sparq

Use when turning a sparq contribution into an academic paper — identifying a genuinely-novel contribution (the re-runnable intake), classifying it and picking a venue (ISWC/ESWC Resource for the engine, PVLDB/SIGMOD/EDBT for DB-systems, arXiv/workshop for not-yet-sound ZK/MPC), drafting a single-source Typst (.typ) paper whose eval section binds to live benchmark data via --input/sys.inputs, building both a PDF and an in-site HTML page from that one source, and reviewing claims↔evidence under sparq's empirical-honesty mandate (canonical vs indicative numbers; the ZK/MPC not-yet-sound disclaimer). The paper-factory for epic sq-gum8.

Graph-level Solid-style access control over a sparq RDF dataset with the opt-in sparq-solid crate: store pods as named-graph-per-document, keep WAC (.acl) / ACP (.acr) documents as queryable triples, materialize their semantics to a queryable authorization view (urn:sparq:auth) via N3 rules, then filter every SPARQL query/update per (WebID, client, issuer) session to the authorized graph set — fail-closed. Use when gating which named graphs a session may read/append/write, mapping WAC/ACP to an allow-deny model, or querying the materialized auth view. RESEARCH/architecture track — this is the authorization LAYER, NOT a production Solid Pod HTTP server, and it does NOT authenticate (the caller asserts the WebID, client, and issuer).

Use when you need to drive the sparq RDF/SPARQL engine from the command line — load a Turtle/N-Triples/N-Quads/TriG (or HDT) file and run a SPARQL query, build/query memory-mapped on-disk indexes for datasets larger than RAM, materialize RDFS/OWL-RL/N3 reasoning closures, stream-ingest huge gzip/bzip2/zstd dumps, or benchmark query suites. Covers the actual `sparq-cli` subcommands, positional argument order, and cargo feature flags.

Parse and load RDF into a sparq Graph (Turtle/N-Triples/N-Quads/TriG via sparq-core, and HDT incl. compressed .hdt.gz/.hdt.zst/.hdt.bz2 via sparq-hdt), do streaming/parallel/external-memory ingest of compressed dumps, and take cheap immutable copy-on-write Graph snapshots. Use when ingesting RDF files, choosing a loader, wiring HDT, or snapshotting a graph for serving.

Cost-based federated SPARQL source selection + bind-vs-hash join planning over already-fetched source descriptors, plus an ANAPSID-style non-blocking streaming join with operator spill, via the opt-in sparq-fedplan crate. Use when planning a federated BGP across multiple SPARQL endpoints from their served statistics (VoID property/class partitions + mined scs: characteristic sets): deciding which sources can contribute to each triple pattern (HiBISCuS recall-safe pruning + CostFed skew-aware cardinality), choosing a join order with per-join bind-vs-hash-vs-streaming algorithm selection (characteristic-set star cardinality for intermediate sizes), and executing a memory-bounded non-blocking symmetric hash join over incrementally-arriving sub-results (StreamJoin, spill to a backing store, result multiset-equal to a blocking join). Pure + deterministic planning, no network I/O. Off by default; does not touch sparq-core/sparq-engine's lean build. Also covers live adaptive RE-planning at stage boundaries (mid-execution plan switching when observed cardinalities diverge from estimates, or when a source is observed to be slow — per-source EWMA-smoothed latency is folded into the cost model as a documented heuristic bias toward faster sources, smoothing out transient spikes) via the further opt-in adaptive-replan feature (AdaptiveExecutor) — sound because BGP join is order-independent (latency changes ordering/cost only, never results), with mid-operator swap + live source failover deferred.