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This was caused by a bug in the binary search algorithm causing it to sometimes return positive values when encoding a search miss. It was also necessary to get rid of the vestiges of the old LongArray and IntArray classes to make this fix doable. |
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| build.gradle | ||
| readme.md | ||
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.