MongoDB Query Optimization for Performance

Using Explain Plans

The explain() method shows how MongoDB executes a query, including index usage and number of documents scanned.

Analyzing explain output helps identify slow queries and missing indexes.

• Use db.collection.find(query).explain('executionStats') to get detailed stats.
• Look for COLLSCAN in the winningPlan to detect collection scans.
• Check keysExamined vs docsExamined ratio to assess index efficiency.

Best Practices for Query Optimization

Writing efficient queries and designing indexes thoughtfully can drastically improve performance.

Consider query patterns and data access when creating indexes.

• Create indexes on fields used in query filters and sort operations.
• Use compound indexes to cover multiple query fields.
• Avoid using $regex or $where without indexes as they cause collection scans.
• Project only necessary fields to reduce data transfer.
• Use aggregation pipeline stages like $match early to filter data.

Example: Optimizing a Query with Indexes

Suppose you have a collection of orders and want to find all orders by a customer sorted by date.

Without an index, MongoDB scans all documents, which is slow for large collections.