Introduction
Updating document fields in Elasticsearch is a common operation that can be optimized to improve the performance and efficiency of your cluster. In this article, we will discuss various techniques and best practices for updating document fields in Elasticsearch, including the use of the Update API, partial updates, scripting, and versioning. If you want to learn about Elasticsearch document check out this guide. You should also take a look at this guide, which contains a detailed explanation on Elasticsearch find document by field value.
1. Using the Update API
The Update API allows you to update a document’s fields without having to reindex the entire document. This is particularly useful when you need to make small changes to large documents, as it reduces the amount of data that needs to be sent over the network, processed and stored.
To update a document field using the Update API, you can use the following request format:
POST /index_name/_update/document_id { "doc": { "field_name": "new_value" } }
For example, to update the “price” field of a document with the ID “1” in the “products” index, you would use the following request:
POST /products/_update/1 { "doc": { "price": 19.99 } }
2. Partial Updates
Partial updates are a way to update specific fields of a document without having to reindex the entire document. This can be achieved using the Update API, as shown in the previous section. Partial updates are more efficient than full updates, as they only modify the fields that need to be changed, reducing the amount of data that needs to be sent over the network, processed and stored.
3. Using Scripting for Field Updates
Elasticsearch allows you to use scripts to update document fields. This can be useful when you need to perform complex updates or calculations based on the existing field values. To update a document field using a script, you can use the following request format:
POST /index_name/_update/document_id { "script": { "source": "ctx._source.field_name = new_value" } }
For example, to increment the “views” field of a document with the ID “1” in the “articles” index, you would use the following request:
POST /articles/_update/1 { "script": { "source": "ctx._source.views += 1" } }
4. Versioning and Optimistic Concurrency Control
When updating document fields, it’s important to ensure that you’re not overwriting changes made by other processes. Elasticsearch provides a built-in mechanism called optimistic concurrency control (OCC) to handle concurrent updates.
To use OCC, you can include the `if_seq_no` and `if_primary_term` fields in your update request, which uniquely specifies the current version of the document. Elasticsearch will only apply the update if the document’s `_seq_no` and `_primary_term` match the specified respective values. If they don’t match, the update will fail, and you can handle the conflict as needed.
For example, to update the “price” field of a document with the ID “1” in the “products” index, and a current `_seq_no`of “2” and `_primary_term` of “124”, you would use the following request:
POST /products/_update/1?if_seq_no=2&if_primary_term=124 { "doc": { "price": 19.99 } }
5. Bulk Updates
When you need to update multiple documents at once, you can use the Bulk API to perform multiple update operations in a single request. This can help improve performance by reducing the number of network round-trips and allowing Elasticsearch to process the updates more efficiently.
To perform bulk updates, you can use the following request format:
POST /_bulk { "update": { "_index": "index_name", "_id": "document_id" } } { "doc": { "field_name": "new_value" } } { "update": { "_index": "index_name", "_id": "document_id" } } { "doc": { "field_name": "new_value" } } ...
For example, to update the “price” field of two documents in the “products” index, you would use the following request:
POST /_bulk { "update": { "_index": "products", "_id": "1" } } { "doc": { "price": 19.99 } } { "update": { "_index": "products", "_id": "2" } } { "doc": { "price": 29.99 } }
Conclusion
In conclusion, updating document fields in Elasticsearch can be optimized using various techniques, such as the Update API, partial updates, scripting, optimistic concurrency control, and bulk updates. By following these best practices, you can improve the performance and efficiency of your Elasticsearch cluster.