Sorting a 4.6 GB File with 500 Million Integers: Internal, Bitmap, and External Sorting Techniques

During an interview I was asked to sort a 4.6 GB file containing 500 million random integers, one per line.

First I tried internal sorting using a three‑way quicksort implementation in Java, with a cutoff to insertion sort for small sub‑arrays, and also a classic merge sort.

private final int cutoff = 8;
public
void perform(Comparable
[] a) {
    // quicksort implementation with cutoff
    // ...
}

These approaches quickly ran into stack‑overflow or out‑of‑memory problems because the whole file cannot be loaded into heap memory.

Next I implemented a bitmap sort that uses a BitSet to record the presence of each integer, reads the file sequentially, sets the corresponding bit, and finally writes the numbers back in order.

private BitSet bits;
public void perform(String largeFileName, int total, String destLargeFileName,
                    int readerBufferSize, int writerBufferSize, boolean asc) throws IOException {
    bits = new BitSet(total);
    // read each integer and set the bit
    Integer data;
    while ((data = largeIn.read()) != null) {
        bits.set(data);
    }
    // write out in order
    for (int i = 0; i < bits.size(); i++) {
        if (bits.get(i)) {
            largeOut.write(i);
        }
    }
}

The bitmap method finished in about 190 seconds (≈3 minutes) but still required a large amount of memory for the bit set.

Finally I applied external sorting: the file is split into many small sorted chunks that fit into a limited memory buffer, each chunk is sorted with the internal sorter and written to disk; then a multi‑way merge reads the heads of all chunks, repeatedly outputs the smallest current value, and refills the buffer from the corresponding chunk.

// Pseudo‑code for the merge phase
while (anyChunkHasData) {
    int min = min(currentHeadValues);
    output.write(min);
    advanceChunkContaining(min);
}

This external sort completed in about 771 seconds (≈13 minutes) and handled the full 5 billion‑number file without exceeding memory limits.

All code examples are written in Java and illustrate the trade‑offs between in‑memory, bitmap, and external sorting techniques for massive datasets.