vcf-rdfizer 2.0.0

VCF-RDFizer is a Docker-first CLI wrapper for:

1. VCF -> RDF (N-Triples) with RMLStreamer
2. Optional RDF compression/decompression

The VCF-RDFizer vocabulary is available at https://w3id.org/vcf-rdfizer/vocab#.

Requirements

• Python 3.10+
• Docker (installed and running)

Install options:

pip install vcf-rdfizer

or

pipx install vcf-rdfizer

or

conda install -c conda-forge vcf-rdfizer

or pull the prebuilt Docker image directly:

docker pull ecrum19/vcf-rdfizer:latest

Release maintainers: see RELEASING.md for the PyPI, Docker Hub, and conda-forge release procedure.

Important CLI Rule

--out is required for all modes.

This is the run output root directory. VCF-RDFizer places:

• final RDF/compression outputs
• run metrics/logs
• hidden intermediates

inside this directory.

Modes

• full: VCF -> TSV -> RDF -> compression
• tsv: VCF -> TSV only (benchmarking)
• compress: compress an existing .nt or .nt.gz
• decompress: decompress .nt.gz, .nt.br, or .hdt
• index: eagerly initialize HDT Java's versioned .hdt.index.* sidecar for an existing .hdt

In full mode with multiple VCF inputs, failures are isolated per input:

• the run continues with remaining files
• failed inputs are summarized in run_metrics/<RUN_ID>/failed_inputs.csv

Main Flags (Most Used)

• -m, --mode {full,compress,decompress,tsv,index}
• -o, --out required output root directory
• --rdf-compression final raw RDF codecs: gzip, brotli, or none
• --representations queryable RDF outputs: hdt, cottas, or none
• --artifact-compression packaging codecs for selected representations: gzip, brotli, or none
• --hdt-strategy {auto,partitioned,single} HDT generation policy
• --chunk-target-bytes, --chunk-min-bytes, --chunk-max-bytes shared record-safe chunk sizing
• -I, --image Docker image repo (default ecrum19/vcf-rdfizer)
• -v, --image-version Docker tag/version
• -b, --build force Docker build
• -B, --no-build fail if image not found
• -h, --help show full usage

Compression Plan

Compression is configured as three independent decisions:

1. RDF staging: --rdf-storage-mode controls how RMLStreamer output is assembled before chunking. plain creates one .nt aggregate; space-optimized streams the parts into one .nt.gz aggregate and removes each source part immediately.
2. Raw RDF artifacts: --rdf-compression gzip,brotli creates compressed copies of the RDF aggregate. Use --rdf-compression none when RDF is only a temporary input to HDT/COTTAS.
3. Queryable representations and packaging: --representations hdt,cottas creates the selected indexed formats. --artifact-compression gzip,brotli packages each selected representation, producing .hdt.gz, .hdt.br, .cottas.gz, or .cottas.br in addition to the queryable base artifact.

Each selector accepts comma-separated values. Use none by itself to disable that stage; do not combine none with another value. --artifact-compression requires at least one selected value in --representations.

The gzip used by --rdf-storage-mode space-optimized is staging storage; it is not automatically a final raw RDF artifact. The default plan preserves the historical outputs: --rdf-compression gzip,brotli and --representations hdt. For the smallest final output, select --rdf-compression none, one representation, and --remove-rdf-storage-output.

Packaged .hdt.gz, .hdt.br, .cottas.gz, and .cottas.br files are archives, not directly queryable indexed files. Keep the unwrapped .hdt/.cottas file when queries must run without a decompression step.

