geo-engine / geoengine / 41639724622
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Files 472
Run time 1min
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coverage: 88.052%. Remained the same
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build(backend): use thin LTO with one codegen unit for release builds (#1393)

* build(backend): use thin LTO with one codegen unit for release builds

Fat LTO made release and bench builds slow (about 87 min for the
datatypes and operators benches, ~3.7 GB per linked binary). Thin LTO
with codegen-units = 1 builds the same benches in about 8 min.

With codegen-units = 1 the hot raster loops inline the same functions as
with fat LTO (e.g. the MaskedGrid validity-mask closure and rayon's
unzip_into_vecs, which thin LTO with 16 codegen units left out of line).
Interleaved runs of the datatypes grid benches stayed within ±5% of fat
LTO, inside the run-to-run noise of fat LTO itself.

* test(backend): add end-to-end WMS query pipeline bench

Times GetMap requests through the full actix app for typical processing
graphs on the local NDVI test data (source, scaling, neighborhood,
interpolation, downsampling, temporal aggregation, reprojection), so the
measured code spans services, operators and datatypes. It prints median,
min and MAD per case plus an output hash to check that builds agree.

Run from geoengine/ (the settings are read from the working directory)
against the Postgres in Settings-default.toml, e.g.
    cargo bench -p geoengine-services --bench query_pipelines

* test(backend): use criterion for query_pipelines bench and document benches

Criterion baselines (--save-baseline / --baseline) compare build settings such as
LTO or codegen units. Each case prints its output hash to check that both builds
produce the same result. The README lists the available benches.

138400 of 157180 relevant lines covered (88.05%)

534523.32 hits per line

Jobs
ID Job ID Ran Files Coverage
1 41639724622.1 472
88.05
GitHub Action Run
Source Files on build 41639724622