Optimize Query Performance¶

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Create Indexes to Support Queries
Limit the Number of Query Results to Reduce Network Demand
Use Projections to Return Only Necessary Data
Use $hint to Select a Particular Index
Use the Increment Operator to Perform Operations Server-Side
Additional Resources

Create Indexes to Support Queries¶

For commonly issued queries, create indexes. If a query searches multiple fields, create a compound index. Scanning an index is much faster than scanning a collection. The indexes structures are smaller than the documents reference, and store references in order.

Example

If you have a posts collection containing blog posts, and if you regularly issue a query that sorts on the author_name field, then you can optimize the query by creating an index on the author_name field:

db.posts.createIndex( { author_name : 1 } )

Indexes also improve efficiency on queries that routinely sort on a given field.

Example

If you regularly issue a query that sorts on the timestamp field, then you can optimize the query by creating an index on the timestamp field:

Creating this index:

db.posts.createIndex( { timestamp : 1 } )

Optimizes this query:

db.posts.find().sort( { timestamp : -1 } )

Because MongoDB can read indexes in both ascending and descending order, the direction of a single-key index does not matter.

Indexes support queries, update operations, and some phases of the aggregation pipeline.

Index keys that are of the BinData type are more efficiently stored in the index if:

the binary subtype value is in the range of 0-7 or 128-135, and
the length of the byte array is: 0, 1, 2, 3, 4, 5, 6, 7, 8, 10, 12, 14, 16, 20, 24, or 32.

Limit the Number of Query Results to Reduce Network Demand¶

MongoDB cursors return results in groups of multiple documents. If you know the number of results you want, you can reduce the demand on network resources by issuing the limit() method.

This is typically used in conjunction with sort operations. For example, if you need only 10 results from your query to the posts collection, you would issue the following command:

db.posts.find().sort( { timestamp : -1 } ).limit(10)

For more information on limiting results, see limit()

Use Projections to Return Only Necessary Data¶

When you need only a subset of fields from documents, you can achieve better performance by returning only the fields you need:

For example, if in your query to the posts collection, you need only the timestamp, title, author, and abstract fields, you would issue the following command:

db.posts.find( {}, { timestamp : 1 , title : 1 , author : 1 , abstract : 1} ).sort( { timestamp : -1 } )

For more information on using projections, see Limit Fields to Return from a Query.

Use `$hint` to Select a Particular Index¶

In most cases the query optimizer selects the optimal index for a specific operation; however, you can force MongoDB to use a specific index using the hint() method. Use hint() to support performance testing, or on some queries where you must select a field or field included in several indexes.

Use the Increment Operator to Perform Operations Server-Side¶

Use MongoDB’s $inc operator to increment or decrement values in documents. The operator increments the value of the field on the server side, as an alternative to selecting a document, making simple modifications in the client and then writing the entire document to the server. The $inc operator can also help avoid race conditions, which would result when two application instances queried for a document, manually incremented a field, and saved the entire document back at the same time.

Additional Resources¶

MongoDB Performance Evaluation and Tuning Consulting Package

← Evaluate Performance of Current Operations Design Notes →

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