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Query Optimization

Optimize Query Performance

On this page

  • 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

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 Project Fields to Return from 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.

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