一覧へ戻る
Adds additional postgres functionality to an ActiveRecord / Rails application
- star 数
- 1,464
- watcher 数
- 7
- fork 数
- 50
- issue 数
- 13
- 最終更新
- 2026/06/24
gem-hunterAdds additional postgres functionality to an ActiveRecord / Rails application
Active Record Extended is the continuation of maintaining and improving the work done by Dan McClain, the original author of postgres_ext.
Overtime the lack of updating to support the latest versions of ActiveRecord 5.x has caused quite a bit of users forking off the project to create their own patches jobs to maintain compatibility. The only problem is that this has created a wild west of environments of sorts. The problem has grown to the point no one is attempting to directly contribute to the original source. And forked repositories are finding themselves as equally as dead with little to no activity.
Active Record Extended is essentially providing users with the other half of Postgreses querying abilities. Due to Rails/ActiveRecord/Arel being designed to be DB agnostic, there are a lot of left out features; Either by choice or the simple lack of supporting API's for other databases. However some features are not exactly PG explicit. Some are just helper methods to express an idea much more easily.
This package is designed to align and work with any officially supported Ruby and Rails versions.
Add this line to your application's Gemfile:
gem 'active_record_extended'
And then execute:
$ bundle
In Postgres the ANY expression is used for gather record's that have an Array column type that contain a single matchable value within its array.
alice = User.create!(tags: [1]) bob = User.create!(tags: [1, 2]) randy = User.create!(tags: [3]) User.where.any(tags: 1) #=> [alice, bob]
This only accepts a single value. So querying for example multiple tag numbers [1,2] will return nothing.
In Postgres the ALL expression is used for gather record's that have an Array column type that contains only a single and matchable element.
alice = User.create!(tags: [1]) bob = User.create!(tags: [1, 2]) randy = User.create!(tags: [3]) User.where.all(tags: 1) #=> [alice]
This only accepts a single value to a given attribute. So querying for example multiple tag numbers [1,2] will return nothing.
Postgres '@>' (Array type) Contains expression
Postgres '@>' (JSONB/HSTORE type) Contains expression
The contains/1 method is used for finding any elements in an Array, JSONB, or HSTORE column type.
That contains all of the provided values.
Array Type:
alice = User.create!(tags: [1, 4]) bob = User.create!(tags: [3, 1]) randy = User.create!(tags: [4, 1]) User.where.contains(tags: [1, 4]) #=> [alice, randy]
HSTORE / JSONB Type:
alice = User.create!(data: { nickname: "ARExtend" }) bob = User.create!(data: { nickname: "ARExtended" }) randy = User.create!(data: { nickname: "ARExtended" }) User.where.contains(data: { nickname: "ARExtended" }) #=> [bob, randy]
Postgres && (overlap) Expression
The overlap/1 method will match an Array column type that contains any of the provided values within its column.
alice = User.create!(tags: [1, 4]) bob = User.create!(tags: [3, 4]) randy = User.create!(tags: [4, 8]) User.where.overlap(tags: [4]) #=> [alice, bob, randy] User.where.overlap(tags: [1, 8]) #=> [alice, randy] User.where.overlap(tags: [1, 3, 8]) #=> [alice, bob, randy]
Postgres >> (contains) Network Expression
The inet_contains method works by taking a column(inet type) that has a submask prepended to it.
And tries to find related records that fall within a given IP's range.
alice = User.create!(ip: "127.0.0.1/16") bob = User.create!(ip: "192.168.0.1/16") User.where.inet_contains(ip: "127.0.0.254") #=> [alice] User.where.inet_contains(ip: "192.168.20.44") #=> [bob] User.where.inet_contains(ip: "192.255.1.1") #=> []
Postgres >>= (contains or equals) Network Expression
The inet_contains_or_equals method works much like the Inet Contains method, but will also accept a submask range.
alice = User.create!(ip: "127.0.0.1/10") bob = User.create!(ip: "127.0.0.44/24") User.where.inet_contains_or_equals(ip: "127.0.0.1/16") #=> [alice] User.where.inet_contains_or_equals(ip: "127.0.0.1/10") #=> [alice] User.where.inet_contains_or_equals(ip: "127.0.0.1/32") #=> [alice, bob]
Postgres << (contained by) Network Expression
For the inet_contained_within method, we try to find IP's that fall within a submasking range we provide.
