Java memory efficiency and column-oriented data

[bcs]

On 02/02/2012 04:21 PM, bearophile wrote:
> Through Reddit I've found this good and long slides pack, it's about using Java data structures to increase memory efficiency of programs:
>
> http://domino.research.ibm.com/comm/research_people.nsf/pages/sevitsky.pubs.html/$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

Ideally this shouldn't require the property. The "natural" or auto type 
for iterating a ParallelArray should be a proxy value that defines 
properties for all the members and looks them up on demand. It would 
just need two words, a pointer to the parent ParallelArray and an index 
into it.

>          writeln(x);
>      foreach (y; a2.y_array)
>          writeln(y);
>      foreach (s; a2.s_array)
>          writeln(s);
>
>      // 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)
>          writeln(s);
>
>      // 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.
>
> Bye,
> bearophile