Load Turtle from disk

One UDF reads a .ttl file off the server filesystem, parses it, dictionary-encodes every term, and inserts the resulting quads in batches.

What it does

pgrdf.load_turtle(path TEXT, graph_id BIGINT, base_iri TEXT DEFAULT NULL) → BIGINT

Reads the file at path (on the Postgres server's filesystem, not the client's), parses it as Turtle, normalises every term through the dictionary, and inserts the quads into the partition for graph_id. Returns the count of triples loaded.

The third argument is the optional base IRI used to resolve relative IRIs in the source document. Pass NULL (the default) when the file has no relative IRIs or sets its own @base.

Why you'd use it

• Project managers — stop scoping custom ETL for RDF. The entire FOAF / PROV-O / DCAT / SOSA / SHACL / OWL ontology set parses with one SQL statement.
• Data scientists — load production graphs into a real Postgres instance without leaving SQL.
• Ontologists — ingest the canonical Turtle releases of any W3C ontology without per-vocabulary tooling.

Example

-- Allocate a partition for graph 100.
SELECT pgrdf.add_graph(100);

-- Load FOAF — returns the triple count.
SELECT pgrdf.load_turtle('/fixtures/ontologies/foaf.ttl', 100);
--  → 631

-- Same call, with an explicit base IRI for relative-IRI resolution.
SELECT pgrdf.load_turtle(
  '/fixtures/ontologies/prov.ttl', 200,
  'http://www.w3.org/ns/prov#');
--  → 1789

For fast end-to-end profiling of an ingest run, use pgrdf.load_turtle_verbose — same loader, JSONB report instead of an integer.

How it works

Under the hood the loader streams Turtle through oxttl, interns terms via the shared-memory dictionary cache, and flushes quads in batches using a prepared INSERT statement (bulk ingest). The full pipeline is described in docs/02-storage.md and SPEC.pgRDF.LLD.v0.4.md §4.

Tests

• tests/regression/sql/20-load-turtle.sql — happy-path ingest contract.
• tests/regression/sql/81-error-paths.sql — locks the load_turtle: failed to open error prefix.
• tests/perf/smoke-ontologies.sh — 24 well-known ontologies → 17,134 triples, locked counts in smoke-ontologies.expected.tsv.

See also

• Inline Turtle ingest — for fixture data and orchestrated loads where the source is a string, not a file.
• Verbose ingest statistics.