Get started with the serverless Ruby client
Set up and use the Ruby client for serverless Elasticsearch.
This page guides you through the installation process Ruby client for serverless Elasticsearch, shows you how to initialize the client, and how to perform basic Elasticsearch operations with it.
Requirements
- Ruby 3.0 or higher installed on your system.
- To use the
elasticsearch-serverless
gem, you must have an API key and Elasticsearch Endpoint for an serverless Elasticsearch project.
Installation
From GitHub's releases
You can install the Ruby Client from RubyGems:
gem install elasticsearch-serverless --pre
Check releases for the latest available versions.
From the source code
You can install the Ruby client from the client's source code with the following commands:
# From the project's root directory:
gem build elasticsearch-serverless.gemspec
gem install elasticsearch-serverless-x.x.x.gem
Using the Gemfile
Alternatively, you can include the client gem in your Ruby project's Gemfile:
gem 'elasticsearch-serverless'
Once installed, require it in your code:
require 'elasticsearch-serverless'
Running a Ruby console
You can also run the client from a Ruby console using the client's source code. To start the console, run the following commands:
# From the project's root directory:
bundle install
bundle exec rake console
Initialize the client
Initialize the client using your API key and Elasticsearch Endpoint:
client = ElasticsearchServerless::Client.new(
api_key: 'your_api_key',
url: 'https://...'
)
To get API keys or the Elasticsearch Endpoint for a project, see Get started.
Using the API
After you've initialized the client, you can start ingesting documents. You can use
the bulk
API for this. This API enables you to index, update, and delete several
documents in one request.
Note
The code examples in this section use the Ruby console. To set up the console, Running a Ruby console.
Creating an index and ingesting documents
You can call the bulk
API with a body parameter, an array of hashes that
define the action, and a document.
The following is an example of indexing some classic books into the books
index:
# First, build your data:
> body = [
{ index: { _index: 'books', data: {name: "Snow Crash", author: "Neal Stephenson", release_date: "1992-06-01", page_count: 470} } },
{ index: { _index: 'books', data: {name: "Revelation Space", author: "Alastair Reynolds", release_date: "2000-03-15", page_count: 585} } },
{ index: { _index: 'books', data: {name: "1984", author: "George Orwell", release_date: "1949-06-08", page_count: 328} } },
{ index: { _index: 'books', data: {name: "Fahrenheit 451", author: "Ray Bradbury", release_date: "1953-10-15", page_count: 227} } },
{ index: { _index: 'books', data: {name: "Brave New World", author: "Aldous Huxley", release_date: "1932-06-01", page_count: 268} } },
{ index: { _index: 'books', data: {name: "The Handmaid's Tale", author: "Margaret Atwood", release_date: "1985-06-01", page_count: 311} } }
]
# Then ingest the data via the bulk API:
> response = client.bulk(body: body)
# You can check the response if the items are indexed and have a document (doc) ID:
> response['items']
# Returns:
# =>
# [{"index"=>{"_index"=>"books", "_id"=>"Pdink4cBmDx329iqhzM2", "_version"=>1, "result"=>"created", "_shards"=>{"total"=>2, "successful"=>1, "failed"=>0}, "_seq_no"=>0, "_primary_term"=>1, "status"=>201}},
# {"index"=>{"_index"=>"books", "_id"=>"Ptink4cBmDx329iqhzM2", "_version"=>1, "result"=>"created", "_shards"=>{"total"=>2, "successful"=>1, "failed"=>0}, "_seq_no"=>1, "_primary_term"=>1, "status"=>201}},
# {"index"=>{"_index"=>"books", "_id"=>"P9ink4cBmDx329iqhzM2", "_version"=>1, "result"=>"created", "_shards"=>{"total"=>2, "successful"=>1, "failed"=>0}, "_seq_no"=>2, "_primary_term"=>1, "status"=>201}},
# {"index"=>{"_index"=>"books", "_id"=>"QNink4cBmDx329iqhzM2", "_version"=>1, "result"=>"created", "_shards"=>{"total"=>2, "successful"=>1, "failed"=>0}, "_seq_no"=>3, "_primary_term"=>1, "status"=>201}},
# {"index"=>{"_index"=>"books", "_id"=>"Qdink4cBmDx329iqhzM2", "_version"=>1, "result"=>"created", "_shards"=>{"total"=>2, "successful"=>1, "failed"=>0}, "_seq_no"=>4, "_primary_term"=>1, "status"=>201}},
# {"index"=>{"_index"=>"books", "_id"=>"Qtink4cBmDx329iqhzM2", "_version"=>1, "result"=>"created", "_shards"=>{"total"=>2, "successful"=>1, "failed"=>0}, "_seq_no"=>5, "_primary_term"=>1, "status"=>201}}]
When you use the client to make a request to Elasticsearch, it returns an API
response object. You can check the HTTP return code by calling status
and the
HTTP headers by calling headers
on the response object. The response object
also behaves as a Hash, so you can access the body values directly as seen on
the previous example with response['items']
.
Getting documents
You can get documents by using the following code:
> client.get(index: 'books', id: 'id') # Replace 'id' with a valid doc ID
Searching
Now that some data is available, you can search your documents using the
search
API:
> response = client.search(index: 'books', q: 'snow')
> response['hits']['hits']
# Returns:
# => [{"_index"=>"books", "_id"=>"Pdink4cBmDx329iqhzM2", "_score"=>1.5904956, "_source"=>{"name"=>"Snow Crash", "author"=>"Neal Stephenson", "release_date"=>"1992-06-01", "page_count"=>470}}]
Updating a document
You can call the update
API to update a document:
> response = client.update(
index: 'books',
id: 'id', # Replace 'id' with a valid doc ID
body: { doc: { page_count: 312 } }
)
Deleting a document
You can call the delete
API to delete a document:
> client.delete(index: 'books', id: 'id') # Replace 'id' with a valid doc ID
Deleting an index
> client.indices.delete(index: 'books')