Awesome

RediSearch

A simple, but powerful, Ruby wrapper around RediSearch, a search engine on top of Redis.

Installation

Firstly, Redis and RediSearch need to be installed.

You can download Redis from https://redis.io/download, and check out installation instructions here. Alternatively, on macOS or Linux you can install via Homebrew.

To install RediSearch check out, https://oss.redislabs.com/redisearch/Quick_Start.html. Once you have RediSearch built, if you are not using Docker, you can update your redis.conf file to always load the RediSearch module with loadmodule /path/to/redisearch.so. (On macOS the redis.conf file can be found at /usr/local/etc/redis.conf)

After Redis and RediSearch are up and running, add the following line to your Gemfile:

gem 'redi_search'

And then:

❯ bundle

Or install it yourself:

❯ gem install redi_search

and require it:

require 'redi_search'

Once the gem is installed and required you'll need to configure it with your Redis configuration. If you're on Rails, this should go in an initializer (config/initializers/redi_search.rb).

RediSearch.configure do |config|
  config.redis_config = {
    host: "127.0.0.1",
    port: "6379"
  }
end

Table of Contents

• Preface
• Schema
• Document
• Index
• Searching
• Spellcheck
• Rails Integration

Preface

RediSearch revolves around a search index, so lets start with defining what a search index is. According to Swiftype:

A search index is a body of structured data that a search engine refers to when looking for results that are relevant to a specific query. Indexes are a critical piece of any search system, since they must be tailored to the specific information retrieval method of the search engine’s algorithm. In this manner, the algorithm and the index are inextricably linked to one another. Index can also be used as a verb (indexing), referring to the process of collecting unstructured website data in a structured format that is tailored for the search engine algorithm.

One way to think about indices is to consider the following analogy between a search infrastructure and an office filing system. Imagine you hand an intern a stack of thousands of pieces of paper (documents) and tell them to organize these pieces of paper in a filing cabinet (index) to help the company find information more efficiently. The intern will first have to sort through the papers and get a sense of all the information contained within them, then they will have to decide on a system for arranging them in the filing cabinet, then finally they’ll need to decide what is the most effective manner for searching through and selecting from the files once they are in the cabinet. In this example, the process of organizing and filing the papers corresponds to the process of indexing website content, and the method for searching across these organized files and finding those that are most relevant corresponds to the search algorithm.

Schema

This defines the fields and the properties of those fields in the index. A schema is a simple DSL. Each field can be one of four types: geo, numeric, tag, or text and can have many options. A simple example of a schema is:

RediSearch::Schema.new do
  text_field :first_name
  text_field :last_name
end

The supported options for each type are as follows:

Text field

With no options: text_field :name

Numeric field

With no options: numeric_field :price

Tag field

With no options: tag_field :tag

Geo field

With no options: geo_field :place

Document

A Document is the Ruby representation of a Redis hash.

You can fetch a Document using .get class methods.

• get(index, document_id) fetches a single Document in an Index for a given document_id.

You can also make a Document instance using the .for_object(index, record, only: []) class method. It takes an Index instance and a Ruby object. That object must respond to all the fields specified in the Index's Schema. only accepts an array of fields from the schema and limits the fields that are passed to the Document.

Once you have an instance of a Document, it responds to all the fields specified in the Index's Schema as methods and document_id. document_id is automatically prepended with the Index's names unless it already is to ensure uniqueness. We prepend the Index name because if you have two Documents with the same id in different Indexs we don't want the Documents to override each other. There is also a #document_id_without_index method which removes the prepended index name.

Finally there is a #del method that will remove the Document from the Index.

Index

To initialize an Index, pass the name of the Index as a string or symbol and the Schema block.

