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https://github.com/toptal/chewy
High-level Elasticsearch Ruby framework based on the official elasticsearch-ruby client
https://github.com/toptal/chewy
elasticsearch elasticsearch-client ruby
Last synced: 6 days ago
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High-level Elasticsearch Ruby framework based on the official elasticsearch-ruby client
- Host: GitHub
- URL: https://github.com/toptal/chewy
- Owner: toptal
- License: mit
- Created: 2013-12-09T08:33:03.000Z (almost 11 years ago)
- Default Branch: master
- Last Pushed: 2024-10-08T18:54:39.000Z (26 days ago)
- Last Synced: 2024-10-19T01:22:39.476Z (16 days ago)
- Topics: elasticsearch, elasticsearch-client, ruby
- Language: Ruby
- Homepage:
- Size: 2.42 MB
- Stars: 1,887
- Watchers: 158
- Forks: 368
- Open Issues: 58
-
Metadata Files:
- Readme: README.md
- Changelog: CHANGELOG.md
- Contributing: CONTRIBUTING.md
- License: LICENSE.txt
- Code of conduct: CODE_OF_CONDUCT.md
- Codeowners: .github/CODEOWNERS
Awesome Lists containing this project
- awesome-ruby - chewy - High-level Elasticsearch Ruby framework based on the official elasticsearch-ruby client. (Search)
- awesome-rails-gem - Chewy - High-level Elasticsearch Ruby framework based on the official elasticsearch-ruby client. (Searching / Omniauth)
README
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# Chewy
Chewy is an ODM (Object Document Mapper), built on top of [the official Elasticsearch client](https://github.com/elastic/elasticsearch-ruby).
## Why Chewy?
In this section we'll cover why you might want to use Chewy instead of the official `elasticsearch-ruby` client gem.
* Every index is observable by all the related models.
Most of the indexed models are related to other and sometimes it is necessary to denormalize this related data and put at the same object. For example, you need to index an array of tags together with an article. Chewy allows you to specify an updateable index for every model separately - so corresponding articles will be reindexed on any tag update.
* Bulk import everywhere.
Chewy utilizes the bulk ES API for full reindexing or index updates. It also uses atomic updates. All the changed objects are collected inside the atomic block and the index is updated once at the end with all the collected objects. See `Chewy.strategy(:atomic)` for more details.
* Powerful querying DSL.
Chewy has an ActiveRecord-style query DSL. It is chainable, mergeable and lazy, so you can produce queries in the most efficient way. It also has object-oriented query and filter builders.
* Support for ActiveRecord.
## Installation
Add this line to your application's `Gemfile`:
gem 'chewy'
And then execute:
$ bundle
Or install it yourself as:
$ gem install chewy
## Compatibility
### Ruby
Chewy is compatible with MRI 3.0-3.3¹.
> ¹ Ruby 3 is supported with Rails 6.1, 7.0, 7.1 and 7.2
### Elasticsearch compatibility matrix
| Chewy version | Elasticsearch version |
| ------------- | ---------------------------------- |
| 8.0.0 | 8.x |
| 7.2.x | 7.x |
| 7.1.x | 7.x |
| 7.0.x | 6.8, 7.x |
| 6.0.0 | 5.x, 6.x |
| 5.x | 5.x, limited support for 1.x & 2.x |
**Important:** Chewy doesn't follow SemVer, so you should always
check the release notes before upgrading. The major version is linked to the
newest supported Elasticsearch and the minor version bumps may include breaking changes.
See our [migration guide](migration_guide.md) for detailed upgrade instructions between
various Chewy versions.
### Active Record
6.1, 7.0, 7.1, 7.2 Active Record versions are supported by Chewy.
## Getting Started
Chewy provides functionality for Elasticsearch index handling, documents import mappings, index update strategies and chainable query DSL.
### Minimal client setting
Create `config/initializers/chewy.rb` with this line:
```ruby
Chewy.settings = {host: 'localhost:9250'}
```
And run `rails g chewy:install` to generate `chewy.yml`:
```yaml
# config/chewy.yml
# separate environment configs
test:
host: 'localhost:9250'
prefix: 'test'
development:
host: 'localhost:9200'
```
### Elasticsearch
Make sure you have Elasticsearch up and running. You can [install](https://www.elastic.co/guide/en/elasticsearch/reference/current/install-elasticsearch.html) it locally, but the easiest way is to use [Docker](https://www.docker.com/get-started):
```shell
$ docker run --rm --name elasticsearch -p 9200:9200 -p 9300:9300 -e "discovery.type=single-node" -e "xpack.security.enabled=false" elasticsearch:8.15.0
```
### Security
Please note that starting from version 8 ElasticSearch has security features enabled by default.
Docker command above has it disabled for local testing convenience. If you want to enable it, omit
`"xpack.security.enabled=false"` part from Docker command, and run these command after starting container (container name `es8` assumed):
Reset password for `elastic` user:
```
docker container exec es8 '/usr/share/elasticsearch/bin/elasticsearch-reset-password' -u elastic
```
Extract CA certificate generated by ElasticSearch on first run:
```
docker container cp es8:/usr/share/elasticsearch/config/certs/http_ca.crt tmp/
```
And then add them to settings:
```yaml
# config/chewy.yml
development:
host: 'localhost:9200'
user: 'elastic'
password: 'SomeLongPassword'
transport_options:
ssl:
ca_file: './tmp/http_ca.crt'
```
### Index
Create `app/chewy/users_index.rb` with User Index:
```ruby
class UsersIndex < Chewy::Index
settings analysis: {
analyzer: {
email: {
tokenizer: 'keyword',
filter: ['lowercase']
}
}
}
index_scope User
field :first_name
field :last_name
field :email, analyzer: 'email'
end
```
### Model
Add User model, table and migrate it:
```shell
$ bundle exec rails g model User first_name last_name email
$ bundle exec rails db:migrate
```
Add `update_index` to app/models/user.rb:
```ruby
class User < ApplicationRecord
update_index('users') { self }
end
```
### Example of data request
1. Once a record is created (could be done via the Rails console), it creates User index too:
```
User.create(
first_name: "test1",
last_name: "test1",
email: '[email protected]',
# other fields
)
# UsersIndex Import (355.3ms) {:index=>1}
# => #
```
2. A query could be exposed at a given `UsersController`:
```ruby
def search
@users = UsersIndex.query(query_string: { fields: [:first_name, :last_name, :email, ...], query: search_params[:query], default_operator: 'and' })
render json: @users.to_json, status: :ok
end
private
def search_params
params.permit(:query, :page, :per)
end
```
3. So a request against `http://localhost:3000/users/[email protected]` issuing a response like:
```json
[
{
"attributes":{
"id":"1",
"first_name":"test1",
"last_name":"test1",
"email":"[email protected]",
...
