10 Database Index Interview Questions and Answers

Database indexing is a crucial technique for optimizing the performance of database queries. By creating indexes, databases can quickly locate and access the data without scanning the entire table, significantly speeding up read operations. Indexes are essential for maintaining efficiency in large-scale databases and are a fundamental concept for anyone working with data storage and retrieval.

This article offers a detailed collection of interview questions focused on database indexing. Reviewing these questions will help you understand the intricacies of indexing, enabling you to demonstrate your knowledge effectively during technical interviews and improve your database management skills.

Database Index Interview Questions and Answers

1. Explain the purpose of an index in a database and how it improves query performance.

An index in a database is a data structure that enhances the speed of data retrieval operations on a table, though it requires additional writes and storage space. Indexes are created on columns frequently used in query conditions, such as the WHERE clause, to allow the database to find rows more efficiently.

When a query is executed, the database engine can use the index to quickly locate the data without scanning the entire table, similar to how an index in a book helps you quickly find the page containing the information you are looking for.

There are different types of indexes, such as:

• Primary Index: Automatically created when a primary key is defined. It ensures that the key is unique and aids in quick retrieval.
• Unique Index: Ensures that all values in the indexed column are unique.
• Composite Index: An index on multiple columns, useful for queries that filter on more than one column.
• Full-Text Index: Used for full-text searches, allowing for efficient searching of text data.

Indexes can significantly improve query performance, but they also come with trade-offs. They require additional storage space and can slow down write operations (INSERT, UPDATE, DELETE) because the index must be updated whenever the data in the indexed columns is modified.

2. What are the differences between a clustered and a non-clustered index?

A clustered index determines the physical order of data in a table. There can be only one clustered index per table because the data rows themselves can be sorted in only one order. When a table has a clustered index, the rows are stored in the leaf nodes of the index. This type of index is particularly useful for range queries, as it allows for faster retrieval of data within a specific range.

A non-clustered index, on the other hand, does not alter the physical order of the data in the table. Instead, it creates a separate object within the table that points back to the original data rows. A table can have multiple non-clustered indexes, which makes them versatile for various types of queries. Non-clustered indexes are useful for improving the performance of queries that do not require the data to be in a specific order.

3. Describe what a composite index is and provide an example of when you might use one.

A composite index is an index that is created on two or more columns of a table. It is particularly useful when queries often filter or sort by multiple columns. By using a composite index, the database can efficiently locate rows that match the criteria specified in the query, thereby improving query performance.

For example, consider a table named employees with columns first_name, last_name, and department_id. If queries frequently search for employees by both last_name and department_id, a composite index on these two columns can significantly speed up the search.

CREATE INDEX idx_lastname_deptid ON employees (last_name, department_id);

In this example, the composite index idx_lastname_deptid is created on the last_name and department_id columns. This index will be used by the database to quickly find rows where both last_name and department_id match the specified criteria.

4. Write a SQL query to create a composite index on the columns ‘first_name’ and ‘last_name’ in the ’employees’ table.

A composite index is an index on multiple columns of a table. It is particularly useful for queries that filter or sort on multiple columns, as it can significantly improve query performance. By creating a composite index on the first_name and last_name columns in the employees table, we can optimize queries that involve these columns.

Example:

CREATE INDEX idx_name ON employees (first_name, last_name);

5. Write a SQL query to create a unique index on the ‘username’ column in the ‘accounts’ table.

A unique index in a database ensures that all values in a column are distinct, preventing duplicate entries. This is particularly useful for columns like ‘username’ in an ‘accounts’ table, where each username must be unique to maintain data integrity.

To create a unique index on the ‘username’ column in the ‘accounts’ table, you can use the following SQL query:

CREATE UNIQUE INDEX idx_unique_username ON accounts(username);

This query creates a unique index named ‘idx_unique_username’ on the ‘username’ column of the ‘accounts’ table. The unique constraint ensures that no two rows can have the same value in the ‘username’ column.

6. Explain the impact of indexing on write operations like INSERT, UPDATE, and DELETE.

Indexes improve the performance of read operations by allowing the database to quickly locate and retrieve the data. However, they can negatively impact write operations like INSERT, UPDATE, and DELETE due to the additional steps required to maintain the index.

• INSERT Operations: When a new record is inserted into a table, the database must also insert the corresponding entry into each index. This additional step can slow down the insert operation, especially if the table has multiple indexes.
• UPDATE Operations: Updating a record can be more complex if the update affects indexed columns. The database must not only update the record but also update the index entries. If the update changes the indexed value, the database may need to remove the old index entry and insert a new one, which can be time-consuming.
• DELETE Operations: Deleting a record requires the database to remove the corresponding entries from all indexes. This can add overhead to the delete operation, particularly if the table has several indexes.

