This commit introduces sparse index support for KDI files to enable fast random access during k-mer matching. It adds a new .kdx index file format and updates the KDI reader and writer to handle index creation and seeking. The changes include:
- New KdxIndex struct and related functions for loading, searching, and writing .kdx files
- Modified KdiReader to support seeking with the new index
- Updated KdiWriter to create .kdx index files during writing
- Enhanced KmerSetGroup.Contains to use the new index for faster lookups
- Added a new 'match' command to annotate sequences with k-mer match positions
The index is created automatically during KDI file creation and allows for O(log N / stride) binary search followed by at most stride linear scan steps, significantly improving performance for large datasets.
Refactor k-mer index building to use the new disk-based KmerSetGroupBuilder instead of the old KmerSet and FrequencyFilter approaches. This change introduces a more efficient and scalable approach to building k-mer indices by using partitioned disk storage with streaming operations.
- Replace BuildKmerIndex and BuildFrequencyFilterIndex with KmerSetGroupBuilder
- Add support for frequency filtering via WithMinFrequency option
- Remove deprecated k-mer set persistence methods
- Update CLI to use new builder approach
- Add new disk-based k-mer operations (union, intersect, difference, quorum)
- Introduce KDI (K-mer Delta Index) file format for efficient storage
- Add K-way merge operations for combining sorted k-mer streams
- Update documentation and examples to reflect new API
This refactoring provides better memory usage, faster operations on large datasets, and more flexible k-mer set operations.