Disadvantages of Using Dynamic Mapping
- Limited Control: Dynamic mapping in MongoDB offers less control over the indexing process compared to static mapping.
- Irrelevant indexes: Large number fields are indexed in the document regardless of whether they are relevant or not.
- Performance Considerations: It added extra processing time by determining the data types during indexing and querying.
- Extra Space: It takes more disk space and might negatively impacts the cluster performance.
- Potential for Inaccuracy: Since dynamic mapping automatically detects field types, there’s a chance it might misinterpret certain data types, leading to less accurate search results.
How to Create a Search Index with Dynamic Field Mapping in MongoDB
Dynamic mapping in MongoDB Atlas Search is a powerful feature that automatically indexes all supported field types in a collection and making it ideal for applications with evolving data models. This type of mapping is particularly useful when the schema is unknown or changes regularly. Dynamic mappings assign fields automatically when new data is inserted, simplifying the setup for diverse data structures.
In this article, We will learn about, What is Dynamic Mapping, Need of Dynamic Field Mapping for Search Indexes, When to Use Dynamic Mapping and how to create Search Index for Dynamic Mapping Using Mongosh or MongoDB Driver detail.