MongoDB Indexing Best Practices

Understanding MongoDB Indexes

MongoDB supports various types of indexes including single-field, compound, multikey, text, and geospatial indexes.

Each index type serves different query patterns and data structures.

• Single-field indexes speed up queries on one field.
• Compound indexes cover queries on multiple fields in a specified order.
• Multikey indexes support indexing array fields.
• Text indexes enable text search capabilities.
• Geospatial indexes support location-based queries.

Best Practices for Creating Indexes

Design indexes based on your application's query patterns to maximize efficiency.

Use compound indexes to cover queries that filter on multiple fields, but be mindful of field order.

• Analyze your most frequent and performance-critical queries first.
• Create indexes on fields used in filters, sorts, and joins.
• Order fields in compound indexes from most to least selective.
• Avoid indexing fields with low cardinality or high update frequency.
• Limit the number of indexes to reduce write overhead.

Monitoring and Maintaining Indexes

Regularly monitor index usage and performance to identify unused or inefficient indexes.

MongoDB provides tools such as explain() and index statistics to help analyze query plans and index effectiveness.

• Use db.collection.explain() to understand query execution plans.
• Check index usage statistics with db.collection.aggregate([{$indexStats: {}}]).
• Remove unused indexes to save storage and improve write performance.
• Rebuild or compact indexes if fragmentation affects performance.

Common Indexing Pitfalls to Avoid

Over-indexing can degrade write performance and increase storage requirements.

Incorrect field order in compound indexes can prevent index usage.

Indexing fields with frequent updates can cause overhead.

• Avoid creating indexes on fields that are rarely queried.
• Do not index large fields or fields with many duplicate values unnecessarily.
• Be cautious with wildcard indexes as they may index unwanted fields.
• Test index impact in staging environments before production deployment.