Full Mode Flags

• -i, --input required VCF file or directory
• -r, --rules mapping rules file (.ttl)
  • default: rules/default_rules.ttl
• --rdf-storage-mode {plain,space-optimized} required full-mode aggregate storage policy
  • plain: merge RMLStreamer parts into one uncompressed .nt
  • space-optimized: gzip each part into one .nt.gz aggregate and delete the source part immediately
• --rdf-compression {gzip,brotli,none} raw RDF artifacts to retain
• --representations {hdt,cottas,none} queryable primary representations
• --artifact-compression {gzip,brotli,none} optional packaging applied to each selected representation
• --hdt-strategy {auto,partitioned,single}
  • auto: in full mode, build smaller HDT chunks and merge them with HDTCat
  • partitioned: always use chunked HDT generation for HDT-based methods
  • single: always use one rdf2hdt run per RDF input
  • with space-optimized, use auto or partitioned; single cannot consume the gzip stream without expanding it
• --chunk-target-bytes target uncompressed bytes per HDT/COTTAS chunk
• --chunk-min-bytes minimum uncompressed bytes before flushing a chunk group
• --chunk-max-bytes maximum uncompressed bytes in a chunk; boundaries remain on complete NT lines
• -P, --spark-partitions optional Spark partition hint (positive integer)
  • low-cost way to tune RMLStreamer parallelism while the wrapper still produces one aggregate RDF output
• -k, --keep-tsv keep hidden TSV intermediates
• -R, --keep-rmlstreamer-rdf-output keep the aggregate RDF output produced by RMLStreamer
• --remove-rdf-storage-output explicitly remove the aggregate .nt/.nt.gz after successful compression
• -e, --estimate-size preflight size estimate

TSV Mode Flags

• -i, --input required VCF file or directory
• Outputs per-run benchmark summary in run_metrics/<RUN_ID>/tsv_metrics.csv
• Raw TSV timing + artifact JSON per input in run_metrics/<RUN_ID>/raw_metrics/tsv_*

Compression Mode Flags

• --rdf required input .nt or .nt.gz file

Decompression Mode Flags

• -C, --compressed-input required .nt.gz, .nt.br, or .hdt
• -d, --decompress-out optional explicit output .nt path (must be inside --out)

HDT Index Mode Flags

• -H, --hdt required existing .hdt file
• HDT Java 3.0.10 generates an HDT v1-1 index named <file>.hdt.index.v1-1.
• The operation is also run automatically after each partitioned HDT merge.

Quick Start

Show help:

vcf-rdfizer --help

Full pipeline (plain aggregate RDF):

vcf-rdfizer \
  --mode full \
  --input ./vcf_files \
  --rdf-storage-mode plain \
  --rdf-compression none \
  --representations none \
  --out ./results

Full pipeline (plain aggregate, chunked HDT + HDTCat merge):

vcf-rdfizer \
  --mode full \
  --input ./vcf_files \
  --rdf-storage-mode plain \
  --rdf-compression none \
  --representations hdt \
  --hdt-strategy partitioned \
  --chunk-target-bytes 536870912 \
  --chunk-min-bytes 134217728 \
  --chunk-max-bytes 1073741824 \
  --out ./results

Full pipeline (space-optimized aggregate with shared HDT and COTTAS chunks):

vcf-rdfizer \
  --mode full \
  --input ./vcf_files \
  --rdf-storage-mode space-optimized \
  --rdf-compression none \
  --representations hdt,cottas \
  --chunk-target-bytes 536870912 \
  --chunk-min-bytes 134217728 \
  --chunk-max-bytes 1073741824 \
  --out ./results

Full pipeline with a Spark partition hint:

vcf-rdfizer \
  --mode full \
  --input ./vcf_files \
  --rdf-storage-mode space-optimized \
  --spark-partitions 8 \
  --rdf-compression none \
  --representations hdt \
  --out ./results

Full pipeline with custom rules + keep RMLStreamer RDF output:

vcf-rdfizer \
  --mode full \
  --input ./vcf_files \
  --rules ./rules/my_rules.ttl \
  --rdf-storage-mode plain \
  --rdf-compression brotli \
  --representations hdt \
  --keep-rmlstreamer-rdf-output \
  --out ./results

Ultra-small full pipeline:

vcf-rdfizer \
  --mode full \
  --input ./vcf_files \
  --rdf-storage-mode space-optimized \
  --rdf-compression none \
  --representations hdt \
  --hdt-strategy partitioned \
  --remove-rdf-storage-output \
  --out ./results