"_score":0.9808291,
"_explanation":null
},
"_data":{
"_index":"users",
"_type":"_doc",
"_id":"1",
"_score":0.9808291,
"_source":{
"first_name":"test1",
"last_name":"test1",
"email":"[email protected]",
...
}
}
}
]
```
## Usage and configuration
### Client settings
To configure the Chewy client you need to add `chewy.rb` file with `Chewy.settings` hash:
```ruby
# config/initializers/chewy.rb
Chewy.settings = {host: 'localhost:9250'} # do not use environments
```
And add `chewy.yml` configuration file.
You can create `chewy.yml` manually or run `rails g chewy:install` to generate it:
```yaml
# config/chewy.yml
# separate environment configs
test:
host: 'localhost:9250'
prefix: 'test'
development:
host: 'localhost:9200'
```
The resulting config merges both hashes. Client options are passed as is to `Elasticsearch::Transport::Client` except for the `:prefix`, which is used internally by Chewy to create prefixed index names:
```ruby
Chewy.settings = {prefix: 'test'}
UsersIndex.index_name # => 'test_users'
```
The logger may be set explicitly:
```ruby
Chewy.logger = Logger.new(STDOUT)
```
See [config.rb](lib/chewy/config.rb) for more details.
#### AWS Elasticsearch
If you would like to use AWS's Elasticsearch using an IAM user policy, you will need to sign your requests for the `es:*` action by injecting the appropriate headers passing a proc to `transport_options`.
You'll need an additional gem for Faraday middleware: add `gem 'faraday_middleware-aws-sigv4'` to your Gemfile.
```ruby
require 'faraday_middleware/aws_sigv4'
Chewy.settings = {
host: 'http://my-es-instance-on-aws.us-east-1.es.amazonaws.com:80',
port: 80, # 443 for https host
transport_options: {
headers: { content_type: 'application/json' },
proc: -> (f) do
f.request :aws_sigv4,
service: 'es',
region: 'us-east-1',
access_key_id: ENV['AWS_ACCESS_KEY'],
secret_access_key: ENV['AWS_SECRET_ACCESS_KEY']
end
}
}
```
#### Index definition
1. Create `/app/chewy/users_index.rb`
```ruby
class UsersIndex < Chewy::Index
end
```
2. Define index scope (you can omit this part if you don't need to specify a scope (i.e. use PORO objects for import) or options)
```ruby
class UsersIndex < Chewy::Index
index_scope User.active # or just model instead_of scope: index_scope User
end
```
3. Add some mappings
```ruby
class UsersIndex < Chewy::Index
index_scope User.active.includes(:country, :badges, :projects)
field :first_name, :last_name # multiple fields without additional options
field :email, analyzer: 'email' # Elasticsearch-related options
field :country, value: ->(user) { user.country.name } # custom value proc
field :badges, value: ->(user) { user.badges.map(&:name) } # passing array values to index
field :projects do # the same block syntax for multi_field, if `:type` is specified
field :title
field :description # default data type is `text`
# additional top-level objects passed to value proc:
field :categories, value: ->(project, user) { project.categories.map(&:name) if user.active? }
end
field :rating, type: 'integer' # custom data type
field :created, type: 'date', include_in_all: false,
value: ->{ created_at } # value proc for source object context
end
```
[See here for mapping definitions](https://www.elastic.co/guide/en/elasticsearch/reference/current/mapping.html).
4. Add some index-related settings. Analyzer repositories might be used as well. See `Chewy::Index.settings` docs for details:
```ruby
class UsersIndex < Chewy::Index
settings analysis: {
analyzer: {
email: {
tokenizer: 'keyword',
filter: ['lowercase']
}
}
}
index_scope User.active.includes(:country, :badges, :projects)
root date_detection: false do
template 'about_translations.*', type: 'text', analyzer: 'standard'
field :first_name, :last_name
field :email, analyzer: 'email'
field :country, value: ->(user) { user.country.name }
field :badges, value: ->(user) { user.badges.map(&:name) }
field :projects do
field :title
field :description
end
field :about_translations, type: 'object' # pass object type explicitly if necessary
field :rating, type: 'integer'
field :created, type: 'date', include_in_all: false,
value: ->{ created_at }
end
end
```
[See index settings here](https://www.elastic.co/guide/en/elasticsearch/reference/current/indices-update-settings.html).
[See root object settings here](https://www.elastic.co/guide/en/elasticsearch/reference/current/dynamic-field-mapping.html).
See [mapping.rb](lib/chewy/index/mapping.rb) for more details.
