In interviews, you may encounter questions designed to assess your understanding of database indexing and its importance. Common questions include:

• "What are the key considerations for database indexing?"
• "Can you explain the different types of indexes and their use cases?"
• "How does indexing impact database performance?"

These questions aim to evaluate your knowledge of indexing strategies, their benefits, and potential pitfalls, ensuring you can optimize database performance effectively.

Understanding Database Indexing

Indexing is a technique used to speed up the retrieval of records from a database by providing quick access paths to data. Here's what you need to grasp:

1. Types of Indexes:

   • Why It Matters: Understanding the variations between types, such as B-tree, bitmap, and hash indexes, helps you choose the right one based on data patterns and query types.
   • B-tree Indexes: Balanced tree structures ideal for a wide range of queries, particularly those involving range searches.
   • Bitmap Indexes: Efficient for low cardinality columns with many repeated values.
   • Hash Indexes: Best for exact match queries, not suitable for range queries.

2. Indexing Considerations:

   • Why It Matters: Effective indexing necessitates considering various factors to ensure optimal performance.
   • Column Selectivity: High-selectivity columns (more unique values) benefit more from indexing.
   • Index Maintenance: Indexes must be maintained during insert, update, and delete operations, which can impact performance.
   • Composite Indexes: Combining multiple columns into one index can optimize complex queries but must be used judiciously.

3. Trade-offs:

   • Why It Matters: Knowing the trade-offs helps in striking a balance between query performance and system overhead.