Index selection guidelines in DBMS Theory - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create an index on the 'email' column of the 'users' table.

DBMS Theory

CREATE INDEX [1] ON users(email);

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

Aidx_email

Busers_email_idx

Cemail_index

Dindex_email

Attempts:

3 left

💡 Hint

Common Mistakes

Using reserved keywords as index names.

Leaving the index name empty.

Using vague names like 'index1'.

The index name should be descriptive and unique. 'users_email_idx' clearly indicates the table and column indexed.

2fill in blank

medium

Complete the code to create a composite index on 'last_name' and 'first_name' columns.

DBMS Theory

CREATE INDEX [1] ON employees(last_name, first_name);

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

Aemp_name_idx

Bname_index

Cidx_employees_name

Demployee_index

Attempts:

3 left

💡 Hint

Common Mistakes

Creating an index with only one column when multiple columns are needed.

Using generic names that don't specify columns.

'idx_employees_name' clearly indicates the table and columns involved in the composite index.

3fill in blank

hard

Fix the error in the code to create a unique index on the 'username' column.

DBMS Theory

CREATE [1] INDEX idx_username ON users(username);

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

ACHECK

BPRIMARY

CFOREIGN

DUNIQUE

Attempts:

3 left

💡 Hint

Common Mistakes

Using PRIMARY instead of UNIQUE for unique indexes.

Omitting the UNIQUE keyword when uniqueness is required.

The keyword 'UNIQUE' ensures that the index enforces uniqueness on the 'username' column.

4fill in blank

hard

Fill both blanks to create an index on the 'order_date' column in descending order.

DBMS Theory

CREATE INDEX idx_order_date ON orders(order_date [1]); -- [2]

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

ADESC

BASC

Cdescending

Dascending

Attempts:

3 left

💡 Hint

Common Mistakes

Using 'ascending' instead of 'ASC' or 'DESC'.

Omitting the order keyword, which defaults to ascending.

The correct SQL keyword for descending order is 'DESC'. The comment uses 'ASC' as a distractor but the code requires descending order.

5fill in blank

hard

Fill all three blanks to create a partial index on the 'status' column where status is 'active'.

DBMS Theory

CREATE INDEX idx_active_users ON users([1]) WHERE [2] = '[3]';

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

Astatus

Cactive

Dinactive

Attempts:

3 left

💡 Hint

Common Mistakes

Using the wrong column name in the WHERE clause.

Using 'inactive' instead of 'active' in the filter.

The partial index is created on the 'status' column, filtering rows where status equals 'active'.

Practice

1. Which of the following is the best reason to create an index on a database column?

easy

A. To make data entry faster

B. To reduce the size of the database

C. To speed up searches on that column

D. To prevent data duplication

Solution

1. Step 1: Understand the purpose of an index

   An index is like a shortcut that helps the database find rows faster when searching by that column.

2. Step 2: Compare options with index purpose

   Only speeding up searches matches the main use of indexes; other options do not relate to indexing benefits.

3. Final Answer:

   To speed up searches on that column -> Option C

4. Quick Check:

   Indexes improve search speed = A [OK]

Hint: Indexes speed up searches, not data entry or size [OK]

Common Mistakes:

• Thinking indexes reduce database size
• Believing indexes speed up data insertion
• Confusing indexes with uniqueness constraints

2. Which of the following is the correct SQL syntax to create an index named idx_name on the column last_name of the table employees?

easy

A. CREATE INDEX idx_name ON employees (last_name);

B. CREATE idx_name INDEX ON employees (last_name);

C. INDEX CREATE idx_name ON employees (last_name);

D. CREATE INDEX ON employees idx_name (last_name);

Solution

1. Step 1: Recall standard SQL syntax for creating an index

   The correct syntax is: CREATE INDEX index_name ON table_name (column_name);

2. Step 2: Match options to syntax

   CREATE INDEX idx_name ON employees (last_name); matches the correct syntax exactly; others have wrong order or keywords.

3. Final Answer:

   CREATE INDEX idx_name ON employees (last_name); -> Option A

4. Quick Check:

   Standard SQL index creation = C [OK]

Hint: Remember: CREATE INDEX name ON table (column) [OK]

Common Mistakes:

• Swapping keywords order
• Omitting the INDEX keyword
• Placing index name after table name incorrectly

3. Consider a table orders with columns order_id, customer_id, and order_date. If you create an index on customer_id, what will be the expected effect when running this query?
SELECT * FROM orders WHERE customer_id = 123;

medium

A. The query will run slower because indexes slow down searches

B. The query will cause an error due to the index

C. The query will return no results because indexes filter data

D. The query will run faster because the index helps find matching rows quickly

Solution

1. Step 1: Understand index effect on search queries

   An index on customer_id allows the database to quickly locate rows where customer_id = 123 without scanning the whole table.

2. Step 2: Analyze query behavior with index

   The query uses a WHERE condition on customer_id, so the index speeds up the search, making the query faster.

3. Final Answer:

   The query will run faster because the index helps find matching rows quickly -> Option D

4. Quick Check:

   Index speeds up WHERE searches = B [OK]

Hint: Indexes speed up WHERE filters on indexed columns [OK]

Common Mistakes:

• Thinking indexes slow down searches
• Believing indexes filter out data
• Assuming indexes cause errors in queries

4. You created an index on the email column of the users table, but after inserting many new users, the database performance for inserts slowed down significantly. What is the most likely cause?

medium

A. The index was created on the wrong column

B. Indexes slow down data insertion because they must update with each insert

C. The database does not support indexes on email columns

D. The table is too small for indexes to help

Solution

1. Step 1: Understand index impact on data changes

   Indexes improve search speed but add overhead during inserts because the index structure must be updated for each new row.

2. Step 2: Analyze why inserts slow down

   Since the index updates on every insert, many inserts cause slower performance, which matches Indexes slow down data insertion because they must update with each insert.

3. Final Answer:

   Indexes slow down data insertion because they must update with each insert -> Option B

4. Quick Check:

   Indexes slow inserts due to update overhead = A [OK]

Hint: Indexes slow inserts due to update work [OK]

Common Mistakes:

• Blaming wrong column choice for insert slowdown
• Thinking indexes cause errors on email columns
• Assuming small tables don't need indexes

5. You have a large sales table with columns sale_id, product_id, sale_date, and region. You often run queries filtering by product_id and region together. Which index strategy is best to improve query speed without hurting insert performance too much?

hard

A. Create a composite index on (product_id, region)

B. Create separate indexes on product_id and region

C. Create an index only on sale_date

D. Do not create any indexes to keep inserts fast

Solution

1. Step 1: Analyze query filter columns

   Queries filter by both product_id and region together, so a composite index on both columns helps the database find matching rows efficiently.

2. Step 2: Compare index strategies

   Separate indexes may help but are less efficient for combined filters; indexing sale_date is irrelevant here; no index hurts query speed.

3. Final Answer:

   Create a composite index on (product_id, region) -> Option A

4. Quick Check:

   Composite index matches multi-column filters = D [OK]

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

Common Mistakes:

• Creating separate indexes instead of composite
• Indexing unrelated columns
• Avoiding indexes and hurting query speed