RediSearch::Index.new(name_of_index) do
  text_field :foobar
end

Available Commands

• create
  • Creates the index in the Redis instance, returns a boolean. Has an accompanying bang method that will raise an exception upon failure. Will return false if the index already exists. Accepts a few options:
    • max_text_fields: #{true || false}
      • For efficiency, RediSearch encodes indexes differently if they are created with less than 32 text fields. This option forces RediSearch to encode indexes as if there were more than 32 text fields, which allows you to add additional fields (beyond 32) using add_field.
    • no_offsets: #{true || false}
      • If set, we do not store term offsets for documents (saves memory, does not allow exact searches or highlighting). Implies no_highlight.
    • temporary: #{seconds}
      • Create a lightweight temporary index which will expire after seconds seconds of inactivity. The internal idle timer is reset whenever the index is searched or added to. Because such indexes are lightweight, you can create thousands of such indexes without negative performance implications.
    • no_highlight: #{true || false}
      • Conserves storage space and memory by disabling highlighting support. If set, we do not store corresponding byte offsets for term positions. no_highlight is also implied by no_offsets.
    • no_fields: #{true || false}
      • If set, we do not store field bits for each term. Saves memory, does not allow filtering by specific fields.
    • no_frequencies: #{true || false}
      • If set, we avoid saving the term frequencies in the index. This saves memory but does not allow sorting based on the frequencies of a given term within the document.
• drop(keep_docs: false)
  • Drops the Index from the Redis instance, returns a boolean. Has an accompanying bang method that will raise an exception upon failure. Will return false if the Index has already been dropped. Takes an option keyword arg, keep_docs, that will by default remove all the document hashes in Redis.
• exist?
  • Returns a boolean signifying Index existence.
• info
  • Returns a struct object with all the information about the Index.
• fields
  • Returns an array of the field names in the Index.
• add(document)
  • Takes a Document object. Has an accompanying bang method that will raise an exception upon failure.
• add_multiple(documents)
  • Takes an array of Document objects. This provides a more performant way to add multiple documents to the Index. Accepts the same options as add.
• del(document)
  • Removes a Document from the Index.
• document_count
  • Returns the number of Documents in the Index
• add_field(name, type, **options, &block)
  • Adds a new field to the Index.
  • The block and options are optional.
  • Ex: index.add_field(:first_name, :text, phonetic: "dm:en")
• reindex(documents, recreate: false)
  • If recreate is true the Index will be dropped and recreated

Searching

Searching is initiated off a RediSearch::Index instance with clauses that can be chained together. When searching, an array of Documents is returned which has public reader methods for all the schema fields.

main ❯ index = RediSearch::Index.new("user_idx") { text_field :name, phonetic: "dm:en" }
main ❯ index.add RediSearch::Document.for_object(index, User.new("10039", "Gene", "Volkman"))
main ❯ index.add RediSearch::Document.for_object(index, User.new("9998", "Jeannie", "Ledner"))
main ❯ index.search("john")
  RediSearch (1.1ms)  FT.SEARCH user_idx `john`
=> [#<RediSearch::Document:0x00007f862e241b78 first: "Gene", last: "Volkman", document_id: "10039">,
#<RediSearch::Document:0x00007f862e2417b8 first: "Jeannie", last: "Ledner", document_id: "9998">]

Simple phrase query - hello AND world

index.search("hello").and("world")

Exact phrase query - hello FOLLOWED BY world

index.search("hello world")

Union query - hello OR world

index.search("hello").or("world")

Negation query - hello AND NOT world

index.search("hello").and.not("world")

Complex intersections and unions:

# Intersection of unions
index.search(index.search("hello").or("halo")).and(index.search("world").or("werld"))
# Negation of union
index.search("hello").and.not(index.search("world").or("werld"))
# Union inside phrase
index.search("hello").and(index.search("world").or("werld"))

All terms support a few options that can be applied.

Prefix terms: match all terms starting with a prefix. (Akin to like term% in SQL)

index.search("hel", prefix: true)
index.search("hello worl", prefix: true)
index.search("hel", prefix: true).and("worl", prefix: true)
index.search("hello").and.not("worl", prefix: true)

Optional terms: documents containing the optional terms will rank higher than those without

index.search("foo").and("bar", optional: true).and("baz", optional: true)

Fuzzy terms: matches are performed based on Levenshtein distance (LD). The maximum Levenshtein distance supported is 3.

index.search("zuchini", fuzziness: 1)

Search terms can also be scoped to specific fields using a where clause:

# Simple field specific query
index.search.where(name: "john")
# Using where with options
index.search.where(first: "jon", fuzziness: 1)
# Using where with more complex query
index.search.where(first: index.search("bill").or("bob"))

Searching for numeric fields takes a range:

index.search.where(number: 0..100)
# Searching to infinity
index.search.where(number: 0..Float::INFINITY)
index.search.where(number: -Float::INFINITY..0)

Query level clauses

• slop(level)
  • We allow a maximum of N intervening number of unmatched offsets between phrase terms. (i.e the slop for exact phrases is 0)
• in_order
  • Usually used in conjunction with slop. We make sure the query terms appear in the same order in the Document as in the query, regardless of the offsets between them.
• no_content
  • Only return the Document ids and not the content. This is useful if RediSearch is being used on a Rails model where the Document attributes don't matter and it's being converted into ActiveRecord objects.
• language(language)
  • Stemmer to use for the supplied language during search for query expansion. If querying Documents in Chinese, this should be set to chinese in order to properly tokenize the query terms. If an unsupported language is sent, the command returns an error.
• sort_by(field, order: :asc)
  • If the supplied field is a sortable field, the results are ordered by the value of this field. This applies to both text and numeric fields. Available orders are :asc or :desc
• limit(num, offset = 0)
  • Limit the results to the specified num at the offset. The default limit is set to 10.
• count
  • Returns the number of Documents found in the search query
• highlight(fields: [], opening_tag: "<b>", closing_tag: "</b>")
  • Use this option to format occurrences of matched text. fields are an array of fields to be highlighted.
• verbatim
  • Do not try to use stemming for query expansion but search the query terms verbatim.
• no_stop_words
  • Do not filter stopwords from the query.
• with_scores
  • Include the relative internal score of each Document. This can be used to merge results from multiple instances. This will add a score method to the returned Document instances.
• return(*fields)
  • Limit which fields from the Document are returned.
• explain
  • Returns the execution plan for a complex query. In the returned response, a + on a term is an indication of stemming.

