Indices and Documents in Elasticsearch
Introduction
Elasticsearch is a distributed, RESTful search and analytics engine capable of solving a growing number of use cases. At its core, it allows you to store, search, and analyze big volumes of data quickly and in near real-time. Two fundamental concepts in Elasticsearch are indices and documents.
What is an Index?
An index in Elasticsearch is like a database in a traditional relational database. It is a collection of documents that share similar characteristics. An index is identified by a name, which is used to refer to the index when performing various operations within it.
Example: Creating an index named my_index
What is a Document?
A document is a basic unit of information that can be indexed. It is expressed in JSON (JavaScript Object Notation), which is a popular data interchange format. Each document is stored in an index and has a unique identifier.
Example: Adding a document to the my_index index
{"name": "John Doe", "age": 30, "occupation": "Software Engineer"}
Index Operations
There are several operations that you can perform on an index. Some of the most common operations include:
- Creating an index
- Deleting an index
- Getting index information
Example: Deleting the my_index index
Document Operations
Elasticsearch provides several operations to manage documents within an index. Common document operations include:
- Indexing a document
- Updating a document
- Deleting a document
- Retrieving a document
Example: Retrieving a document from the my_index index
Conclusion
Understanding indices and documents is crucial to effectively using Elasticsearch. Indices help you organize your data, while documents store your data in a structured format. With these basics, you can start exploring more advanced features of Elasticsearch to build powerful search and analytics solutions.