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# Arel
* http://github.com/rails/arel
## DESCRIPTION
Arel Really Exasperates Logicians
Arel is a SQL AST manager for Ruby. It
1. Simplifies the generation of complex SQL queries
2. Adapts to various RDBMSes
It is intended to be a framework framework; that is, you can build your own ORM
with it, focusing on innovative object and collection modeling as opposed to
database compatibility and query generation.
## Status
For the moment, Arel uses Active Record's connection adapters to connect to the various engines, connection pooling, perform quoting, and do type conversion.
## A Gentle Introduction
Generating a query with Arel is simple. For example, in order to produce
```sql
SELECT * FROM users
```
you construct a table relation and convert it to sql:
```ruby
users = Arel::Table.new(:users)
query = users.project(Arel.sql('*'))
query.to_sql
```
### More Sophisticated Queries
Here is a whirlwind tour through the most common SQL operators. These will probably cover 80% of all interaction with the database.
First is the 'restriction' operator, `where`:
```ruby
users.where(users[:name].eq('amy'))
# => SELECT * FROM users WHERE users.name = 'amy'
```
What would, in SQL, be part of the `SELECT` clause is called in Arel a `projection`:
```ruby
users.project(users[:id])
# => SELECT users.id FROM users
```
Comparison operators `=`, `!=`, `<`, `>`, `<=`, `>=`, `IN`:
```ruby
users.where(users[:age].eq(10)).project(Arel.sql('*')) # => SELECT * FROM "users" WHERE "users"."age" = 10
users.where(users[:age].not_eq(10)).project(Arel.sql('*')) # => SELECT * FROM "users" WHERE "users"."age" != 10
users.where(users[:age].lt(10)).project(Arel.sql('*')) # => SELECT * FROM "users" WHERE "users"."age" < 10
users.where(users[:age].gt(10)).project(Arel.sql('*')) # => SELECT * FROM "users" WHERE "users"."age" > 10
users.where(users[:age].lteq(10)).project(Arel.sql('*')) # => SELECT * FROM "users" WHERE "users"."age" <= 10
users.where(users[:age].gteq(10)).project(Arel.sql('*')) # => SELECT * FROM "users" WHERE "users"."age" >= 10
users.where(users[:age].in([20, 16, 17])).project(Arel.sql('*')) # => SELECT * FROM "users" WHERE "users"."age" IN (20, 16, 17)
```
Joins resemble SQL strongly:
```ruby
users.join(photos).on(users[:id].eq(photos[:user_id]))
# => SELECT * FROM users INNER JOIN photos ON users.id = photos.user_id
```
Left Joins
```ruby
users.join(photos, Arel::Nodes::OuterJoin).on(users[:id].eq(photos[:user_id]))
# => SELECT FROM users LEFT OUTER JOIN photos ON users.id = photos.user_id
```
What are called `LIMIT` and `OFFSET` in SQL are called `take` and `skip` in Arel:
```ruby
users.take(5) # => SELECT * FROM users LIMIT 5
users.skip(4) # => SELECT * FROM users OFFSET 4
```
`GROUP BY` is called `group`:
```ruby
users.project(users[:name]).group(users[:name])
# => SELECT users.name FROM users GROUP BY users.name
```
The best property of arel is its "composability", or closure under all operations. For example, to restrict AND project, just "chain" the method invocations:
```ruby
users \
.where(users[:name].eq('amy')) \
.project(users[:id]) \
# => SELECT users.id FROM users WHERE users.name = 'amy'
```
All operators are chainable in this way, and they are chainable any number of times, in any order.
```ruby
users.where(users[:name].eq('bob')).where(users[:age].lt(25))
```
The `OR` operator works like this:
```ruby
users.where(users[:name].eq('bob').or(users[:age].lt(25)))
```
The `AND` operator behaves similarly.