alice = User.create!(ip: "127.0.0.1") bob = User.create!(ip: "127.0.0.44") randy = User.create!(ip: "127.0.55.20") User.where.inet_contained_within(ip: "127.0.0.1/24") #=> [alice, bob] User.where.inet_contained_within(ip: "127.0.0.1/16") #=> [alice, bob, randy]
Postgres <<= (contained by or equals) Network Expression
The inet_contained_within_or_equals method works much like the Inet Contained Within method, but will also accept a submask range.
alice = User.create!(ip: "127.0.0.1/10") bob = User.create!(ip: "127.0.0.44/32") randy = User.create!(ip: "127.0.99.1") User.where.inet_contained_within_or_equals(ip: "127.0.0.44/32") #=> [bob] User.where.inet_contained_within_or_equals(ip: "127.0.0.1/16") #=> [bob, randy] User.where.inet_contained_within_or_equals(ip: "127.0.0.44/8") #=> [alice, bob, randy]
Postgres && (contains or is contained by) Network Expression
The inet_contains_or_contained_within method is a combination of Inet Contains and Inet Contained Within.
It essentially (the database) tries to use both methods to find as many records as possible that match either condition on both sides.
alice = User.create!(ip: "127.0.0.1/24") bob = User.create!(ip: "127.0.22.44/8") randy = User.create!(ip: "127.0.99.1") User.where.inet_contains_or_is_contained_within(ip: "127.0.255.80") #=> [bob] User.where.inet_contains_or_is_contained_within(ip: "127.0.0.80") #=> [alice, bob] User.where.inet_contains_or_is_contained_within(ip: "127.0.0.80/8") #=> [alice, bob, randy]
any_of/1 simplifies the process of finding records that require multiple or conditions.
none_of/1 is the inverse of any_of/1. It'll find records where none of the contains are matched.
Both accepts An array of: ActiveRecord Objects, Query Strings, and basic attribute names.
Querying With Attributes:
alice = User.create!(uid: 1) bob = User.create!(uid: 2) randy = User.create!(uid: 3) User.where.any_of({ uid: 1 }, { uid: 2 }) #=> [alice, bob]
Querying With ActiveRecord Objects:
alice = User.create!(uid: 1) bob = User.create!(uid: 2) randy = User.create!(uid: 3) uid_one = User.where(uid: 1) uid_two = User.where(uid: 2) User.where.any_of(uid_one, uid_two) #=> [alice, bob]
Querying with Joined Relationships:
alice = User.create!(uid: 1) bob = User.create!(uid: 2) randy = User.create!(uid: 3) tag_alice = Tag.create!(user_id: alice.id) tag_bob = Tag.create!(user_id: bob.id) tag_randy = Tag.create!(user_id: randy.id) bob_tag_query = Tag.where(users: { id: bob.id }).includes(:user) randy_tag_query = Tag.where(users: { id: randy.id }).joins(:user) Tag.joins(:user).where.any_of(bob_tag_query, randy_tag_query) #=> [tag_bob, tag_randy] (with users table joined)
The #either_join/2 method is a base ActiveRecord querying method that will joins records based on a set of conditionally joinable tables.
class User < ActiveRecord::Base has_one :profile_l, class: "ProfileL" has_one :profile_r, class: "ProfileR" scope :completed_profile, -> { either_joins(:profile_l, :profile_r) } end alice = User.create! bob = User.create! randy = User.create! # Does not have a single completed profile type ProfileL.create!(user_id: alice.id) ProfileR.create!(user_id: bob.id) User.completed_profile #=> [alice, bob] # alternatively User.either_joins(:profile_l, :profile_r) #=> [alice, bob]
The #either_order/3 method is a base ActiveRecord querying method that will order a set of columns that may or may not exist for each record.
This works similar to how Either Join works. This does not however exclude records that do not have relationships.
alice = User.create! bob = User.create! ProfileL.create!(user_id: alice.id, left_turns: 100) ProfileR.create!(user_id: bob.id, right_turns: 50) User.either_order(:asc, profile_l: :left_turns, profile_r: :right_turns) #=> [bob, alice] User.either_order(:desc, profile_l: :left_turns, profile_r: :right_turns) #=> [alice, bob] randy = User.create! User.either_order(:asc, profile_l: :left_turns, profile_r: :right_turns) #=> [bob, alice, randy] User.either_order(:desc, profile_l: :left_turns, profile_r: :right_turns) #=> [randy, alice, bob]
The .with/1 method is a base ActiveRecord querying method that will aid in creating complex queries.
