Introduces a new `merge` CLI subcommand and underlying implementation to consolidate multiple pre-indexed k-mer indexes into a single output. Adds `append_column` methods to persistent bit and int matrices to enable incremental genome column expansion without rebuilding the MPHF. Includes new error variants for index readiness and configuration mismatches, adds a `--force` flag to the index command, and updates documentation and navigation structure accordingly.
5.5 KiB
Merge command
Purpose
obikmer merge combines multiple existing kmer indexes into a single index. The result contains all kmers from all sources, with per-genome presence/absence or count data for every genome across every layer.
Modes
pub enum MergeMode { Presence, Count }
Default mode is Presence. Count mode requires all source indexes to have with_counts=true; mixing count and non-count sources is rejected at validation.
| Mode | Column type | Constraint |
|---|---|---|
Presence |
PersistentBitMatrix (one bit per genome per slot) |
none |
Count |
PersistentCompactIntMatrix (one u32 per genome per slot) |
all sources with_counts=true |
Input / output constraints
All source indexes must satisfy:
IndexState::Indexed(fully built —index.donesentinel present)- Same
kmer_size,minimizer_size,n_bits - If
Countmode: all sources must havewith_counts=true
--force: if the output directory already exists, it is deleted before the merge begins.
Algorithm
1. Validation
Check all sources against the constraints above. Abort on any mismatch.
2. Bootstrap output from first source
Recursive file copy of sources[0] → output. This establishes the partition layout, all existing MPHFs, unitigs, and evidence files. The first source's genome is genome 0 in the output.
3. For each subsequent source (parallel across partitions)
For each partition, process one source at a time sequentially:
a. Classify kmers
Iterate all kmers in the source partition (via UnitigFileReader + canonical kmer iteration). For each kmer, probe the destination LayeredMap<()>:
- Hit
(dst_layer, slot): record(dst_layer, slot, value)wherevalueis the source count (Count mode) or1(Presence mode). - Miss: add kmer to a
GraphDeBruijnaccumulator; record its value in aHashMap<CanonicalKmer, Vec<u32>>.
b. Extend existing layers
For each existing layer in the destination partition, call append_genome_column once per source genome being merged. Slots that received a hit are populated with their recorded value; all other slots receive 0 (absent).
If this is the first merge and operating in Presence mode, call Layer<()>::init_presence_matrix before appending any source column. This creates presence/ with col_000000.pbiv set all-true (genome 0 is present in every slot of this layer).
c. Build new layer for new kmers
If the GraphDeBruijn accumulator is non-empty (misses exist), write compact unitigs from the de Bruijn graph, then call the appropriate Layer::build variant. Before appending the source's own column, prepend n_existing_genomes absent columns (value 0) — one per genome already in the index — so the column count invariant holds immediately after layer creation.
d. Update partition metadata
Write updated meta.json with the incremented n_layers if a new layer was added.
4. Update index metadata
Append the merged source's genome label(s) to index.meta.genomes. Write updated index.meta.
Column count invariant
After any merge, every layer in every partition has exactly n_genomes columns, where n_genomes is the total genome count in the index at that point.
This is maintained by three mechanisms:
- Existing layers: one column appended per source genome (
append_genome_column). - New layers created during merge:
n_existing_genomesabsent columns prepended before the source's own column. - First merge, Presence mode:
init_presence_matrixretroactively createspresence/col_0all-true for genome 0 before any source column is appended.
The invariant is a precondition of the LayeredStore aggregation traits: col_weights() and all partial distance methods assume every inner store has the same column count.
New layer construction
All kmers absent from the destination index — across all sources being merged — accumulate into a single GraphDeBruijn per partition. One new layer is built from this graph, not one layer per source. This keeps the layer count bounded and preserves compact unitig representation.
De Bruijn reconstruction ensures that overlapping k-1 suffixes/prefixes from different source kmers are merged into minimal unitigs before MPHF construction.
On-disk impact
After merging G genomes (1 existing + G-1 new sources):
partitions/
part_00000/
index/
meta.json ← n_layers updated if new layer added
layer_0/
mphf.bin ← unchanged (MPHF immutable)
unitigs.bin ← unchanged
evidence.bin ← unchanged
presence/ ← created on first merge (Presence mode)
meta.json {"n": N, "n_cols": G}
col_000000.pbiv ← all-true (genome 0)
col_000001.pbiv ← source 1 presence
...
counts/ ← extended (Count mode)
meta.json {"n": N, "n_cols": G}
col_000000.pciv ← genome 0 counts (from original build)
col_000001.pciv ← source 1 counts
...
layer_1/ ← new layer (if new kmers found)
mphf.bin
unitigs.bin
evidence.bin
presence/ or counts/
meta.json {"n": N1, "n_cols": G}
col_000000.pbiv ← all-false (genome 0 absent from this layer)
...
col_000001.pbiv ← source 1 presence in this new layer
The index.meta genome list grows from 1 entry to G entries after all sources are merged.