Building Custom Collections

In this lesson, you will learn how to design custom collections that move beyond standard library defaults to achieve highly optimized, memory-efficient data layouts.

Why Build Custom Collections?

Standard collections like Vec<T> or HashMap<K, V> are general-purpose. They make trade-offs that might not suit your specific performance needs. When you are operating in memory-constrained environments or high-throughput systems, you may need to control exactly how memory is allocated, aligned, and packed. By building a custom collection, you can optimize the memory layout to be cache-friendly, minimize padding, or use specialized pointers for internal state.

Structuring for Memory Efficiency

To build a custom collection, you start by defining a structure that manages raw memory, typically using Unique<T> or a raw pointer to handle the allocation manually. Consider a scenario where you want a "Packed Stack" that avoids the heap overhead of Vec<T> by using a fixed-size buffer or a custom allocator.

use std::ptr::NonNull;
use std::alloc::{self, Layout};

pub struct TinyStack<T> {
    ptr: NonNull<T>,
    capacity: usize,
    len: usize,
}

impl<T> TinyStack<T> {
    pub fn new(capacity: usize) -> Self {
        let layout = Layout::array::<T>(capacity).unwrap();
        let ptr = unsafe { alloc::alloc(layout) as *mut T };
        
        TinyStack {
            ptr: NonNull::new(ptr).expect("Allocation failed"),
            capacity,
            len: 0,
        }
    }
}

The Role of Interior Mutability

When designing these containers, you often need to provide a public API that allows modification while upholding safety invariants. This is where Interior Mutability becomes essential. By wrapping your internal pointers in UnsafeCell<T>, you can allow mutation even when the container itself is shared via a reference. This enables you to build high-performance data structures—like lock-free queues or specialized ring buffers—that look immutable to the user but perform mutation safely under the hood.

Building a custom collection is essentially an exercise in data-oriented design. You are taking responsibility for the memory lifecycle, ensuring that your data fits perfectly into the CPU cache and that your pointer arithmetic is minimal and correct.

Key Takeaway: Building custom collections allows you to bypass general-purpose memory overhead by taking full control over allocation, alignment, and internal mutability patterns to suit your specific hardware constraints.