mongodb advanced indexing
MongoDB supports various advanced indexing techniques that can improve the performance of queries and aggregations. Some of the advanced indexing techniques supported by MongoDB are:
Multi-key Indexing: Multi-key indexing is used when an index field contains an array. MongoDB creates separate index entries for each element of the array. This technique can be used to optimize queries that involve array fields.
Text Indexing: Text indexing is used to support text search queries in MongoDB. Text indexes are created on a single field that contains string content. MongoDB provides several text search features, such as stemming and stop words.
Geospatial Indexing: Geospatial indexing is used to support queries that involve geospatial data. MongoDB supports two types of geospatial indexing: 2d indexes and 2dsphere indexes. 2d indexes are used to index points on a two-dimensional plane, while 2dsphere indexes are used to index points on a sphere or a geoid.
Hashed Indexing: Hashed indexing is used to create a hash index on a single field. MongoDB uses a hash function to generate an index key based on the field value. Hashed indexing is used for equality-based queries, and it can improve the performance of queries that use sharding.
Covered Queries: A covered query is a query that can be satisfied entirely from an index without accessing the actual documents in the collection. Covered queries can improve query performance because they avoid reading data from disk.
Index Intersection: Index intersection is a technique that involves using multiple indexes to satisfy a query. MongoDB can combine multiple indexes to satisfy a query, even if the indexes do not cover all the fields in the query.
By using these advanced indexing techniques, you can optimize the performance of your MongoDB queries and improve the scalability of your applications.