7. How would you handle indexing in a highly transactional environment where data changes frequently?

In a highly transactional environment, handling indexing requires careful consideration to ensure that the benefits of indexing outweigh the costs. Here are some strategies to manage indexing effectively:

• Selective Indexing: Only create indexes on columns that are frequently used in query conditions (WHERE clauses) and join operations. Avoid over-indexing, as each index adds overhead to data modification operations (INSERT, UPDATE, DELETE).
• Index Maintenance: Regularly monitor and maintain indexes. This includes rebuilding or reorganizing fragmented indexes to ensure optimal performance. Automated maintenance tasks can help manage this process.
• Composite Indexes: Use composite indexes for queries that filter on multiple columns. This can reduce the number of indexes needed and improve query performance.
• Indexing Strategies: Consider using different types of indexes based on the workload. For example, clustered indexes can be beneficial for range queries, while non-clustered indexes are useful for specific lookups.
• Partitioning: Partition large tables to improve manageability and performance. Indexes on partitioned tables can be more efficient, as they operate on smaller subsets of data.
• Monitoring and Tuning: Continuously monitor query performance and index usage. Use database tools and query execution plans to identify and address performance bottlenecks.

8. Discuss the pros and cons of using full-text indexes compared to traditional B-tree indexes.

Full-text indexes and traditional B-tree indexes serve different purposes and have distinct advantages and disadvantages.

Full-text indexes are designed for searching large bodies of text. They allow for efficient querying of text data, such as finding all documents that contain a particular word or phrase. This type of index is particularly useful for applications like search engines, where the ability to quickly search through text is important.

• Pros of Full-text Indexes:
• Efficient text searching: Full-text indexes are optimized for searching text, making them much faster than traditional indexes for this purpose.
• Advanced search capabilities: They support complex queries, such as searching for phrases, proximity searches, and ranking results by relevance.
• Handling large text data: Full-text indexes are designed to manage and search through large volumes of text data efficiently.

• Cons of Full-text Indexes:
• Increased storage requirements: Full-text indexes can consume more storage space compared to traditional indexes.
• Slower updates: Updating a full-text index can be slower, especially if the text data changes frequently.
• Complexity: Implementing and maintaining full-text indexes can be more complex than traditional indexes.

Traditional B-tree indexes are general-purpose indexes used to speed up the retrieval of rows from a database table. They are particularly effective for range queries and exact match queries on columns with a limited number of distinct values.

• Pros of B-tree Indexes:
• Efficient range and exact match queries: B-tree indexes are optimized for range queries and exact match queries, making them ideal for many common database operations.
• Lower storage requirements: B-tree indexes typically require less storage space compared to full-text indexes.
• Faster updates: Updating a B-tree index is generally faster and less resource-intensive than updating a full-text index.

• Cons of B-tree Indexes:
• Limited text search capabilities: B-tree indexes are not optimized for searching large bodies of text and can be inefficient for this purpose.
• Less advanced search features: They do not support advanced text search features like phrase searching or relevance ranking.

9. Explain the importance of index maintenance and how you would perform it.

Indexes are important for improving the performance of database queries by allowing faster retrieval of records. However, over time, indexes can become fragmented and less efficient, leading to slower query performance. Therefore, regular index maintenance is essential to ensure optimal database performance.

Index maintenance involves several key activities:

• Rebuilding Indexes: This process involves dropping and recreating the index. It is useful for heavily fragmented indexes and can significantly improve performance.
• Reorganizing Indexes: This is a lighter operation compared to rebuilding. It defragments the leaf level of the index and compacts the pages, which can help in improving performance without the overhead of a full rebuild.
• Updating Statistics: Keeping statistics up-to-date ensures that the query optimizer has accurate information to make the best decisions for query execution plans.
• Monitoring Index Usage: Regularly monitoring index usage helps identify unused or rarely used indexes, which can then be removed to reduce overhead.

10. What is index fragmentation and how do you address it?

Index fragmentation is a common issue in databases that can degrade performance over time. It occurs when the logical sequence of index pages does not align with their physical sequence on the disk. This misalignment can result from frequent insertions, updates, and deletions, leading to gaps and out-of-order pages.

There are two types of fragmentation:

• Internal Fragmentation: This happens when there is unused space within index pages.
• External Fragmentation: This occurs when the logical order of pages does not match the physical order.

To address index fragmentation, you can use the following strategies:

• Reorganize Index: This is a lightweight operation that defragments the leaf level of the index by physically reordering the pages to match the logical order. It is less resource-intensive and can be done online without significant downtime.
• Rebuild Index: This operation drops and recreates the index. It is more resource-intensive but results in a completely defragmented index. Rebuilding can be done online or offline, depending on the database system and the need for availability.

In SQL Server, for example, you can use the following commands:

-- Reorganize Index
ALTER INDEX index_name ON table_name REORGANIZE;

-- Rebuild Index
ALTER INDEX index_name ON table_name REBUILD;