alice = User.create! bob = User.create! randy = User.create! ProfileL.create!(user_id: alice.id, likes: 200) ProfileL.create!(user_id: bob.id, likes: 400) ProfileL.create!(user_id: randy.id, likes: 600) User.with(highly_liked: ProfileL.where("likes > 300")) .joins("JOIN highly_liked ON highly_liked.user_id = users.id") #=> [bob, randy]
Query output:
WITH "highly_liked" AS (SELECT "profile_ls".* FROM "profile_ls" WHERE (likes >= 300)) SELECT "users".* FROM "users" JOIN highly_liked ON highly_liked.user_id = users.id
You can also chain or provide additional arguments to the with/1 method for it to merge into a single, WITH statement.
User.with(highly_liked: ProfileL.where("likes > 300"), less_liked: ProfileL.where("likes <= 200")) .joins("JOIN highly_liked ON highly_liked.user_id = users.id") .joins("JOIN less_liked ON less_liked.user_id = users.id") # OR User.with(highly_liked: ProfileL.where("likes > 300")) .with(less_liked: ProfileL.where("likes <= 200")) .joins("JOIN highly_liked ON highly_liked.user_id = users.id") .joins("JOIN less_liked ON less_liked.user_id = users.id")
Query output:
WITH "highly_liked" AS (SELECT "profile_ls".* FROM "profile_ls" WHERE (likes > 300)), "less_liked" AS (SELECT "profile_ls".* FROM "profile_ls" WHERE (likes <= 200)) SELECT "users".* FROM "users" JOIN highly_liked ON highly_liked.user_id = users.id JOIN less_liked ON less_liked.user_id = users.id
There are three methods you can chain to the with/1 to add modifiers to the query.
User.with.recursive(highly_liked: ProfileL.where("likes > 300")) .joins("JOIN highly_liked ON highly_liked.user_id = users.id")
Query output:
WITH RECURSIVE "highly_liked" AS (SELECT "profile_ls".* FROM "profile_ls" WHERE (likes >= 300)) SELECT "users".* FROM "users" JOIN highly_liked ON highly_liked.user_id = users.id
materialized (Note: MATERIALIZED modifier is only available in PG versions 12+.)User.with.materialized(highly_liked: ProfileL.where("likes > 300")) .joins("JOIN highly_liked ON highly_liked.user_id = users.id")
Query output:
WITH "highly_liked" AS MATERIALIZED (SELECT "profile_ls".* FROM "profile_ls" WHERE (likes >= 300)) SELECT "users".* FROM "users" JOIN highly_liked ON highly_liked.user_id = users.id
not_materialized (Note: NOT MATERIALIZED modifier is only available in PG versions 12+.)User.with.not_materialized(highly_liked: ProfileL.where("likes > 300")) .joins("JOIN highly_liked ON highly_liked.user_id = users.id")
Query output:
WITH "highly_liked" AS NOT MATERIALIZED (SELECT "profile_ls".* FROM "profile_ls" WHERE (likes >= 300)) SELECT "users".* FROM "users" JOIN highly_liked ON highly_liked.user_id = users.id
In order keep queries PG valid, subquery explicit methods (like Unions and JSON methods) will be subject to "Piping" the CTE clauses up to the parents query level.
This also means there's potential for having duplicate CTE names. In order to combat duplicate CTE references with the same name, piping will favor the parents CTE over the nested sub-queries.
This also means that this is a "First come First Served" implementation. So if you have a parent with no CTE's but two sub-queries with the same CTE name but with different querying statements. It will process and favor the one that comes first.
Example:
sub_query = Person.with(dupped_cte: Person.where(id: 1)).select("dup_cte.id").from(:dup_cte) other_subquery = Person.with(unique_cte: Person.where(id: 5)).select("unique_cte.id").from(:unique_cte) # Will favor this CTE below, over the `sub_query`'s CTE Person.with(dupped_cte: Person.where.not(id: 1..4)).union(sub_query, other_subquery)
Query Output
WITH "unique_cte" AS ( SELECT "people".* FROM "people" WHERE "people"."id" = 5 ), "dupped_cte" AS ( SELECT "people".* FROM "people" WHERE NOT ("people"."id" BETWEEN 1 AND 4) ) SELECT "people".* FROM (( ( SELECT dup_cte.id FROM dup_cte ) UNION ( SELECT unique_cte.id FROM unique_cte ) )) people
If any or all of your json sub-queries include a CTE, read the Subquery CTE Gotchas warnings.
