A monadic library to resolve object relations with the aim of avoiding the N+1 query problem.
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README.md

bullet Build Status Coverage status Maven Central Scaladoc

A monadic library to resolve object relations with the aim of avoiding the N+1 query problem. The solution requires only pure computations in Scala depending on neither database implementations nor any other frameworks.

Getting started

Add dependency in your build.sbt as the following.

    libraryDependencies ++= Seq(
      "com.github.tarao" %% "bullet" % "0.0.2"
    )

The library is available on Maven Central. Currently, supported Scala version is 2.11.

Overview

The problem

Assume that you have Car and Engine classes and, if Car has an Engine, it is resolved by a type class method toEngine.

type CarId = Long
type EngineId = Long

case class Car(id: CarId)
case class Engine(id: EngineId, carId: CarId)

implicit class CarRelation(val car: Car) extends AnyVal {
  def toEngine: Option[Engine] = ...
}

It is quite usual to implement toEngine method by using a repository which issues a DB query.

implicit class CarRelation(val car: Car) extends AnyVal {
  def toEngine: Option[Engine] = EngineRepository.findByCarId(car.id)
}

val db = ...
object EngineRepository {
  def findByCarId(carId: CarId): Option[Engine] = db.run {
    sql"SELECT * FROM engine WHERE car_id = $carId LIMIT 1".as[Engine]
  }.headOption
}

There is no problem when you resolve an Engine from a Car. In this case, a SELECT query is executed internally.

val car: Car = Car(1234L)
val engine: Option[Engine] = car.toEngine
// SELECT * FROM engine WHERE car_id = 1234 LIMIT 1

If you have multiple Cars and want to get their Engines, you may want to write like this.

val cars: Seq[Car] = Seq(Car(1L), Car(2L), Car(3L), ...)
val engines: Seq[Engine] = cars.map(_.toEngine).flatten
// SELECT * FROM engine WHERE car_id = 1 LIMIT 1
// SELECT * FROM engine WHERE car_id = 2 LIMIT 1
// SELECT * FROM engine WHERE car_id = 3 LIMIT 1
// ...

Yes, it works. But there is a problem that the SELECT query is executed for each id of the element of cars. When you have hundreds or thousands of cars, it is likely to be a perfomance issue.

One way to solve this problem is to JOIN tables. When you instantiate Cars from car table in your DB, engine table might also be INNER JOINed. This is a quite common solution but not the best one. If you have for example Wheels, a Bumper, and Doors for a Car, you will soon need to JOIN them all but not all of them are needed every time. You will have to write instantiation methods with ugly JOIN queries for each combination of parts that you need.

Ideally, it would be nice if the last expression executes a single SELECT query.

val engines: Seq[Engine] = cars.map(_.toEngine).flatten
// SELECT * FROM engine WHERE car_id IN (1, 2, 3, ...)

Is this possible? In Scala, yes, it is.

Our solution

All you have to do is to replace toEngine method to return an instance of a monad created by HasA.Monadic with an instance of HasA[Car, Engine], which describes how to resolve Engines from Cars.

import com.github.tarao.bullet.HasA

implicit class CarRelation(val car: Car) extends AnyVal {
  def toEngine = HasA.Monadic(car, hasEngine)
}
val hasEngine: HasA[Car, Engine] = ...

The usage of toEngine is quite the same except that (1) you have to write a type of return value (Option[Engine] or Seq[Engine] in this case), (2) you don't need to flatten anymore.

import com.github.tarao.bullet.Implicits._

val car: Car = ...
val engine: Option[Engine] = car.toEngine

val cars: Seq[Car] = ...
val engines: Seq[Engine] = cars.map(_.toEngine)

The implementation of hasEngine should resolve Engines from Cars in a single query. HasA[Car, Engine] has an interface for that named map(), whose type is Seq[Car] => Seq[Engine]. Then the implementation whould be the following.

val hasEngine: HasA[Car, Engine] = new HasA[Car, Engine] {
  def map(cars: Seq[Car]): Seq[Engine] = db.run {
    sql"SELECT * FROM engine WHERE car_id IN (${cars.map(_.id)})".as[Engine]
  }
}

Note that map() method is used for resolving both Option[Engine] and Seq[Engine]. In our example, toEngine results in executing a SELECT-WHERE-IN query in the both cases.

val car: Car = Car(1234L)
val engine: Option[Engine] = car.toEngine
// SELECT * FROM engine WHERE car_id IN (1234L)

val cars: Seq[Car] = Seq(Car(1L), Car(2L), Car(3L), ...)
val engines: Seq[Engine] = cars.map(_.toEngine)
// SELECT * FROM engine WHERE car_id IN (1, 2, 3, ...)

How does it work?

The key mechanism is a monad, which is a return value of toEngine. In the last example, we receive a monad as a variable of type Option[Engine] or Seq[Engine]. This is actually an implicit conversion. If we make it explicit, the example looks like this.

val car: Car = ...
val engine: Option[Engine] = car.toEngine.run

val cars: Seq[Car] = ...
val engines: Seq[Engine] = cars.map(_.toEngine).run

It is run() which actually calls HasA[].map(). Until then, the invocation of HasA[].map() is postponed inside the monad. If the receiver of run() is a list of monads, it will organize them into an argument of a single invocation of HasA[].map(). (You may wonder how it is possible since each monad value has its own instance of HasA[]. It is actually only the first one in the list to be used.)