5. Add model-observing code
```ruby
class User < ActiveRecord::Base
update_index('users') { self } # specifying index and back-reference
# for updating after user save or destroy
end
class Country < ActiveRecord::Base
has_many :users
update_index('users') { users } # return single object or collection
end
class Project < ActiveRecord::Base
update_index('users') { user if user.active? } # you can return even `nil` from the back-reference
end
class Book < ActiveRecord::Base
update_index(->(book) {"books_#{book.language}"}) { self } # dynamic index name with proc.
# For book with language == "en"
# this code will generate `books_en`
end
```
Also, you can use the second argument for method name passing:
```ruby
update_index('users', :self)
update_index('users', :users)
```
In the case of a belongs_to association you may need to update both associated objects, previous and current:
```ruby
class City < ActiveRecord::Base
belongs_to :country
update_index('cities') { self }
update_index 'countries' do
previous_changes['country_id'] || country
end
end
```
### Default import options
Every index has `default_import_options` configuration to specify, suddenly, default import options:
```ruby
class ProductsIndex < Chewy::Index
index_scope Post.includes(:tags)
default_import_options batch_size: 100, bulk_size: 10.megabytes, refresh: false
field :name
field :tags, value: -> { tags.map(&:name) }
end
```
See [import.rb](lib/chewy/index/import.rb) for available options.
### Multi (nested) and object field types
To define an objects field you can simply nest fields in the DSL:
```ruby
field :projects do
field :title
field :description
end
```
This will automatically set the type or root field to `object`. You may also specify `type: 'objects'` explicitly.
To define a multi field you have to specify any type except for `object` or `nested` in the root field:
```ruby
field :full_name, type: 'text', value: ->{ full_name.strip } do
field :ordered, analyzer: 'ordered'
field :untouched, type: 'keyword'
end
```
The `value:` option for internal fields will no longer be effective.
### Geo Point fields
You can use [Elasticsearch's geo mapping](https://www.elastic.co/guide/en/elasticsearch/reference/current/geo-point.html) with the `geo_point` field type, allowing you to query, filter and order by latitude and longitude. You can use the following hash format:
```ruby
field :coordinates, type: 'geo_point', value: ->{ {lat: latitude, lon: longitude} }
```
or by using nested fields:
```ruby
field :coordinates, type: 'geo_point' do
field :lat, value: ->{ latitude }
field :long, value: ->{ longitude }
end
```
See the section on *Script fields* for details on calculating distance in a search.
### Join fields
You can use a [join field](https://www.elastic.co/guide/en/elasticsearch/reference/current/parent-join.html)
to implement parent-child relationships between documents.
It [replaces the old `parent_id` based parent-child mapping](https://www.elastic.co/guide/en/elasticsearch/reference/current/removal-of-types.html#parent-child-mapping-types)
To use it, you need to pass `relations` and `join` (with `type` and `id`) options:
```ruby
field :hierarchy_link, type: :join, relations: {question: %i[answer comment], answer: :vote, vote: :subvote}, join: {type: :comment_type, id: :commented_id}
```
assuming you have `comment_type` and `commented_id` fields in your model.
Note that when you reindex a parent, its children and grandchildren will be reindexed as well.
This may require additional queries to the primary database and to elastisearch.
Also note that the join field doesn't support crutches (it should be a field directly defined on the model).
### Crutches™ technology
Assume you are defining your index like this (product has_many categories through product_categories):
```ruby
class ProductsIndex < Chewy::Index
index_scope Product.includes(:categories)
field :name
field :category_names, value: ->(product) { product.categories.map(&:name) } # or shorter just -> { categories.map(&:name) }
end
```
Then the Chewy reindexing flow will look like the following pseudo-code:
```ruby
Product.includes(:categories).find_in_batches(1000) do |batch|
bulk_body = batch.map do |object|
{name: object.name, category_names: object.categories.map(&:name)}.to_json
end
# here we are sending every batch of data to ES
Chewy.client.bulk bulk_body
end
```
If you meet complicated cases when associations are not applicable you can replace Rails associations with Chewy Crutches™ technology:
```ruby
class ProductsIndex < Chewy::Index
index_scope Product
crutch :categories do |collection| # collection here is a current batch of products
# data is fetched with a lightweight query without objects initialization
data = ProductCategory.joins(:category).where(product_id: collection.map(&:id)).pluck(:product_id, 'categories.name')
# then we have to convert fetched data to appropriate format
# this will return our data in structure like:
# {123 => ['sweets', 'juices'], 456 => ['meat']}
data.each.with_object({}) { |(id, name), result| (result[id] ||= []).push(name) }
end
field :name
# simply use crutch-fetched data as a value:
field :category_names, value: ->(product, crutches) { crutches[:categories][product.id] }
end
```
An example flow will look like this:
```ruby
Product.includes(:categories).find_in_batches(1000) do |batch|
crutches[:categories] = ProductCategory.joins(:category).where(product_id: batch.map(&:id)).pluck(:product_id, 'categories.name')
.each.with_object({}) { |(id, name), result| (result[id] ||= []).push(name) }
bulk_body = batch.map do |object|
{name: object.name, category_names: crutches[:categories][object.id]}.to_json
end
Chewy.client.bulk bulk_body
end
```
So Chewy Crutches™ technology is able to increase your indexing performance in some cases up to a hundredfold or even more depending on your associations complexity.
### Witchcraft™ technology
One more experimental technology to increase import performance. As far as you know, chewy defines value proc for every imported field in mapping, so at the import time each of these procs is executed on imported object to extract result document to import. It would be great for performance to use one huge whole-document-returning proc instead. So basically the idea or Witchcraft™ technology is to compile a single document-returning proc from the index definition.