Postgres 'ROW_TO_JSON' function
The implementation of the.select_row_to_json/2 method is designed to be used with sub-queries. As a means for taking complex
query logic and transform them into a single or multiple json responses. These responses are required to be assigned
to an aliased column on the parent(callee) level.
While quite the mouthful of an explanation. The implementation of combining unrelated or semi-related queries is quite smooth(imo).
Arguments:
from [String, Arel, or ActiveRecord::Relation]: A subquery that can be nested into a ROW_TO_JSON clauseOptions:
as [Symbol or String] (default="results"): What the column will be aliased tokey [Symbol or String] (default=[random letter]): Internal query alias name.
cast_with [Symbol or Array<Symbol>]:
:to_jsonb:array:array_agg:distinct (auto applies :array_agg & :to_jsonb)order_by [Symbol or Hash]: Applies an ordering operation (similar to ActiveRecord #order)
physical_cat = Category.create!(name: "Physical") products = 3.times.map { Product.create! } products.each { |product| 100.times { Variant.create!(product: product, category: physical_cat) } } # Since we plan to nest this query, you have access top level information. (I.E categories table) item_query = Variant.select(:name, :id, :category_id, :product_id).where("categories.id = variants.category_id") # You can provide addition scopes that will be applied to the nested query (but will not effect the actual inner query) # This is ideal if you are dealing with but not limited to, CTE's being applied multiple times and require additional constraints product_query = Product.select(:id) .joins(:items) .select_row_to_json(item_query, key: :outer_items, as: :items, cast_with: :array) do |item_scope| item_scope.where("outer_items.product_id = products.id") # Results to: # SELECT ..., ARRAY(SELECT ROW_TO_JSON("outer_items") # FROM ([:item_query:]) outer_items # WHERE outer_items.product_id = products.id # ) AS items end # Not defining a key will automatically generate a random key between a-z category_query = Category.select(:name, :id).select_row_to_json(product_query, as: :products, cast_with: :array) Category.json_build_object(:physical_category, category_query.where(id: physical_cat.id)).results #=> { # "physical_category" => { # "name" => "Physical", # "id" => 1, # "products" => [ # { # "id" => 2, # "items" => [{"name" => "Bojangels", "id" => 3, "category_id" => 1, "product_id" => 2}, ...] # }, # ... # ] # } # } #
Query Output
SELECT (JSON_BUILD_OBJECT('physical_category', "physical_category")) AS "results" FROM ( SELECT "categories"."name", "categories"."id", (ARRAY( SELECT ROW_TO_JSON("j") FROM ( SELECT "products"."id", (ARRAY( SELECT ROW_TO_JSON("outer_item") FROM ( SELECT "variants"."name", "variants"."id", "variants"."category_id", "variants"."product_id" FROM "variants" WHERE (categories.id = variants.category_id) ) outer_items WHERE (outer_items.product_id = products.id) )) AS "items" FROM "products" INNER JOIN "items" ON "products"."id" = "items"."product_id" ) j )) AS "products" FROM "categories" WHERE "categories"."id" = 1 ) AS "physical_category"
Postgres 'json(b)_build_object' function
The implementation of the.json_build_object/2 and .jsonb_build_object/2 methods are designed to be used with sub-queries.
As a means for taking complex query logic and transform them into a single or multiple json responses.
Arguments:
key: [Symbol or String]: What should this response return asfrom: [String, Arel, or ActiveRecord::Relation] : A subquery that can be nested into the top-level from clauseOptions:
as: [Symbol or String] (defaults to "results"): What the column will be aliased tovalue: [Symbol or String] (defaults to key argument): How the response should handle the json value returnSee the included example on Row To JSON to see it in action.
Postgres 'json(b)_build_object' function
The implementation of the.json_build_literal/1 and .jsonb_build_literal/1 is designed for creating static json objects
that don't require subquery interfacing.
Arguments:
Options:
as: [Symbol or String] (defaults to "results"): What the column will be aliased toUser.json_build_literal(number: 1, last_name: "json", pi: 3.14).take.results #=> { "number" => 1, "last_name" => "json", "pi" => 3.14 } # Or as array elements User.json_build_literal(:number, 1, :last_name, "json", :pi, 3.14).take.results #=> { "number" => 1, "last_name" => "json", "pi" => 3.14 }
Query Output
SELECT (JSON_BUILD_OBJECT('number', 1, 'last_name', 'json', 'pi', 3.14)) AS "results" FROM "users"
If any or all of your union queries include a CTE, read the Subquery CTE Gotchas warnings.