Aggregate functions `AVG`, `SUM`, `COUNT`, `MIN`, `MAX`, `HAVING`:
```ruby
photos.group(photos[:user_id]).having(photos[:id].count.gt(5)) # => SELECT FROM photos GROUP BY photos.user_id HAVING COUNT(photos.id) > 5
users.project(users[:age].sum) # => SELECT SUM(users.age) FROM users
users.project(users[:age].average) # => SELECT AVG(users.age) FROM users
users.project(users[:age].maximum) # => SELECT MAX(users.age) FROM users
users.project(users[:age].minimum) # => SELECT MIN(users.age) FROM users
users.project(users[:age].count) # => SELECT COUNT(users.age) FROM users
```
Aliasing Aggregate Functions:
```ruby
users.project(users[:age].average.as("mean_age")) # => SELECT AVG(users.age) AS mean_age FROM users
```
### The Crazy Features
The examples above are fairly simple and other libraries match or come close to matching the expressiveness of Arel (e.g., `Sequel` in Ruby).
#### Inline math operations
Suppose we have a table `products` with prices in different currencies. And we have a table `currency_rates`, of constantly changing currency rates. In Arel:
```ruby
products = Arel::Table.new(:products)
# Attributes: [:id, :name, :price, :currency_id]
currency_rates = Arel::Table.new(:currency_rates)
# Attributes: [:from_id, :to_id, :date, :rate]
```
Now, to order products by price in user preferred currency simply call:
```ruby
products.
join(:currency_rates).on(products[:currency_id].eq(currency_rates[:from_id])).
where(currency_rates[:to_id].eq(user_preferred_currency), currency_rates[:date].eq(Date.today)).
order(products[:price] * currency_rates[:rate])
```
#### Complex Joins
Where Arel really shines is in its ability to handle complex joins and aggregations. As a first example, let's consider an "adjacency list", a tree represented in a table. Suppose we have a table `comments`, representing a threaded discussion:
```ruby
comments = Arel::Table.new(:comments)
```
And this table has the following attributes:
```ruby
# [:id, :body, :parent_id]
```
The `parent_id` column is a foreign key from the `comments` table to itself.
Joining a table to itself requires aliasing in SQL. This aliasing can be handled from Arel as below:
```ruby
replies = comments.alias
comments_with_replies = \
comments.join(replies).on(replies[:parent_id].eq(comments[:id])).where(comments[:id].eq(1))
# => SELECT * FROM comments INNER JOIN comments AS comments_2 WHERE comments_2.parent_id = comments.id AND comments.id = 1
```
This will return the reply for the first comment.
[Common Table Expressions(CTE)](https://en.wikipedia.org/wiki/Common_table_expressions#Common_table_expression) support via:
Create a `CTE`
```ruby
cte_table = Arel::Table.new(:cte_table)
composed_cte = Arel::Nodes::As.new(cte_table, photos.where(photos[:created_at].gt(Date.current)))
```
Use the created `CTE`:
```ruby
users.
join(cte_table).on(users[:id].eq(cte_table[:user_id])).
project(users[:id], cte_table[:click].sum).
with(composed_cte)
# => WITH cte_table AS (SELECT FROM photos WHERE photos.created_at > '2014-05-02') SELECT users.id, SUM(cte_table.click) FROM users INNER JOIN cte_table ON users.id = cte_table.user_id
```
When your query is too complex for `Arel`, you can use `Arel::SqlLiteral`:
```ruby
photo_clicks = Arel::Nodes::SqlLiteral.new(<<-SQL
CASE WHEN condition1 THEN calculation1
WHEN condition2 THEN calculation2
WHEN condition3 THEN calculation3
ELSE default_calculation END
SQL
)
photos.project(photo_clicks.as("photo_clicks"))
# => SELECT CASE WHEN condition1 THEN calculation1
WHEN condition2 THEN calculation2
WHEN condition3 THEN calculation3
ELSE default_calculation END
FROM "photos"
```
## Contributing to Arel
Arel is work of many contributors. You're encouraged to submit pull requests, propose
features and discuss issues.
See [CONTRIBUTING](CONTRIBUTING.md).
## License
Arel is released under the [MIT License](http://www.opensource.org/licenses/MIT).
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