📄️ Indexing
Indexing is a critical feature in MongoDB that allows you to perform queries more efficiently. Without indexes, MongoDB would have to perform a collection scan, i.e., scan every document in a collection, to find the documents that match the query statement. With indexes, however, MongoDB can limit the number of documents it needs to examine, thereby improving query performance.
📄️ Advanced concepts
Background indexes
📄️ Single indexes
In MongoDB, single-field indexing refers to creating an index on a single field of the documents in a collection. Indexing improves the performance of search queries by allowing the database engine to look up values more efficiently. The most basic type of index is the single-field index, and MongoDB automatically creates one on the _id field when you create a new collection.
📄️ Compound indexes
In MongoDB, a compound index is an index that involves multiple fields within a collection's documents. Compound indexes can greatly improve query performance by allowing the database engine to filter on multiple criteria simultaneously. They are particularly useful for queries that involve sorting or filtering on more than one field.
📄️ Text indexes
In MongoDB, a text index is a special type of index that allows for text search queries on string content. Text indexes can include any field whose value is a string or an array of string elements. These indexes are particularly useful for implementing features like search engines, where you need to locate documents based on text content.
📄️ Hashed indexes
A hashed index in MongoDB is a type of index that stores the hash of the field value instead of the value itself. Hashed indexes are particularly useful for sharding collections, as they provide a more even distribution of data across shards. They are also useful for equality-based queries but are not suitable for range queries or sorting.
📄️ Geospatial indexes
Geospatial indexing in MongoDB allows you to perform queries on geometric data types like points, lines, and polygons. These indexes are particularly useful for location-based services such as mapping, routing, and geofencing. MongoDB supports two main types of geospatial indexes: 2d indexes and 2dsphere indexes.
📄️ explain()
The explain() method in MongoDB provides detailed information about how a query is executed, allowing you to analyze its performance characteristics. By using explain(), you can understand the query execution plan, which helps in optimizing queries for better performance.
📄️ MultiKey indexes
Multi-Key indexes in MongoDB allow you to index fields that contain an array value. When you create a Multi-Key index on an array field, MongoDB creates separate index entries for each element in the array. This enables efficient queries on individual elements within arrays.