Queryable HDT and COTTAS plus gzip/Brotli packages:

vcf-rdfizer \
  --mode full \
  --input ./vcf_files \
  --rdf-storage-mode space-optimized \
  --rdf-compression none \
  --representations hdt,cottas \
  --artifact-compression gzip,brotli \
  --out ./results

TSV-only benchmark:

vcf-rdfizer \
  --mode tsv \
  --input ./vcf_files \
  --out ./results

Compression-only:

vcf-rdfizer \
  --mode compress \
  --rdf ./results/sample/sample.nt \
  --rdf-compression none \
  --representations hdt \
  --artifact-compression gzip \
  --out ./results

Compression-only from a space-optimized aggregate:

vcf-rdfizer \
  --mode compress \
  --rdf ./results/sample/sample.nt.gz \
  --rdf-compression none \
  --representations hdt,cottas \
  --chunk-target-bytes 536870912 \
  --out ./results

Decompression-only:

vcf-rdfizer \
  --mode decompress \
  --compressed-input ./results/sample/sample.hdt \
  --out ./results

Initialize an index for an existing HDT:

vcf-rdfizer \
  --mode index \
  --hdt ./results/sample/sample.hdt \
  --out ./results

Output Layout

Given --out ./results:

• final outputs:
  • ./results/<sample>/...
• per-run metrics/logs:
  • ./results/run_metrics/<RUN_ID>/...
• hidden intermediates:
  • ./results/.intermediate/tsv/

For an existing RDF input named test-larger.nt or test-larger.nt.gz, --mode compress --out ./results always uses one directory:

./results/test-larger/test-larger.hdt
./results/test-larger/test-larger.hdt.index.v1-1
./results/test-larger/test-larger.cottas
./results/test-larger/test-larger.nt.gz

The same basename rule applies in full mode. VCF-RDFizer performs an output collision check before Docker or conversion starts and never overwrites a planned artifact. Choose a new --out directory, or rename/remove the conflicting output before rerunning.

Intermediates are hidden by default. Raw RDF files are removed after successful compression by default. Use --remove-rdf-storage-output to make that cleanup explicit, or use --keep-rmlstreamer-rdf-output to retain the aggregate RDF output instead. The space-optimized mode retains the .nt.gz aggregate when gzip is selected because that file is the gzip artifact itself.

Metrics

For each run, VCF-RDFizer writes:

• run_metrics/<RUN_ID>/metrics.csv
• run_metrics/<RUN_ID>/wrapper_execution_times.csv
• run_metrics/<RUN_ID>/progress.log
• run_metrics/<RUN_ID>/hdt_index_metrics.json for standalone HDT index mode

Compression metrics now include per-method:

• wall_seconds_*
• user_seconds_*
• sys_seconds_*
• max_rss_kb_*

When HDT or COTTAS is selected, compression also validates the final base artifact before packaging or RDF cleanup. The validator reads the source triple count, streams the artifact back through the native decoder, and requires equal counts. HDT validation also initializes the versioned .hdt.index.* sidecar. Validation results and source_triples/decoded_triples are stored in the per-run compression JSON and in the HDT/COTTAS columns of metrics.csv. Compression fails closed if the artifact cannot be decoded or the counts do not match. In compression-only mode, the source count is obtained by a streaming fallback when no upstream conversion metrics are available.

For partitioned HDT/COTTAS runs, the final method metric reports one sample-level result, while raw metrics also include a sample-scoped __partitioned_compression__ artifact describing chunk conversion, merge rounds, and the generated chunk guide.

Metrics may use internal stage names such as hdt_gzip and cottas_brotli. These correspond to the public combination of --representations and --artifact-compression; users do not need to pass those compound names.

Chunked Compression

Full mode always uses one of the two aggregate storage modes. Both modes create one logical N-Triples aggregate. The space-optimized mode streams each RMLStreamer part through gzip and deletes that part before processing the next one, so it avoids retaining both the part files and a full uncompressed aggregate.