```ruby
index_scope Product
witchcraft!
field :title
field :tags, value: -> { tags.map(&:name) }
field :categories do
field :name, value: -> (product, category) { category.name }
field :type, value: -> (product, category, crutch) { crutch.types[category.name] }
end
```
The index definition above will be compiled to something close to:
```ruby
-> (object, crutches) do
{
title: object.title,
tags: object.tags.map(&:name),
categories: object.categories.map do |object2|
{
name: object2.name
type: crutches.types[object2.name]
}
end
}
end
```
And don't even ask how is it possible, it is a witchcraft.
Obviously not every type of definition might be compiled. There are some restrictions:
1. Use reasonable formatting to make `method_source` be able to extract field value proc sources.
2. Value procs with splat arguments are not supported right now.
3. If you are generating fields dynamically use value proc with arguments, argumentless value procs are not supported yet:
```ruby
[:first_name, :last_name].each do |name|
field name, value: -> (o) { o.send(name) }
end
```
However, it is quite possible that your index definition will be supported by Witchcraft™ technology out of the box in most of the cases.
### Raw Import
Another way to speed up import time is Raw Imports. This technology is only available in ActiveRecord adapter. Very often, ActiveRecord model instantiation is what consumes most of the CPU and RAM resources. Precious time is wasted on converting, say, timestamps from strings and then serializing them back to strings. Chewy can operate on raw hashes of data directly obtained from the database. All you need is to provide a way to convert that hash to a lightweight object that mimics the behaviour of the normal ActiveRecord object.
```ruby
class LightweightProduct
def initialize(attributes)
@attributes = attributes
end
# Depending on the database, `created_at` might
# be in different formats. In PostgreSQL, for example,
# you might see the following format:
# "2016-03-22 16:23:22"
#
# Taking into account that Elastic expects something different,
# one might do something like the following, just to avoid
# unnecessary String -> DateTime -> String conversion.
#
# "2016-03-22 16:23:22" -> "2016-03-22T16:23:22Z"
def created_at
@attributes['created_at'].tr(' ', 'T') << 'Z'
end
end
index_scope Product
default_import_options raw_import: ->(hash) {
LightweightProduct.new(hash)
}
field :created_at, 'datetime'
```
Also, you can pass `:raw_import` option to the `import` method explicitly.
### Index creation during import
By default, when you perform import Chewy checks whether an index exists and creates it if it's absent.
You can turn off this feature to decrease Elasticsearch hits count.
To do so you need to set `skip_index_creation_on_import` parameter to `false` in your `config/chewy.yml`
### Skip record fields during import
You can use `ignore_blank: true` to skip fields that return `true` for the `.blank?` method:
```ruby
index_scope Country
field :id
field :cities, ignore_blank: true do
field :id
field :name
field :surname, ignore_blank: true
field :description
end
```
#### Default values for different types
By default `ignore_blank` is false on every type except `geo_point`.
### Journaling
You can record all actions that were made to the separate journal index in ElasticSearch.
When you create/update/destroy your documents, it will be saved in this special index.
If you make something with a batch of documents (e.g. during index reset) it will be saved as a one record, including primary keys of each document that was affected.
Common journal record looks like this:
```json
{
"action": "index",
"object_id": [1, 2, 3],
"index_name": "...",
"created_at": ""
}
```
This feature is turned off by default.
But you can turn it on by setting `journal` setting to `true` in `config/chewy.yml`.
Also, you can specify journal index name. For example:
```yaml
# config/chewy.yml
production:
journal: true
journal_name: my_super_journal
```
Also, you can provide this option while you're importing some index:
```ruby
CityIndex.import journal: true
```
Or as a default import option for an index:
```ruby
class CityIndex
index_scope City
default_import_options journal: true
end
```
You may be wondering why do you need it? The answer is simple: not to lose the data.
Imagine that you reset your index in a zero-downtime manner (to separate index), and in the meantime somebody keeps updating the data frequently (to old index). So all these actions will be written to the journal index and you'll be able to apply them after index reset using the `Chewy::Journal` interface.
When enabled, journal can grow to enormous size, consider setting up cron job that would clean it occasionally using [`chewy:journal:clean` rake task](#chewyjournal).
### Index manipulation
```ruby
UsersIndex.delete # destroy index if it exists
UsersIndex.delete!
UsersIndex.create
UsersIndex.create! # use bang or non-bang methods
UsersIndex.purge
UsersIndex.purge! # deletes then creates index
UsersIndex.import # import with 0 arguments process all the data specified in index_scope definition
UsersIndex.import User.where('rating > 100') # or import specified users scope
UsersIndex.import User.where('rating > 100').to_a # or import specified users array
UsersIndex.import [1, 2, 42] # pass even ids for import, it will be handled in the most effective way
UsersIndex.import User.where('rating > 100'), update_fields: [:email] # if update fields are specified - it will update their values only with the `update` bulk action
UsersIndex.import! # raises an exception in case of any import errors
UsersIndex.reset! # purges index and imports default data for all types
```
If the passed user is `#destroyed?`, or satisfies a `delete_if` index_scope option, or the specified id does not exist in the database, import will perform delete from index action for this object.
```ruby
index_scope User, delete_if: :deleted_at
index_scope User, delete_if: -> { deleted_at }
index_scope User, delete_if: ->(user) { user.deleted_at }
```
See [actions.rb](lib/chewy/index/actions.rb) for more details.
### Index update strategies
Assume you've got the following code:
```ruby
class City < ActiveRecord::Base
update_index 'cities', :self
end
class CitiesIndex < Chewy::Index
index_scope City
field :name
end
```
If you do something like `City.first.save!` you'll get an UndefinedUpdateStrategy exception instead of the object saving and index updating. This exception forces you to choose an appropriate update strategy for the current context.
If you want to return to the pre-0.7.0 behavior - just set `Chewy.root_strategy = :bypass`.
#### `:atomic`
The main strategy here is `:atomic`. Assume you have to update a lot of records in the db.
