In this section, we will cover how to update and delete data in Elasticsearch. These operations are crucial for maintaining the accuracy and relevance of your data. We will explore the following topics:
- Updating Documents
- Deleting Documents
- Bulk Operations
- Practical Exercises
- Updating Documents
Updating documents in Elasticsearch can be done in several ways. The most common methods are:
- Partial Update: Update specific fields of a document.
- Scripted Update: Use a script to update a document.
Partial Update
A partial update allows you to update specific fields of a document without sending the entire document. This is done using the _update
endpoint.
Example:
In this example, the document with ID 1
in the index my_index
will have its field1
updated to new_value
.
Scripted Update
A scripted update allows you to use a script to update a document. This is useful for more complex updates.
Example:
POST /my_index/_update/1 { "script": { "source": "ctx._source.field1 += params.increment", "params": { "increment": 5 } } }
In this example, the script increments the value of field1
by 5 for the document with ID 1
in the index my_index
.
- Deleting Documents
Deleting documents in Elasticsearch can be done using the _delete
endpoint. You can delete a single document or multiple documents using a query.
Deleting a Single Document
To delete a single document, you need to specify the index and the document ID.
Example:
In this example, the document with ID 1
in the index my_index
will be deleted.
Deleting Documents by Query
You can delete multiple documents that match a specific query using the _delete_by_query
endpoint.
Example:
In this example, all documents in the index my_index
where field1
matches value_to_delete
will be deleted.
- Bulk Operations
Elasticsearch provides a bulk API to perform multiple update and delete operations in a single request. This is useful for improving performance when dealing with large datasets.
Bulk Update
Example:
POST /_bulk { "update": { "_id": "1", "_index": "my_index" } } { "doc": { "field1": "new_value" } } { "update": { "_id": "2", "_index": "my_index" } } { "doc": { "field1": "another_value" } }
In this example, two documents in the index my_index
are updated in a single bulk request.
Bulk Delete
Example:
POST /_bulk { "delete": { "_id": "1", "_index": "my_index" } } { "delete": { "_id": "2", "_index": "my_index" } }
In this example, two documents in the index my_index
are deleted in a single bulk request.
- Practical Exercises
Exercise 1: Partial Update
- Create an index
test_index
and add a document with ID1
and the following content:{ "name": "John Doe", "age": 30, "city": "New York" }
- Update the
age
field to31
using a partial update.
Solution:
Exercise 2: Scripted Update
- Create an index
test_index
and add a document with ID2
and the following content:{ "name": "Jane Doe", "age": 25, "city": "Los Angeles" }
- Increment the
age
field by1
using a scripted update.
Solution:
POST /test_index/_update/2 { "script": { "source": "ctx._source.age += params.increment", "params": { "increment": 1 } } }
Exercise 3: Delete by Query
- Create an index
test_index
and add multiple documents with thecity
field set toNew York
. - Delete all documents where the
city
field isNew York
.
Solution:
Conclusion
In this section, we covered how to update and delete data in Elasticsearch. We explored partial updates, scripted updates, and bulk operations. We also provided practical exercises to reinforce the learned concepts. Understanding these operations is essential for maintaining and managing your Elasticsearch indices effectively. In the next section, we will dive into the Elasticsearch Query DSL to perform more advanced searches.
Elasticsearch Course
Module 1: Introduction to Elasticsearch
- What is Elasticsearch?
- Installing Elasticsearch
- Basic Concepts: Nodes, Clusters, and Indices
- Elasticsearch Architecture
Module 2: Getting Started with Elasticsearch
Module 3: Advanced Search Techniques
Module 4: Data Modeling and Index Management
Module 5: Performance and Scaling
Module 6: Security and Access Control
- Securing Elasticsearch
- User Authentication and Authorization
- Role-Based Access Control
- Auditing and Compliance
Module 7: Integrations and Ecosystem
- Elasticsearch with Logstash
- Elasticsearch with Kibana
- Elasticsearch with Beats
- Elasticsearch with Other Tools