MarginaliaSearch/code/libraries/btree
Viktor Lofgren 1d34224416 (refac) Remove src/main from all source code paths.
Look, this will make the git history look funny, but trimming unnecessary depth from the source tree is a very necessary sanity-preserving measure when dealing with a super-modularized codebase like this one.

While it makes the project configuration a bit less conventional, it will save you several clicks every time you jump between modules.  Which you'll do a lot, because it's *modul*ar.  The src/main/java convention makes a lot of sense for a non-modular project though.  This ain't that.
2024-02-23 16:13:40 +01:00
..
java/nu/marginalia/btree (refac) Remove src/main from all source code paths. 2024-02-23 16:13:40 +01:00
test/nu/marginalia/btree (refac) Remove src/main from all source code paths. 2024-02-23 16:13:40 +01:00
build.gradle (refac) Remove src/main from all source code paths. 2024-02-23 16:13:40 +01:00
readme.md Update readme.md 2023-03-20 16:39:15 +01:00

BTree

This package contains a small library for creating and reading a static b-tree in as implicit pointer-less datastructure. Both binary indices (i.e. sets) are supported, as well as arbitrary multiple-of-keysize key-value mappings where the data is interlaced with the keys in the leaf nodes. This is a fairly low-level datastructure.

The b-trees are specified through a BTreeContext which contains information about the data and index layout.

The b-trees are written through a BTreeWriter and read with a BTreeReader.

Demo

BTreeContext ctx = new BTreeContext(
        4,  // num layers max
        1,  // entry size, 1 = the leaf node has just just the key
        BTreeBlockSize.BS_4096); // page size

// Allocate a memory area to work in, see the array library for how to do this with files
LongArray array = LongArray.allocate(8192);

// Write a btree at offset 123 in the area
long[] items = new long[400];
BTreeWriter writer = new BTreeWriter(array, ctx);
final int offsetInFile = 123;

long btreeSize = writer.write(offsetInFile, items.length, slice -> {
    // here we *must* write items.length * entry.size words in slice
    // these items must be sorted!!

    for (int i = 0; i < items.length; i++) {
        slice.set(i, items[i]);
    }
});

// Read the BTree

BTreeReader reader = new BTreeReader(array, ctx, offsetInFile);
reader.findEntry(items[0]);

Useful Resources

Youtube: Abdul Bari, 10.2 B Trees and B+ Trees. How they are useful in Databases. This isn't exactly the design implemented in this library, but very well presented and a good refresher.