Why is it a monad?

The above story does not describe the way using our monad as a monad. Actually, it is not necessarily a monad as long as it is some kind of a deferred object. It is a monad just for convenience.

Let's see an example. Suppose that an Engine has its Crankshaft and there is a type class method toCrankshaft defined in the same way as toEngine. If we don't have the monadic feature, we need to look up a Crankshaft of a Car via an Engine in the way like this.

val car: Car = ...
val engine: Option[Engine] = car.toEngine
val crankshaft: Option[Crankshaft] =
  engine.map(_.toCrankshaft: Option[Crankshaft]).flatten

If we use the monadic feature, it can be written like this.

val car: Car = ...
val crankshaft: Option[Crankshaft] = for {
  e <- car.toEngine
  c <- e.toCrankshaft
} yield(c)

This is much easier to read especially when you need a complex operation on e and/or c.

Has-a relation

As you have seen in the overview, only things you have to do are to implement HasA[].map() and to provide a monad factory using it.

Summary

  • Extend HasA[From, To] and implement map: Seq[From] => Seq[To].
  • Provide a monad factory which returns HasA.Monadic(from, hasA) where:
    • from is an instance of From
    • hasA is an instance of HasA[From, To]

Has-many relation

You can specify a list type as To type argument of HasA[From, To]. In this case, you can resolve a single value as a Seq[_] instead of Option[Seq[_]], or multiple values as a Seq[_] instead of Seq[Seq[_]]. For example, if you have HasA[Car, Seq[Wheel]] and toWheels returns a monad, then these can be used as the following.

val car: Car = ...
val wheels: Seq[Wheel] = car.toWheels
val cars: Seq[Car] = ...
val totalWheels: Seq[Wheel] = cars.map(_.toWheels)

Summary

  • The same as HasA[From, To] but To is a list type
  • The result can be flattened automatically

Joining related objects

Sometimes you may want to merge related two objects into one. For example, if you have Cars and their Engines, you may want to have values of CarWithEngines where those are merged. To do this, you can use another interface Join.Monadic to define a type class method withEngine.

import com.github.tarao.bullet.Join

type CarWithEngine = (Car, Engine)

implicit class CarRelation(val car: Car) extends AnyVal {
  def withEngine = Join.Monadic(car, joinEngine)
}

type JoinEngineToCar = Join[CarWithEngine, CarId, Car, Engine]
val joinEngine: JoinEngineToCar = new JoinEngineToCar {
  def map(cars: Seq[Car]): Seq[Engine] = ... // the same as HasA[Car, Engine]
  def leftKey(car: Car): CarId = car.id
  def rightKey(engine: Engine): CarId = engine.carId
  def merge(car: Car, engine: Engine): CarWithEngine = (car, engine)
}

This time you have four methods to implement. map(), leftKey(), rightKey() and merge(). map() is the same as in HasA[Car, Engine]. leftKey() and rightKey() provides how you associate one object to another. In this case, a Car and its Engine should share their CarId. associated objects are passed to merge().

The usage is quite similar to toEngine.

val car: Car = ...
val enginedCar: Option[CarWithEngine] = car.withEngine

val cars: Seq[Car] = ...
val enginedCars: Seq[CarWithEngine] = cars.map(_.withEngine)

Summary

  • Extend Join[Result, Key, Left, Right] and implement four methods:
    • map: Seq[Left] => Seq[Right]
    • leftKey: Left => Key
    • rightKey: Right => Key
    • merge: (Left, Right) => Result
  • Provide a monad factory which returns Join.Monadic(left, join) where:
    • left is an instance of Left
    • join is an instance of Join[Result, Key, Left, Right]

Default values

An Option[] return value of run() may be None if HasA[].map() returns an empty list. In this case, you can provide a default value to ensure having some value returned. This is done by providing an implicit value of Monad.Default[]. If you provide a default value, the return value can be received without being wrapped by Option[]. For example, the following code defines a default value for an Engine.

implicit val defaultEngine: Monad.Default[Engine] =
  Monad.Default[Engine](Engine(0L, 0L))

val car: Car = ...
val engine: Engine = car.toEngine

In this case, note that the implicit value must be visible in the scope where the invocation of run() or the implicit conversion occurs.

For Join[], you should be careful that you have two choices of types to provide a default value, either Result or Right of Join[Result, Key, Left, Right]. If you provide a default value for Result, then you will always get a value by run() on a single monad but still get some values lacked by run() on multiple monads. You should provide a default value for Right to avoid this. In this time, the implicit value must be visible in the scope where the invoction of Join.Monadic() occurs.

An implicit conversion vs. an explicit run

You may think that resolving object relations on an implicit conversion is too aggressive. There is a way not to allow implicit conversions and force explicit run()s instead. Only you have to do is not to import com.github.bullet.Implicits._. Other things will work fine without this.

License

  • Copyright (C) INA Lintaro
  • MIT License