Java memory efficiency and column-oriented data

bearophile bearophileHUGS at
Thu Feb 2 16:21:22 PST 2012

Through Reddit I've found this good and long slides pack, it's about using Java data structures to increase memory efficiency of programs:$FILE/oopsla08%20memory-efficient%20java%20slides.pdf

Despite the D situation is different (there are structs as in C#), it will be good to have weak and soft references in Phobos, and to have better memory analysis tools outside Phobos.

The slides have reminded me my desire of a column-oriented "struct array" in Phobos (some time ago someone has written a minimal version for D1).

The usage is simple:

import std.stdio, std.conv;

struct Foo { // an example struct
    int x;
    float y;
    string s;

    this(int xx, float yy) {
        x = xx;
        y = yy;
        s = text(x);

    float sum() {
        return x + y;

void main() {
    auto a1 = new Foo[1000]; // normal not parallel array
    foreach (ref Foo f; a1)
        writeln(f.s, " ", f.sum());

    // default usage example of ParallelArray
    // 3 Foo fields stored as 3 separated arrays inside a2
    ParallelArray!Foo a2; // valid
    static assert(a2[0].sizeof == size_t.sizeof * 4); // 3 pointers + 1 length
    a2.length = 1000;
    foreach (ref Foo f; a2) // A f Foo is built on the fly
        writeln(f, " ", f.sum());
    a2[10] = Foo(1, 2, "1");
    foreach (x; a2.x_array) // x_array is a property slice
    foreach (y; a2.y_array)
    foreach (s; a2.s_array)

    // specialized usage example of ParallelArray
    // x,y fields stored as an array, s field as another array
    ParallelArray!(Foo, "x y # s") a3; // valid
    static assert(a3[0].sizeof == size_t.sizeof * 3); // 2 pointers + 1 length
    a3.length = 1000;
    foreach (ref Foo f; a3) // A f Foo is built on the fly
        writeln(f, " ", f.sum());
    a3[10] = Foo(1, 2, "1");
    foreach (xy; a3.x_y_array)
        writeln(xy.x, " ", xy.y);
    foreach (s; a3.s_array)

    // float z0 = a3.x_y_array[10].sum(); // invalid code
    ParallelArray!(Foo, "x # y # s") a4; // valid code
    // ParallelArray!(Foo, "x y # s x") a5; // invalid, dupe field x
    // ParallelArray!(Foo, "x # y") a6; // invalid, s field missing
    // so if you give a string with the field names, you need to
    // list them all, and only once each. Other designs are possible
    // but this is the simplest to use and implement.

    float z1 = a3[10].sum(); // a3[10] returns a Foo
    // a3(10) doesn't create a Foo, it just fetches what
    // .sum() needs, so it's faster if you have to call .sum()
    // on many records.
    // so the calls to sum() are implemented at compile-time
    float z2 = a3(10).sum();

    // To keep design simple. ParallelArray can't create 2D arrays

Do you like?
I have several usages of such struct in my code.


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