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  • High-Performance Primitive Collections

    In Kotlin primitive types such as Int or Double correspond to high-performant Java primitive types such as int or double. But nullable (Int?) and generic (<Int>) versions of those types are mapped to boxed Java types such as Integer or Double.

    Boxed types have a serious impact on memory usage. Let’s make a simple comparison.

    @Test
fun `memory occupied by primitive int`() {
    data class A(
        val x: Int
    )

    val N = 100_000_000

    val mem1 = calculateOccupiedMemoryMB()

    val list = List(N) { A(it) }

    val mem2 = calculateOccupiedMemoryMB()

    println("Occupied memory: ${mem2 - mem1} MB")

    list
}

> Occupied memory: 1910 MB
    @Test
fun `memory occupied by boxed Int`() {
    data class A(
        val x: Int?
    )

    val N = 100_000_000

    val mem1 = calculateOccupiedMemoryMB()

    val list = List(N) { A(it) }

    val mem2 = calculateOccupiedMemoryMB()

    println("Occupied memory: ${mem2 - mem1} MB")

    list
}

> Occupied memory: 3436 MB

    We already see almost 2x difference, but actually it’s more serious as our test is not accurate enough.

    Now imagine we need a set of Int or a map of Int to Object. If we use standard Java collections we will get all the boxed type overhead because all Java collection types are generic.

    Fortunately there’re quite a lot of nice primitive collection implementations. After some research I sticked to HPPC: High Performance Primitive Collections.

    Let’s compare memory footprints of a normal Java HashSet of Int and an HPPC IntHashSet.

    @Test
fun `memory occupied by HashSet`() {
    val N = 100_000_000

    val mem1 = calculateOccupiedMemoryMB()

    val set = hashSetOf<Int>()
    repeat(N) { set.add(it) }

    val mem2 = calculateOccupiedMemoryMB()

    println("Occupied memory: ${mem2 - mem1} MB")

    1 in set
}

> Occupied memory: 5098 MB
    @Test
fun `memory occupied by HashSet`() {
    val N = 100_000_000

    val mem1 = calculateOccupiedMemoryMB()

    val set = IntHashSet()
    repeat(N) { set.add(it) }

    val mem2 = calculateOccupiedMemoryMB()

    println("Occupied memory: ${mem2 - mem1} MB")

    1 in set
}

> Occupied memory: 518 MB

    10x less memory used!