Description
Related is a Ruby relational algebra engine. Define relations, add data to them, and then perform relational algebra operations on them.
When I was learning relational algebra, I had trouble visualizing what my operations were doing, and I had no quick way of testing them out without spinning up a database. Even then, SQL didn't map very directly to the underlying principles I was trying to learn.
Enter Related. Related was written to provide students and others with a quick scratchpad to run relational algebra operations.
Each of Codd's Primitives (selection, projection, cross_product, union, and difference) are implemented, meaning you can in theory perform any operation possible. natural_join is also implemented, and I'll work to add more over time.
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README
Related
Related is a Ruby relational algebra engine. Define relations, add data to them, and then perform relational algebra operations on them.
When I was learning relational algebra, I had trouble visualizing what my operations were doing, and I had no quick way of testing them out without spinning up a database. Even then, SQL didn't map very directly to the underlying principles I was trying to learn.
Enter Related. Related was written to provide students and others with a quick scratchpad to run relational algebra operations.
Each of Codd's Primitives (selection
, projection
, cross_product
, union
, and difference
) are implemented, meaning you can in theory perform any operation possible. natural_join
is also implemented, and I'll work to add more over time.
Example
Define relations like this:
require 'related'
people = Relation.new do r
r.schema = Schema.new(name: String, age: Integer, gender: String)
r.add_tuple ['Amy', 16, 'female']
r.add_tuple ['Ben', 21, 'male']
r.add_tuple ['Cal', 33, 'male']
r.add_tuple ['Dan', 13, 'male']
r.add_tuple ['Eli', 45, 'male']
r.add_tuple ['Fay', 21, 'female']
r.add_tuple ['Gus', 24, 'male']
r.add_tuple ['Hil', 30, 'female']
r.add_tuple ['Ian', 18, 'male']
end
favorites = Relation.new do r
r.schema = Schema.new(name: String, pizza: String)
r.add_tuple ['Amy', 'mushroom']
r.add_tuple ['Amy', 'pepperoni']
r.add_tuple ['Ben', 'cheese']
r.add_tuple ['Ben', 'pepperoni']
r.add_tuple ['Cal', 'supreme']
r.add_tuple ['Dan', 'cheese']
r.add_tuple ['Dan', 'mushroom']
r.add_tuple ['Dan', 'pepperoni']
r.add_tuple ['Dan', 'sausage']
r.add_tuple ['Dan', 'supreme']
r.add_tuple ['Eli', 'cheese']
r.add_tuple ['Eli', 'supreme']
r.add_tuple ['Fay', 'mushroom']
r.add_tuple ['Gus', 'cheese']
r.add_tuple ['Gus', 'mushroom']
r.add_tuple ['Gus', 'supreme']
r.add_tuple ['Hil', 'cheese']
r.add_tuple ['Hil', 'supreme']
r.add_tuple ['Ian', 'pepperoni']
r.add_tuple ['Ian', 'supreme']
end
menus = Relation.new do r
r.schema = Schema.new(pizzeria: String, pizza: String, price: Numeric)
r.add_tuple ['Chicago Pizza', 'cheese', 7.75]
r.add_tuple ['Chicago Pizza', 'supreme', 8.5]
r.add_tuple ['Dominos', 'cheese', 9.75]
r.add_tuple ['Dominos', 'mushroom', 11]
r.add_tuple ['Little Caesars', 'cheese', 7]
r.add_tuple ['Little Caesars', 'mushroom', 9.25]
r.add_tuple ['Little Caesars', 'pepperoni', 9.75]
r.add_tuple ['Little Caesars', 'sausage', 9.5]
r.add_tuple ['New York Pizza', 'cheese', 7]
r.add_tuple ['New York Pizza', 'pepperoni', 8]
r.add_tuple ['New York Pizza', 'supreme', 8.5]
r.add_tuple ['Pizza Hut', 'cheese', 9]
r.add_tuple ['Pizza Hut', 'pepperoni', 12]
r.add_tuple ['Pizza Hut', 'sausage', 12]
r.add_tuple ['Pizza Hut', 'supreme', 12]
r.add_tuple ['Straw Hat', 'cheese', 9.25]
r.add_tuple ['Straw Hat', 'pepperoni', 8]
r.add_tuple ['Straw Hat', 'sausage', 9.75]
end
Then, perform operations on them.
Say you wanted to find the names of all females that would be happy eating at Straw Hat. You would need to join all three relations, select tuples on the condition that gender = 'female' and pizzeria = 'Straw Hat'
, then project name
on to the resulting relation.
With Related, I could do:
joined_relations = people.natural_join(favorites).natural_join(menus)
happy_females = joined_relations.select do t
#Each tuple is passed to this block, and behaves like a hash
t[:gender] == 'female' && t[:pizzeria] == 'Straw Hat'
end
names = happy_females.project(:name)
puts names
This'll output:
Relation
 Name 
_________
 Amy 
 Hil 
Limitations
Be warned: not only is Related a work in progress, it's also meant as a fun side project.
First and foremost, relations are all anonymous. Therefore, you can't get the cross product of relations with any matching attributes. Make sure to rename those first (natural_join
takes care of that for you).
While I tried to grab any lowhanging performance fruit, performamce and efficiency hasn't been focused on. Think twice before using this on relations thousands of tuples big.
Todo
 More Operations
 Theta Joins
 Semi Joins
 Division
 Outer Joins?
 Easier to Import/Export Data
 Read/Write CSV?
 Better DSL
 particularly for defining Relations
Contributing
Thetajoins, Semijoins, division, outer joins... There's plenty left that can be implemented for convenience and illustration purposes. There's also plenty of refactoring that can be done, as well as the limitations above that can be addressed. Feel free to open an issue if something is important to you, or submit pull requests and I'll happily review them.
I try to stay consistent with these style guides, but there's always room for improvement!