Optimize Query Performance

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 } )
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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 } )
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Optimizes this query:

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

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