Spellcheck

Spellchecking is initiated off a RediSearch::Index instance and provides suggestions for misspelled search terms. It takes an optional distance argument which is the maximal Levenshtein distance for spelling suggestions. It returns an array where each element contains suggestions for each search term and a normalized score based on its occurrences in the index.

main ❯ index = RediSearch::Index.new("user_idx") { text_field :name, phonetic: "dm:en" }
main ❯ index.spellcheck("jimy")
  RediSearch (1.1ms)  FT.SPELLCHECK user_idx jimy DISTANCE 1
  => [#<RediSearch::Spellcheck::Result:0x00007f805591c670
    term: "jimy",
    suggestions:
     [#<struct RediSearch::Spellcheck::Suggestion score=0.0006849315068493151, suggestion="jimmy">,
      #<struct RediSearch::Spellcheck::Suggestion score=0.00019569471624266145, suggestion="jim">]>]
main ❯ index.spellcheck("jimy", distance: 2).first.suggestions
  RediSearch (0.5ms)  FT.SPELLCHECK user_idx jimy DISTANCE 2
=> [#<struct RediSearch::Spellcheck::Suggestion score=0.0006849315068493151, suggestion="jimmy">,
 #<struct RediSearch::Spellcheck::Suggestion score=0.00019569471624266145, suggestion="jim">]

Rails Integration

Integration with Rails is super easy! Call redi_search with the schema keyword argument from inside your model. Ex:

class User < ApplicationRecord
  redi_search do
    text_field :first, phonetic: "dm:en"
    text_field :last, phonetic: "dm:en"
  end
end

This will automatically add User.search and User.spellcheck methods which behave the same as if you called them on an Index instance.

User.reindex(recreate: false, only: []) is also added and behaves similarly to RediSearch::Index#reindex. Some of the differences include:

• Documents do not need to be passed as the first parameter. The search_import scope is automatically called and all the records are converted to Documents.
• Accepts an optional only parameter where you can specify a limited number of fields to update. Useful if you alter the schema and only need to index a particular field.

While defining the schema you can optionally pass it a block. If no block is passed the name will called on the model to get the value. If a block is passed the value for the field is obtained through calling the block.

class User < ApplicationRecord
  redi_search do
    text_field :name do
      "#{first_name} #{last_name}"
    end
  end
end

You can override the search_import scope on the model to eager load relationships when indexing or it can be used to limit the records to index.

class User < ApplicationRecord
  scope :search_import, -> { includes(:posts) }
end

When searching, by default a collection of Documents is returned. Calling #results on the search query will execute the search, and then look up all the found records in the database and return an ActiveRecord relation.

The default Index name for model Indexs is #{model_name.plural}_#{RediSearch.env}. The redi_search method takes an optional index_prefix argument which gets prepended to the index name:

class User < ApplicationRecord
  redi_search index_prefix: 'prefix' do
    text_field :first, phonetic: "dm:en"
    text_field :last, phonetic: "dm:en"
  end
end

User.search_index.name
# => prefix_users_development

When integrating RediSearch into a model, records will automatically be indexed after creating and updating and will be removed from the Index upon destruction.

There are a few more convenience methods that are publicly available:

• search_document
  • Returns the record as a RediSearch::Document instance
• remove_from_index
  • Removes the record from the Index
• add_to_index
  • Adds the record to the Index
• search_index
  • Returns the RediSearch::Index instance

Development

After checking out the repo, run bin/setup to install dependencies. Then, run rake test to run the both unit and integration tests. To run them individually you can run rake test:unit or rake test:integration. You can also run bin/console for an interactive prompt that will allow you to experiment.

To install this gem onto your local machine, run bundle exec rake install. To release a new version, execute bin/publish (major|minor|patch) which will update the version number in version.rb, create a git tag for the version, push git commits and tags, and push the .gem file to rubygems.org and GitHub.

Contributing

Bug reports and pull requests are welcome on GitHub. This project is intended to be a safe, welcoming space for collaboration, and contributors are expected to adhere to the Contributor Covenant code of conduct.

License

The gem is available as open source under the terms of the MIT License.

Code of Conduct

Everyone interacting in the RediSearch project’s codebases, issue trackers, chat rooms and mailing lists is expected to follow the code of conduct.