.to_union_sql : Will return a string of the constructed union query without being nested in the from clause..to_nice_union_sql(requires NiceQL Gem to be install): A formatted .to_union_sqlThere's an issue with providing a single union clause and chaining it with a different union clause. This is due to requirements of grouping SQL statements. The issue is being working on, but with no ETA.
This issue only applies to the first initial set of unions and is recommended that you union two relations right off the bat. Afterwards you can union/chain single relations.
Example
Person.union(Person.where(id: 1..4)).union_except(Person.where(id: 3..4)).union(Person.where(id: 4)) #=> Will include all people with an ID between 1 & 3 (throwing the except on ID 4) # This can be fixed by doing something like Person.union_except(Person.where(id: 1..4), Person.where(id: 3..4)).union(Person.where(id: 4)) #=> Will include people with the ids of 1, 2, and 4 (properly excluding the user with the ID of 3)
Problem Query Output
( ( ( SELECT "people".* FROM "people" WHERE "people"."id" BETWEEN 1 AND 4 ) UNION ( SELECT "people".* FROM "people" WHERE "people"."id" BETWEEN 3 AND 4 ) ) EXCEPT ( SELECT "people".* FROM "people" WHERE "people"."id" = 4 ) )
user_1 = Person.where(id: 1) user_2 = Person.where(id: 2) users = Person.where(id: 1..3) Person.union(user_1, user_2, users) #=> [#<Person id: 1, ..>, #<Person id: 2,..>, #<Person id: 3,..>] # You can also chain union's Person.union(user_1).union(user_2).union(users)
Query Output
SELECT "people".* FROM (( ( ( SELECT "people".* FROM "people" WHERE "people"."id" = 1 ) UNION ( SELECT "people".* FROM "people" WHERE "people"."id" = 2 ) ) UNION ( SELECT "people".* FROM "people" WHERE "people"."id" BETWEEN 1 AND 3 ) )) people
Postgres 'UNION ALL' combination
user_1 = Person.where(id: 1) user_2 = Person.where(id: 2) users = Person.where(id: 1..3) Person.union_all(user_1, user_2, users) #=> [#<Person id: 1, ..>, #<Person id: 2,..>, #<Person id: 1, ..>, #<Person id: 2,..>, #<Person id: 3,..>] # You can also chain union's Person.union_all(user_1).union_all(user_2).union_all(users) # Or Person.union.all(user1, user_2).union.all(users)
Query Output
SELECT "people".* FROM (( ( ( SELECT "people".* FROM "people" WHERE "people"."id" = 1 ) UNION ALL ( SELECT "people".* FROM "people" WHERE "people"."id" = 2 ) ) UNION ALL ( SELECT "people".* FROM "people" WHERE "people"."id" BETWEEN 1 AND 3 ) )) people
users = Person.where(id: 1..5) except_these_users = Person.where(id: 2..4) Person.union_except(users, except_these_users) #=> [#<Person id: 1, ..>, #<Person id: 5,..>] # You can also chain union's Person.union.except(users, except_these_users).union(Person.where(id: 20))
Query Output
SELECT "people".* FROM (( ( ( SELECT "people".* FROM "people" WHERE "people"."id" BETWEEN 1 AND 5 ) EXCEPT ( SELECT "people".* FROM "people" WHERE "people"."id" BETWEEN 2 AND 4 )) people
Postgres 'INTERSECT' combination
randy = Person.create! alice = Person.create! ProfileL.create!(person: randy, likes: 100) ProfileL.create!(person: alice, likes: 120) likes_100 = Person.select(:id, "profile_ls.likes").joins(:profile_l).where(profile_ls: { likes: 100 }) likes_less_than_150 = Person.select(:id, "profile_ls.likes").joins(:profile_l).where("profile_ls.likes < 150") Person.union_intersect(likes_100, likes_less_than_150) #=> [randy] # You can also chain union's Person.union_intersect(likes_100).union_intersect(likes_less_than_150) #=> [randy] # Or Person.union.intersect(likes_100, likes_less_than_150) #=> [randy]
Query Output
SELECT "people".* FROM (( ( SELECT "people"."id", profile_ls.likes FROM "people" INNER JOIN "profile_ls" ON "profile_ls"."person_id" = "people"."id" WHERE "profile_ls"."likes" = 100 ) INTERSECT ( SELECT "people"."id", profile_ls.likes FROM "people" INNER JOIN "profile_ls" ON "profile_ls"."person_id" = "people"."id" WHERE (profile_ls.likes < 150) ) )) people
By default unions are nested in the from clause and are aliased to the parents table name.
