110 lines
4.4 KiB
Ruby
110 lines
4.4 KiB
Ruby
# frozen_string_literal: true
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module Gitlab
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module Database
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class SimilarityScore
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EMPTY_STRING = Arel.sql("''").freeze
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EXPRESSION_ON_INVALID_INPUT = Arel::Nodes::NamedFunction.new('CAST', [Arel.sql('0').as('integer')]).freeze
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DEFAULT_MULTIPLIER = 1
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# This method returns an Arel expression that can be used in an ActiveRecord query to order the resultset by similarity.
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#
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# Note: Calculating similarity score for large volume of records is inefficient. use SimilarityScore only for smaller
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# resultset which is already filtered by other conditions (< 10_000 records).
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#
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# ==== Parameters
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# * +search+ - [String] the user provided search string
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# * +rules+ - [{ column: COLUMN, multiplier: 1 }, { column: COLUMN_2, multiplier: 0.5 }] rules for the scoring.
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# * +column+ - Arel column expression, example: Project.arel_table["name"]
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# * +multiplier+ - Integer or Float to increase or decrease the score (optional, defaults to 1)
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#
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# ==== Use case
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#
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# We'd like to search for projects by path, name and description. We want to rank higher the path and name matches, since
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# it's more likely that the user was remembering the path or the name of the project.
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#
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# Rules:
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# [
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# { column: Project.arel_table['path'], multiplier: 1 },
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# { column: Project.arel_table['name'], multiplier: 1 },
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# { column: Project.arel_table['description'], multiplier: 0.5 }
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# ]
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#
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# ==== Examples
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#
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# Similarity calculation based on one column:
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#
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# Gitlab::Database::SimilarityScore.build_expession(search: 'my input', rules: [{ column: Project.arel_table['name'] }])
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#
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# Similarity calculation based on two column, where the second column has lower priority:
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#
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# Gitlab::Database::SimilarityScore.build_expession(search: 'my input', rules: [
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# { column: Project.arel_table['name'], multiplier: 1 },
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# { column: Project.arel_table['description'], multiplier: 0.5 }
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# ])
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#
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# Integration with an ActiveRecord query:
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#
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# table = Project.arel_table
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#
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# order_expression = Gitlab::Database::SimilarityScore.build_expession(search: 'input', rules: [
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# { column: table['name'], multiplier: 1 },
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# { column: table['description'], multiplier: 0.5 }
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# ])
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#
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# Project.where("name LIKE ?", '%' + 'input' + '%').order(order_expression.desc)
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#
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# The expression can be also used in SELECT:
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#
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# results = Project.select(order_expression.as('similarity')).where("name LIKE ?", '%' + 'input' + '%').order(similarity: :desc)
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# puts results.map(&:similarity)
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#
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def self.build_expression(search:, rules:)
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return EXPRESSION_ON_INVALID_INPUT if search.blank? || rules.empty?
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quoted_search = ActiveRecord::Base.connection.quote(search.to_s)
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first_expression, *expressions = rules.map do |rule|
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rule_to_arel(quoted_search, rule)
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end
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# (SIMILARITY ...) + (SIMILARITY ...)
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expressions.inject(first_expression) do |expression1, expression2|
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Arel::Nodes::Addition.new(expression1, expression2)
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end
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end
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# (SIMILARITY(COALESCE(column, ''), 'search_string') * CAST(multiplier AS numeric))
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def self.rule_to_arel(search, rule)
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Arel::Nodes::Grouping.new(
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Arel::Nodes::Multiplication.new(
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similarity_function_call(search, column_expression(rule)),
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multiplier_expression(rule)
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)
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)
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end
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# COALESCE(column, '')
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def self.column_expression(rule)
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Arel::Nodes::NamedFunction.new('COALESCE', [rule.fetch(:column), EMPTY_STRING])
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end
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# SIMILARITY(COALESCE(column, ''), 'search_string')
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def self.similarity_function_call(search, column)
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Arel::Nodes::NamedFunction.new('SIMILARITY', [column, Arel.sql(search)])
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end
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# CAST(multiplier AS numeric)
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def self.multiplier_expression(rule)
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quoted_multiplier = ActiveRecord::Base.connection.quote(rule.fetch(:multiplier, DEFAULT_MULTIPLIER).to_s)
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Arel::Nodes::NamedFunction.new('CAST', [Arel.sql(quoted_multiplier).as('numeric')])
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end
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private_class_method :rule_to_arel
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private_class_method :column_expression
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private_class_method :similarity_function_call
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private_class_method :multiplier_expression
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end
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end
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end
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