jiayuasu opened a new pull request, #129:
URL: https://github.com/apache/sedona-spatialbench/pull/129
## Summary
Adds the **SF10 ground-truth answers**
(`benchmark/answers/sf10/q{1..12}.{parquet,csv}`), completing the correctness
fixtures for #126. The answers are the **SedonaDB oracle's output, produced in
CI** — no queries were run on a local machine. The verify job now gates SF10 as
well as SF1.
## How the answers were produced
- The benchmark run dumps each query's normalized result (`--result-dir`);
the SedonaDB SF10 dumps *are* the answers. The type-faithful `.parquet` is
reconstructed from the CI `.csv` dumps using the SF1 schema (same queries, same
column types across scale factors).
- **SedonaDB 0.3.0** was used for SF10. **0.4.0 cannot compute Q5 at SF10**
— its grouped convex-hull aggregation (`ST_Collect_Agg` → `ST_ConvexHull`)
spills **>100 GB** and aborts (filed as
[apache/sedona-db#1077](https://github.com/apache/sedona-db/issues/1077)).
0.3.0 computes it in modest space.
- The two versions produce **identical results for the other 11 queries** at
SF10 (verified positionally within `rtol=1e-6`), so the values are
version-independent — only Q5's feasibility differs.
- Self-check: all 12 committed SF10 answers verify cleanly against
SedonaDB's SF10 output.
## Supporting changes
- **`run_benchmark.py`** — dump normalized results whenever `--result-dir`
is set (previously gated on committed answers already existing). Dumping reuses
the timed run, so it's free; this is what let CI bootstrap the SF10 answers.
The verify job independently skips scale factors with no answers. (Drops the
now-unused `--answers-dir`.)
- **`benchmark.yml`** — free ~20 GB of preinstalled toolchains before each
query. SF10 queries spill several GB; without headroom SedonaDB's Q5 hit `No
space left on device` on the standard runner.
- READMEs updated (SF10 present, provenance, the 0.4.0/Q5 caveat).
## After merge
The correctness verify job runs every engine against the SF10 answers, so
each is independently cross-checked wherever the other engines can compute the
query at scale.
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