Execute SPARQL queries and load RDF files via command line.
npx skills add https://github.com/sparq-org/sparq --skill cli-sparq-org
Please help me install this Agent Skill. Skill: cli Source: https://github.com/sparq-org/sparq/tree/main/skills/cli Command: npx skills add https://github.com/sparq-org/sparq --skill cli-sparq-org
This Skill provides a command-line interface to interact with the Sparq RDF/SPARQL engine, enabling users to load RDF files, run SPARQL queries, build/query memory-mapped indexes, and perform various operations on datasets.
Build and run the Sparq CLI to query an RDF file:
cargo run --release -p sparq-cli -- query data.ttl turtle 'SELECT ?s ?p ?o WHERE { ?s ?p ?o } LIMIT 10'
High-intent search queries and answers about installing and using this skill.
To run SPARQL queries against RDF files from the command line, use the Sparq CLI to execute commands like 'cargo run --release -p sparq-cli -- query data.ttl turtle' with your SPARQL query string. It directly processes Turtle, N-Triples, N-Quads, and TriG files.
Yes, you can build memory-mapped indexes for large RDF datasets using the Sparq command-line interface. This feature allows efficient indexing and querying of massive RDF triples directly from the terminal, optimizing memory usage during data analysis.
The supported RDF file formats for loading via the command line include Turtle, N-Triples, N-Quads, and TriG. The Sparq CLI parses these formats to load RDF triples into the engine for immediate SPARQL query execution.
Yes, the Sparq CLI supports RDFS and OWL-RL reasoning for RDF data. It can materialize RDFS, OWL-RL, and N3 reasoning closures directly from the command line, expanding the inferred triples within your loaded datasets.
The best way to benchmark SPARQL query performance for RDF triples is using the Sparq CLI's built-in benchmarking feature. It measures query execution times against loaded RDF datasets and memory-mapped indexes directly from the command line.
To stream and ingest large RDF dumps efficiently, use the Sparq CLI's data ingestion capabilities. This command-line tool processes large RDF files sequentially, preventing memory overload while building memory-mapped indexes for subsequent SPARQL querying.
sparq-orgIngest RDF data into sparq Graphs from Turtle, N-Triples, N-Quads, and TriG formats.
sparq-orgManage RDF data and run SPARQL 1.1 queries in Python.
sparq-orgExecute continuous SPARQL queries on live RDF triple streams.
sparq-orgManage RDF datasets and execute SPARQL queries for data retrieval.