When HDT or COTTAS is selected, the aggregate is read sequentially and split into complete N-Triples records. The same temporary chunks are consumed by both converters before cleanup. HDT chunks are merged with HDTCat, the final HDT index is generated after merging through HDT Java's indexed search loader, and COTTAS chunks are merged with pycottas.cat, which rebuilds the query indexes for the merged representation.

After each final HDT/COTTAS base artifact is produced, VCF-RDFizer performs a streaming decode/count check. This verifies both readability and that the decoded artifact contains exactly the number of source triples. The check is performed before .hdt.gz, .hdt.br, .cottas.gz, or .cottas.br packaging, and before raw RDF cleanup.

Partitioned HDT/COTTAS compression runs in an ephemeral Docker-managed workspace. Temporary RDF chunks, COTTAS/DuckDB scratch data, intermediate representations, and merge files are not written to the output directory. After a successful or failed run, the temporary workspace is removed; only the selected final artifacts and normal run metrics remain on the host. Each COTTAS conversion and merge also receives a fresh container-local DuckDB workspace, which is removed as soon as that operation completes. This prevents state from one chunk being reused by another and requires no user configuration.

HDT Java 3.0.10 does not provide a standalone hdtGenerateIndex executable. VCF-RDFizer sends an exit command to the supported hdtSearch.sh launcher; this opens the HDT through mapIndexedHDT() without executing a data query and creates the sibling .hdt.index sidecar before the run is marked successful. For the pinned HDT Java 3.0.10 distribution, this is the HDT v1-1 sidecar <file>.hdt.index.v1-1; VCF-RDFizer reports the actual path in its metrics.

The record-safe chunk plan and per-stage timings are retained in the raw partitioned-compression metrics JSON for diagnostics. The temporary chunk files and guide are not retained as host files.

See COMPRESSION_CHANGELOG.md for the detailed implementation approach and operational constraints.

Rules

• default rules file: rules/default_rules.ttl
• rules guide: rules/README.md

Troubleshooting

If Docker permission issues occur, rerun with a Docker-allowed user (or configure Docker group/sudo access on your system).

If HDT compression fails on very large RDF files, use --rdf-storage-mode space-optimized or --rdf-storage-mode plain with --hdt-strategy partitioned, then lower --chunk-target-bytes and --chunk-max-bytes to reduce each converter's working set.

Safe termination:

• Press Ctrl+C to interrupt a run.
• The wrapper exits with code 130, writes progress to run_metrics/<RUN_ID>/progress.log, and performs best-effort cleanup of tracked intermediates.
• Raw RDF cleanup on interrupt follows --keep-rmlstreamer-rdf-output:
  • with --keep-rmlstreamer-rdf-output, raw RDF files are preserved
  • without it, tracked raw RDF files are removed during interrupt cleanup

Citation

If you use VCF-RDFizer in a publication, please cite:

VCF-RDFizer maintainers. (2026). VCF-RDFizer (Version 2.0.0) [Computer software]. GitHub. https://github.com/ecrum19/VCF-RDFizer

BibTeX:

@software{vcf_rdfizer_2026,
  author  = {{VCF-RDFizer maintainers}},
  title   = {VCF-RDFizer},
  year    = {2026},
  version = {2.0.0},
  url     = {https://github.com/ecrum19/VCF-RDFizer},
  note    = {Computer software}
}

You can also use the machine-readable citation file: CITATION.cff.

Contributing

Contributions are welcome. If you want to improve VCF-RDFizer:

• Open an issue first for bug reports, feature requests, or design changes.
• Fork the repo and create a feature branch from main.
• Keep changes focused and include/update tests for behavior changes.
• Run the unit tests locally before opening a PR:

python3 -m unittest discover -s test -p "test_*_unit.py" -q

• In your PR, include what changed, why it changed, and how you validated it.
• Use clear commit messages (for Docker publish control, include [publish-docker] only when intended).

Licensing

• Project license: LICENSE (MIT)
• Third-party runtime notices: THIRD_PARTY_NOTICES.md