replace existing benchmark.rs with benches and queries derived from t…

.gitmodules

@@ -4,3 +4,6 @@
 [submodule "w3c-validation/rdf-tests"]
 	path = w3c-validation/rdf-tests
 	url = https://github.com/w3c/rdf-tests
+[submodule "benches/trainmarks"]
+	path = benches/trainmarks
+	url = https://github.com/DeciSym/trainmarks.git

Cargo.toml

@@ -13,14 +13,17 @@ repository = "https://github.com/DeciSym/de"
 default-run = "de"
 keywords = ["hdt", "rdf", "semantic-web", "triple-store", "sparql"]
 categories = ["command-line-utilities"]
+# The trainmarks benchmark submodule is a separate repo of fixtures and
+# harnesses for other engines; it has no place in the published crate.
+exclude = ["benches/trainmarks"]
 
 [[bin]]
 name = "de"
 path = "src/main.rs"
 bench = false
 
 [[bench]]
-name = "benchmark"
+name = "trainmarks"
 harness = false
 
 [dependencies]

Makefile

@@ -1,6 +1,9 @@
 HUB ?= decisym
 TAG ?= latest
 VERSION ?= 0.0.0-test
+# Dataset scale for the trainmarks benchmarks: medium (~100K triples),
+# large (~1M) or xlarge (~10M). Must match DE_BENCH_SCALE at bench time.
+BENCH_SCALE ?= large
 
 init:
 	scripts/download-sample-bench.sh
@@ -21,8 +24,15 @@ test: init
 
 presubmit: lint test
 
-bench: init
-	cargo bench
+# Check out the trainmarks submodule and generate the N-Triples and Turtle
+# fixtures the trainmarks bench target reads. Split out from `init` because
+# they are ~150 MB at the default scale and only the benchmarks need them.
+bench-init: init
+	git submodule update --init benches/trainmarks
+	python3 scripts/gen-trainmarks-data.py $(BENCH_SCALE)
+
+bench: bench-init
+	DE_BENCH_SCALE=$(BENCH_SCALE) cargo bench
 
 build:
 	cargo build --features=server

README.md

@@ -135,3 +135,49 @@ Run W3C RDF/SPARQL integration tests:
 ```sh
 cargo test --all-features --test w3c-sparql
 ```
+
+## Benchmarks
+
+The `trainmarks` criterion suite covers `create` and `query` over the synthetic
+e-commerce graph from [trainmarks](https://github.com/DeciSym/trainmarks),
+checked out as a submodule at `benches/trainmarks`. It exists to catch
+performance regressions at a realistic dataset size, not to compare `de`
+against other engines.
+
+It measures four things: building an HDT from N-Triples, building one from
+Turtle (the only path that runs the RDF parser), the five queries against a
+prebuilt HDT, and one query given a Turtle file directly, which `de` converts
+to a temporary package before evaluating.
+
+`make bench` first checks out the submodule and generates the fixtures the
+suite reads:
+
+```sh
+make bench
+```
+
+The dataset scale is `BENCH_SCALE` — `medium` (~100K triples), `large` (~1M,
+the default) or `xlarge` (~10M):
+
+```sh
+BENCH_SCALE=medium make bench
+```
+
+`make bench` passes the scale through to the suite as `DE_BENCH_SCALE`, which
+is also what to set when driving `cargo bench` directly. The fixtures and the
+benchmark must agree on it, since the scale is part of every benchmark id
+(`trainmarks_query/large/q3_join_3_entities`) and criterion compares each run
+against the stored baseline for that id:
+
+```sh
+make bench-init                          # once, to lay down the fixtures
+DE_BENCH_SCALE=large cargo bench --bench trainmarks
+DE_BENCH_SCALE=large cargo bench --bench trainmarks -- q3_join_3_entities
+```
+
+Without the fixtures the suite prints how to get them and measures nothing, so
+`cargo bench` still works on a fresh clone.
+
+The queries are trainmarks' own `q1`–`q5`, shared verbatim with the other
+engines in that report. `q6_delete_insert` is omitted: it is a SPARQL Update,
+and HDT packages are immutable.