```ruby
Chewy.strategy(:atomic) do
City.popular.map(&:do_some_update_action!)
end
```
Using this strategy delays the index update request until the end of the block. Updated records are aggregated and the index update happens with the bulk API. So this strategy is highly optimized.
#### `:sidekiq`
This does the same thing as `:atomic`, but asynchronously using sidekiq. Patch `Chewy::Strategy::Sidekiq::Worker` for index updates improving.
```ruby
Chewy.strategy(:sidekiq) do
City.popular.map(&:do_some_update_action!)
end
```
The default queue name is `chewy`, you can customize it in settings: `sidekiq.queue_name`
```
Chewy.settings[:sidekiq] = {queue: :low}
```
#### `:lazy_sidekiq`
This does the same thing as `:sidekiq`, but with lazy evaluation. Beware it does not allow you to use any non-persistent record state for indices and conditions because record will be re-fetched from database asynchronously using sidekiq. However for destroying records strategy will fallback to `:sidekiq` because it's not possible to re-fetch deleted records from database.
The purpose of this strategy is to improve the response time of the code that should update indexes, as it does not only defer actual ES calls to a background job but `update_index` callbacks evaluation (for created and updated objects) too. Similar to `:sidekiq`, index update is asynchronous so this strategy cannot be used when data and index synchronization is required.
```ruby
Chewy.strategy(:lazy_sidekiq) do
City.popular.map(&:do_some_update_action!)
end
```
The default queue name is `chewy`, you can customize it in settings: `sidekiq.queue_name`
```
Chewy.settings[:sidekiq] = {queue: :low}
```
#### `:delayed_sidekiq`
It accumulates IDs of records to be reindexed during the latency window in Redis and then performs the reindexing of all accumulated records at once.
This strategy is very useful in the case of frequently mutated records.
It supports the `update_fields` option, so it will attempt to select just enough data from the database.
Keep in mind, this strategy does not guarantee reindexing in the event of Sidekiq worker termination or an error during the reindexing phase.
This behavior is intentional to prevent continuous growth of Redis db.
There are three options that can be defined in the index:
```ruby
class CitiesIndex...
strategy_config delayed_sidekiq: {
latency: 3,
margin: 2,
ttl: 60 * 60 * 24,
reindex_wrapper: ->(&reindex) {
ActiveRecord::Base.connected_to(role: :reading) { reindex.call }
}
# latency - will prevent scheduling identical jobs
# margin - main purpose is to cover db replication lag by the margin
# ttl - a chunk expiration time (in seconds)
# reindex_wrapper - lambda that accepts block to wrap that reindex process AR connection block.
}
...
end
```
Also you can define defaults in the `initializers/chewy.rb`
```ruby
Chewy.settings = {
strategy_config: {
delayed_sidekiq: {
latency: 3,
margin: 2,
ttl: 60 * 60 * 24,
reindex_wrapper: ->(&reindex) {
ActiveRecord::Base.connected_to(role: :reading) { reindex.call }
}
}
}
}
```
or in `config/chewy.yml`
```ruby
strategy_config:
delayed_sidekiq:
latency: 3
margin: 2
ttl: <%= 60 * 60 * 24 %>
# reindex_wrapper setting is not possible here!!! use the initializer instead
```
You can use the strategy identically to other strategies
```ruby
Chewy.strategy(:delayed_sidekiq) do
City.popular.map(&:do_some_update_action!)
end
```
The default queue name is `chewy`, you can customize it in settings: `sidekiq.queue_name`
```
Chewy.settings[:sidekiq] = {queue: :low}
```
Explicit call of the reindex using `:delayed_sidekiq strategy`
```ruby
CitiesIndex.import([1, 2, 3], strategy: :delayed_sidekiq)
```
Explicit call of the reindex using `:delayed_sidekiq` strategy with `:update_fields` support
```ruby
CitiesIndex.import([1, 2, 3], update_fields: [:name], strategy: :delayed_sidekiq)
```
While running tests with delayed_sidekiq strategy and Sidekiq is using a real redis instance that is NOT cleaned up in between tests (via e.g. `Sidekiq.redis(&:flushdb)`), you'll want to cleanup some redis keys in between tests to avoid state leaking and flaky tests. Chewy provides a convenience method for that:
```ruby
# it might be a good idea to also add to your testing setup, e.g.: a rspec `before` hook
Chewy::Strategy::DelayedSidekiq.clear_timechunks!
```
#### `:active_job`
This does the same thing as `:atomic`, but using ActiveJob. This will inherit the ActiveJob configuration settings including the `active_job.queue_adapter` setting for the environment. Patch `Chewy::Strategy::ActiveJob::Worker` for index updates improving.
```ruby
Chewy.strategy(:active_job) do
City.popular.map(&:do_some_update_action!)
end
```
The default queue name is `chewy`, you can customize it in settings: `active_job.queue_name`
```
Chewy.settings[:active_job] = {queue: :low}
```
#### `:urgent`
The following strategy is convenient if you are going to update documents in your index one by one.
```ruby
Chewy.strategy(:urgent) do
City.popular.map(&:do_some_update_action!)
end
```
This code will perform `City.popular.count` requests for ES documents update.
It is convenient for use in e.g. the Rails console with non-block notation:
```ruby
> Chewy.strategy(:urgent)
> City.popular.map(&:do_some_update_action!)
```
#### `:bypass`
When the bypass strategy is active the index will not be automatically updated on object save.
For example, on `City.first.save!` the cities index would not be updated.
#### Nesting
Strategies are designed to allow nesting, so it is possible to redefine it for nested contexts.
```ruby
Chewy.strategy(:atomic) do
city1.do_update!
Chewy.strategy(:urgent) do
city2.do_update!
city3.do_update!
# there will be 2 update index requests for city2 and city3
end
city4..do_update!
