and column list in parentheses.

2. Step 2: Match syntax to options

   CREATE INDEX idx_email ON users (email); matches the correct syntax exactly; others have wrong keywords or missing parentheses.

3. Final Answer:

   CREATE INDEX idx_email ON users (email); -> Option B

4. Quick Check:

   CREATE INDEX ... ON table (column) [OK]

Hint: Use CREATE INDEX index_name ON table (column) [OK]

Common Mistakes:

• Omitting parentheses around column name
• Using wrong keywords like MAKE or INDEX CREATE
• Missing ON keyword before table name

3. Given a table orders with 1 million rows and an index on customer_id, what is the likely result of this query?

SELECT * FROM orders WHERE customer_id = 12345;

medium

A. The query will return no rows because indexes filter data.

B. The query will scan all rows, ignoring the index.

C. The query will fail due to missing index.

D. The query will use the index to quickly find matching rows.

Solution

1. Step 1: Understand index usage in queries

   When a column is indexed, PostgreSQL uses the index to find matching rows quickly instead of scanning the whole table.

2. Step 2: Apply to the given query

   The query filters by customer_id, which is indexed, so the index helps find rows efficiently.

3. Final Answer:

   The query will use the index to quickly find matching rows. -> Option D

4. Quick Check:

   Indexed column = faster search [OK]

Hint: Queries on indexed columns use indexes for speed [OK]

Common Mistakes:

• Thinking index is ignored automatically
• Assuming query fails without explicit index hint
• Believing indexes filter out rows

4. You created multiple indexes on a table, but your INSERT queries became slower. What is the most likely cause?

medium

A. Indexes slow down data changes because they must update on each insert.

B. Indexes cause syntax errors during INSERT.

C. Indexes delete rows automatically on insert.

D. Indexes prevent data from being inserted.

Solution

1. Step 1: Understand index impact on data modification

   Indexes must be updated every time data changes, so more indexes mean more work during INSERT, UPDATE, DELETE.

2. Step 2: Connect to slower INSERT queries

   Because indexes update on each insert, having many indexes slows down insert speed.

3. Final Answer:

   Indexes slow down data changes because they must update on each insert. -> Option A

4. Quick Check:

   More indexes = slower inserts [OK]

Hint: More indexes slow inserts due to update overhead [OK]

Common Mistakes:

• Thinking indexes cause syntax errors
• Believing indexes block inserts
• Assuming indexes delete data automatically

5. You have a table products with columns id, category, and price. You often run this query:

SELECT * FROM products WHERE category = 'books' AND price < 20;

Which indexing strategy will most improve query speed without slowing inserts too much?

hard

A. Create no indexes to keep inserts fast.

B. Create separate indexes on category and price.

C. Create a composite index on (category, price).

D. Create an index only on price.

Solution

1. Step 1: Analyze query filter conditions

   The query filters on both category and price together, so a composite index on both columns helps the database find matching rows efficiently.

2. Step 2: Compare indexing options

   Separate indexes may be less efficient because PostgreSQL might not combine them well; no index slows queries; indexing only price misses category filtering.

3. Final Answer:

   Create a composite index on (category, price). -> Option C

4. Quick Check:

   Composite index matches multi-column filters [OK]

Hint: Use composite index for multi-column WHERE filters [OK]

Common Mistakes:

• Creating separate indexes expecting same speed
• Indexing only one column in multi-filter queries
• Avoiding indexes to keep inserts fast but hurting queries