We can change this behavior by chaining the method .union_as/1
Person.select("good_people.id").union(Person.where(id: 1), Person.where(id: 2)).union_as(:good_people)
Query Output
SELECT good_people.id FROM (( ( SELECT "people".* FROM "people" WHERE "people"."id" = 1 ) UNION ( SELECT "people".* FROM "people" WHERE "people"."id" = 2 ) )) good_people
Unions allow for a final outside ORDER BY clause. This will ensure that all the results that come back are ordered in an expected return.
query_1 = Person.where(id: 1..3) query_2 = Person.where(id: 3) query_3 = Person.where(id: 3..10) Person.union_except(query_1, query_2).union(query_3).order_union(:id, tags: :desc)
Query Output
SELECT "people".* FROM (( ( ( SELECT "people".* FROM "people" WHERE "people"."id" BETWEEN 1 AND 3 ) EXCEPT ( SELECT "people".* FROM "people" WHERE "people"."id" = 3 ) ) UNION ( SELECT "people".* FROM "people" WHERE "people"."id" BETWEEN 3 AND 10 ) ) ORDER BY id ASC, tags DESC) people
much like Rails .reorder; .reorder_union/1 will clear the previous order in a new instance and/or apply a new ordering scheme
query_1 = Person.where(id: 1..3) query_2 = Person.where(id: 3) query_3 = Person.where(id: 3..10) union_query = Person.union_except(query_1, query_2).union(query_3).order_union(:id, tags: :desc) union_query.reorder_union(personal_id: :desc, id: :desc)
Query Output
SELECT "people".* FROM (( ( ( SELECT "people".* FROM "people" WHERE "people"."id" BETWEEN 1 AND 3 ) EXCEPT ( SELECT "people".* FROM "people" WHERE "people"."id" = 3 ) ) UNION ( SELECT "people".* FROM "people" WHERE "people"."id" BETWEEN 3 AND 10 ) ) ORDER BY personal_id DESC, id DESC) people
Let's address the elephant in the room. Arel has had, for a long time now, window function capabilities; However they've never seen the lime light in ActiveRecord's query logic. The following brings the dormant Arel methods up to the ActiveRecord Querying level.
To set up a window function, we first must establish the window and we do this by using the .define_window/1 method.
This method also requires you to call chain .partition_by/2
.define_window/1 - Establishes the name of the window you'll reference later on in .select_window
.partition_by/2 - Establishes the windows operations a pre-defined window function will leverage.
order_by: Processes how the window should be orderedUser .define_window(:number_window).partition_by(:number, order_by: { id: :desc }) .define_window(:name_window).partition_by(:name, order_by: :id) .define_window(:no_order_name).partition_by(:name)
Query Output
SELECT * FROM users WINDOW number_window AS (PARTITION BY number ORDER BY id DESC), name_window AS (PARTITION BY name ORDER BY id), no_order_name AS (PARTITION BY name)
Once you've define a window, the next step to to utilize it on one of the many provided postgres window functions.
.select_window/3
as: : Alias name of the final resultover: : name of defined windowUser.create!(name: "Alice", number: 100) #=> id: 1 User.create!(name: "Randy", number: 100) #=> id: 2 User.create!(name: "Bob", number: 300) #=> id: 3 User .define_window(:number_window).partition_by(:number, order_by: { id: :desc }) .select(:id, :name) .select_window(:row_number, over: :number_window, as: :row_id) .select_window(:first_value, :name, over: :number_window, as: :first_value_name) #=> [ # { id: 1, name: "Alice", row_id: 2, first_value_name: "Randy" } # { id: 2, name: "Randy", row_id: 1, first_value_name: "Randy" } # { id: 3, name: "Bob", row_id: 1, first_value_name: "Bob" } # ] #
Query Output
SELECT "users"."id", "users"."name", (ROW_NUMBER() OVER number_window) AS "row_id", (FIRST_VALUE(name) OVER number_window) AS "first_value_name" FROM "users" WINDOW number_window AS (PARTITION BY number ORDER BY id DESC)
The gem is available as open source under the terms of the MIT License.