# city1 and city4 will be grouped in one index update request
end
```
#### Non-block notation
It is possible to nest strategies without blocks:
```ruby
Chewy.strategy(:urgent)
city1.do_update! # index updated
Chewy.strategy(:bypass)
city2.do_update! # update bypassed
Chewy.strategy.pop
city3.do_update! # index updated again
```
#### Designing your own strategies
See [strategy/base.rb](lib/chewy/strategy/base.rb) for more details. See [strategy/atomic.rb](lib/chewy/strategy/atomic.rb) for an example.
### Rails application strategies integration
There are a couple of predefined strategies for your Rails application. Initially, the Rails console uses the `:urgent` strategy by default, except in the sandbox case. When you are running sandbox it switches to the `:bypass` strategy to avoid polluting the index.
Migrations are wrapped with the `:bypass` strategy. Because the main behavior implies that indices are reset after migration, there is no need for extra index updates. Also indexing might be broken during migrations because of the outdated schema.
Controller actions are wrapped with the configurable value of `Chewy.request_strategy` and defaults to `:atomic`. This is done at the middleware level to reduce the number of index update requests inside actions.
It is also a good idea to set up the `:bypass` strategy inside your test suite and import objects manually only when needed, and use `Chewy.massacre` when needed to flush test ES indices before every example. This will allow you to minimize unnecessary ES requests and reduce overhead.
Deprecation note: since version 8 wildcard removing of indices is disabled by default. You can enable it for a cluster with setting `action.destructive_requires_name` to false.
```ruby
RSpec.configure do |config|
config.before(:suite) do
Chewy.strategy(:bypass)
end
end
```
### Elasticsearch client options
All connection options, except the `:prefix`, are passed to the `Elasticseach::Client.new` ([chewy/lib/chewy.rb](https://github.com/toptal/chewy/blob/f5bad9f83c21416ac10590f6f34009c645062e89/lib/chewy.rb#L153-L160)):
Here's the relevant Elasticsearch documentation on the subject: https://rubydoc.info/gems/elasticsearch-transport#setting-hosts
### `ActiveSupport::Notifications` support
Chewy has notifying the following events:
#### `search_query.chewy` payload
* `payload[:index]`: requested index class
* `payload[:request]`: request hash
#### `import_objects.chewy` payload
* `payload[:index]`: currently imported index name
* `payload[:import]`: imports stats, total imported and deleted objects count:
```ruby
{index: 30, delete: 5}
```
* `payload[:errors]`: might not exist. Contains grouped errors with objects ids list:
```ruby
{index: {
'error 1 text' => ['1', '2', '3'],
'error 2 text' => ['4']
}, delete: {
'delete error text' => ['10', '12']
}}
```
### NewRelic integration
To integrate with NewRelic you may use the following example source (config/initializers/chewy.rb):
```ruby
require 'new_relic/agent/instrumentation/evented_subscriber'
class ChewySubscriber < NewRelic::Agent::Instrumentation::EventedSubscriber
def start(name, id, payload)
event = ChewyEvent.new(name, Time.current, nil, id, payload)
push_event(event)
end
def finish(_name, id, _payload)
pop_event(id).finish
end
class ChewyEvent < NewRelic::Agent::Instrumentation::Event
OPERATIONS = {
'import_objects.chewy' => 'import',
'search_query.chewy' => 'search',
'delete_query.chewy' => 'delete'
}.freeze
def initialize(*args)
super
@segment = start_segment
end
def start_segment
segment = NewRelic::Agent::Transaction::DatastoreSegment.new product, operation, collection, host, port
if (txn = state.current_transaction)
segment.transaction = txn
end
segment.notice_sql @payload[:request].to_s
segment.start
segment
end
def finish
if (txn = state.current_transaction)
txn.add_segment @segment
end
@segment.finish
end
private
def state
@state ||= NewRelic::Agent::TransactionState.tl_get
end
def product
'Elasticsearch'
end
def operation
OPERATIONS[name]
end
def collection
payload.values_at(:type, :index)
.reject { |value| value.try(:empty?) }
.first
.to_s
end
def host
Chewy.client.transport.hosts.first[:host]
end
def port
Chewy.client.transport.hosts.first[:port]
end
end
end
ActiveSupport::Notifications.subscribe(/.chewy$/, ChewySubscriber.new)
```
### Search requests
Quick introduction.
#### Composing requests
The request DSL have the same chainable nature as AR. The main class is `Chewy::Search::Request`.
```ruby
CitiesIndex.query(match: {name: 'London'})
```
Main methods of the request DSL are: `query`, `filter` and `post_filter`, it is possible to pass pure query hashes or use `elasticsearch-dsl`.
```ruby
CitiesIndex
.filter(term: {name: 'Bangkok'})
.query(match: {name: 'London'})
.query.not(range: {population: {gt: 1_000_000}})
```
You can query a set of indexes at once:
```ruby
CitiesIndex.indices(CountriesIndex).query(match: {name: 'Some'})
```
See https://www.elastic.co/guide/en/elasticsearch/reference/current/query-dsl.html and https://github.com/elastic/elasticsearch-dsl-ruby for more details.
An important part of requests manipulation is merging. There are 4 methods to perform it: `merge`, `and`, `or`, `not`. See [Chewy::Search::QueryProxy](lib/chewy/search/query_proxy.rb) for details. Also, `only` and `except` methods help to remove unneeded parts of the request.
Every other request part is covered by a bunch of additional methods, see [Chewy::Search::Request](lib/chewy/search/request.rb) for details:
```ruby
CitiesIndex.limit(10).offset(30).order(:name, {population: {order: :desc}})
```
Request DSL also provides additional scope actions, like `delete_all`, `exists?`, `count`, `pluck`, etc.
#### Pagination
The request DSL supports pagination with `Kaminari`. An extension is enabled on initialization if `Kaminari` is available. See [Chewy::Search](lib/chewy/search.rb) and [Chewy::Search::Pagination::Kaminari](lib/chewy/search/pagination/kaminari.rb) for details.
#### Named scopes
Chewy supports named scopes functionality. There is no specialized DSL for named scopes definition, it is simply about defining class methods.
See [Chewy::Search::Scoping](lib/chewy/search/scoping.rb) for details.
#### Scroll API
ElasticSearch scroll API is utilized by a bunch of methods: `scroll_batches`, `scroll_hits`, `scroll_wrappers` and `scroll_objects`.
See [Chewy::Search::Scrolling](lib/chewy/search/scrolling.rb) for details.
#### Loading objects
It is possible to load ORM/ODM source objects with the `objects` method. To provide additional loading options use `load` method:
```ruby
CitiesIndex.load(scope: -> { active }).to_a # to_a returns `Chewy::Index` wrappers.
CitiesIndex.load(scope: -> { active }).objects # An array of AR source objects.
```
See [Chewy::Search::Loader](lib/chewy/search/loader.rb) for more details.
In case when it is necessary to iterate through both of the wrappers and objects simultaneously, `object_hash` method helps a lot:
```ruby
scope = CitiesIndex.load(scope: -> { active })
scope.each do |wrapper|
scope.object_hash[wrapper]
end
```
### Rake tasks
For a Rails application, some index-maintaining rake tasks are defined.
#### `chewy:reset`
Performs zero-downtime reindexing as described [here](https://www.elastic.co/blog/changing-mapping-with-zero-downtime). So the rake task creates a new index with unique suffix and then simply aliases it to the common index name. The previous index is deleted afterwards (see `Chewy::Index.reset!` for more details).
```bash
rake chewy:reset # resets all the existing indices
rake chewy:reset[users] # resets UsersIndex only
rake chewy:reset[users,cities] # resets UsersIndex and CitiesIndex
rake chewy:reset[-users,cities] # resets every index in the application except specified ones
```
#### `chewy:upgrade`
Performs reset exactly the same way as `chewy:reset` does, but only when the index specification (setting or mapping) was changed.
It works only when index specification is locked in `Chewy::Stash::Specification` index. The first run will reset all indexes and lock their specifications.
See [Chewy::Stash::Specification](lib/chewy/stash.rb) and [Chewy::Index::Specification](lib/chewy/index/specification.rb) for more details.
```bash
rake chewy:upgrade # upgrades all the existing indices
rake chewy:upgrade[users] # upgrades UsersIndex only
rake chewy:upgrade[users,cities] # upgrades UsersIndex and CitiesIndex
rake chewy:upgrade[-users,cities] # upgrades every index in the application except specified ones
```
#### `chewy:update`
It doesn't create indexes, it simply imports everything to the existing ones and fails if the index was not created before.
```bash
rake chewy:update # updates all the existing indices
rake chewy:update[users] # updates UsersIndex only
rake chewy:update[users,cities] # updates UsersIndex and CitiesIndex
rake chewy:update[-users,cities] # updates every index in the application except UsersIndex and CitiesIndex
```
#### `chewy:sync`
Provides a way to synchronize outdated indexes with the source quickly and without doing a full reset. By default field `updated_at` is used to find outdated records, but this could be customized by `outdated_sync_field` as described at [Chewy::Index::Syncer](lib/chewy/index/syncer.rb).
Arguments are similar to the ones taken by `chewy:update` task.
See [Chewy::Index::Syncer](lib/chewy/index/syncer.rb) for more details.
```bash
rake chewy:sync # synchronizes all the existing indices
rake chewy:sync[users] # synchronizes UsersIndex only
rake chewy:sync[users,cities] # synchronizes UsersIndex and CitiesIndex
rake chewy:sync[-users,cities] # synchronizes every index in the application except except UsersIndex and CitiesIndex
```
#### `chewy:deploy`
This rake task is especially useful during the production deploy. It is a combination of `chewy:upgrade` and `chewy:sync` and the latter is called only for the indexes that were not reset during the first stage.
It is not possible to specify any particular indexes for this task as it doesn't make much sense.
Right now the approach is that if some data had been updated, but index definition was not changed (no changes satisfying the synchronization algorithm were done), it would be much faster to perform manual partial index update inside data migrations or even manually after the deploy.
Also, there is always full reset alternative with `rake chewy:reset`.
#### `chewy:create_missing_indexes`
This rake task creates newly defined indexes in ElasticSearch and skips existing ones. Useful for production-like environments.
#### Parallelizing rake tasks
Every task described above has its own parallel version. Every parallel rake task takes the number for processes for execution as the first argument and the rest of the arguments are exactly the same as for the non-parallel task version.
[https://github.com/grosser/parallel](https://github.com/grosser/parallel) gem is required to use these tasks.
If the number of processes is not specified explicitly - `parallel` gem tries to automatically derive the number of processes to use.
```bash
rake chewy:parallel:reset
rake chewy:parallel:upgrade[4]
rake chewy:parallel:update[4,cities]
rake chewy:parallel:sync[4,-users]
rake chewy:parallel:deploy[4] # performs parallel upgrade and parallel sync afterwards
```
#### `chewy:journal`
This namespace contains two tasks for the journal manipulations: `chewy:journal:apply` and `chewy:journal:clean`. Both are taking time as the first argument (optional for clean) and a list of indexes exactly as the tasks above. Time can be in any format parsable by ActiveSupport.
```bash
rake chewy:journal:apply["$(date -v-1H -u +%FT%TZ)"] # apply journaled changes for the past hour
rake chewy:journal:apply["$(date -v-1H -u +%FT%TZ)",users] # apply journaled changes for the past hour on UsersIndex only
```
When the size of the journal becomes very large, the classical way of deletion would be obstructive and resource consuming. Fortunately, Chewy internally uses [delete-by-query](https://www.elastic.co/guide/en/elasticsearch/reference/7.17/docs-delete-by-query.html#docs-delete-by-query-task-api) ES function which supports async execution with batching and [throttling](https://www.elastic.co/guide/en/elasticsearch/reference/current/docs-delete-by-query.html#docs-delete-by-query-throttle).
The available options, which can be set by ENV variables, are listed below:
* `WAIT_FOR_COMPLETION` - a boolean flag. It controls async execution. It waits by default. When set to `false` (`0`, `f`, `false` or `off` in any case spelling is accepted as `false`), Elasticsearch performs some preflight checks, launches the request, and returns a task reference you can use to cancel the task or get its status.
* `REQUESTS_PER_SECOND` - float. The throttle for this request in sub-requests per second. No throttling is enforced by default.
* `SCROLL_SIZE` - integer. The number of documents to be deleted in single sub-request. The default batch size is 1000.
```bash
rake chewy:journal:clean WAIT_FOR_COMPLETION=false REQUESTS_PER_SECOND=10 SCROLL_SIZE=5000
```
### RSpec integration
Just add `require 'chewy/rspec'` to your spec_helper.rb and you will get additional features:
[update_index](lib/chewy/rspec/update_index.rb) helper
`mock_elasticsearch_response` helper to mock elasticsearch response
`mock_elasticsearch_response_sources` helper to mock elasticsearch response sources
`build_query` matcher to compare request and expected query (returns `true`/`false`)
To use `mock_elasticsearch_response` and `mock_elasticsearch_response_sources` helpers add `include Chewy::Rspec::Helpers` to your tests.
See [chewy/rspec/](lib/chewy/rspec/) for more details.
### Minitest integration
Add `require 'chewy/minitest'` to your test_helper.rb, and then for tests which you'd like indexing test hooks, `include Chewy::Minitest::Helpers`.
Since you can set `:bypass` strategy for test suites and manually handle import for the index and manually flush test indices using `Chewy.massacre`. This will help reduce unnecessary ES requests
But if you require chewy to index/update model regularly in your test suite then you can specify `:urgent` strategy for documents indexing. Add `Chewy.strategy(:urgent)` to test_helper.rb.
Also, you can use additional helpers:
`mock_elasticsearch_response` to mock elasticsearch response
`mock_elasticsearch_response_sources` to mock elasticsearch response sources
`assert_elasticsearch_query` to compare request and expected query (returns `true`/`false`)
See [chewy/minitest/](lib/chewy/minitest/) for more details.
### DatabaseCleaner
If you use `DatabaseCleaner` in your tests with [the `transaction` strategy](https://github.com/DatabaseCleaner/database_cleaner#how-to-use), you may run into the problem that `ActiveRecord`'s models are not indexed automatically on save despite the fact that you set the callbacks to do this with the `update_index` method. The issue arises because `chewy` indices data on `after_commit` run as default, but all `after_commit` callbacks are not run with the `DatabaseCleaner`'s' `transaction` strategy. You can solve this issue by changing the `Chewy.use_after_commit_callbacks` option. Just add the following initializer in your Rails application:
```ruby
#config/initializers/chewy.rb
Chewy.use_after_commit_callbacks = !Rails.env.test?
```
### Pre-request Filter
Should you need to inspect the query prior to it being dispatched to ElasticSearch during any queries, you can use the `before_es_request_filter`. `before_es_request_filter` is a callable object, as demonstrated below:
```ruby
Chewy.before_es_request_filter = -> (method_name, args, kw_args) { ... }
```
While using the `before_es_request_filter`, please consider the following:
* `before_es_request_filter` acts as a simple proxy before any request made via the `ElasticSearch::Client`. The arguments passed to this filter include:
* `method_name` - The name of the method being called. Examples are search, count, bulk and etc.
* `args` and `kw_args` - These are the positional arguments provided in the method call.
* The operation is synchronous, so avoid executing any heavy or time-consuming operations within the filter to prevent performance degradation.
* The return value of the proc is disregarded. This filter is intended for inspection or modification of the query rather than generating a response.
* Any exception raised inside the callback will propagate upward and halt the execution of the query. It is essential to handle potential errors adequately to ensure the stability of your search functionality.
### Import scope clean-up behavior
Whenever you set the `import_scope` for the index, in the case of ActiveRecord,
options for order, offset and limit will be removed. You can set the behavior of
chewy, before the clean-up itself.
The default behavior is a warning sent to the Chewy logger (`:warn`). Another more
restrictive option is raising an exception (`:raise`). Both options have a
negative impact on performance since verifying whether the code uses any of
these options requires building AREL query.
To avoid the loading time impact, you can ignore the check (`:ignore`) before
the clean-up.
```
Chewy.import_scope_cleanup_behavior = :ignore
```
## Contributing
1. Fork it (http://github.com/toptal/chewy/fork)
2. Create your feature branch (`git checkout -b my-new-feature`)
3. Implement your changes, cover it with specs and make sure old specs are passing
4. Commit your changes (`git commit -am 'Add some feature'`)
5. Push to the branch (`git push origin my-new-feature`)
6. Create new Pull Request
Use the following Rake tasks to control the Elasticsearch cluster while developing, if you prefer native Elasticsearch installation over the dockerized one:
```bash
rake elasticsearch:start # start Elasticsearch cluster on 9250 port for tests
rake elasticsearch:stop # stop Elasticsearch
```
## Copyright
Copyright (c) 2013-2021 Toptal, LLC. See [LICENSE.txt](LICENSE.txt) for
further details.