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README.md

cloud-optimized-stac-geoparquet

Given one or more stac-geoparquet files, re-write them into spatio-temporal-optimized stac-geoparquet by sorting them by their stac-hash. Optionally, prefix item ids by their hash value, drastically improving the performance of single-id searches against the stac-geoparquet.

This tool formats stac-geoparquet files per the best practices.

Usage

Install dependencies and run the cosgp CLI via uv:

uv sync
uv run cosgp INFILE DATETIME OUTDIR
  • INFILE: a stac-geoparquet file, or a directory of .parquet files
  • DATETIME: the datetime range to hash against — a year (2024), year-month (2024-06), or year-month-day (2024-06-01)
  • OUTDIR: where the cloud-optimized output files are written

For example:

uv run cosgp items.parquet 2024 optimized/

Some useful options:

  • --bbox MINX MINY MAXX MAXY: restrict the hash's spatial extent (defaults to the whole globe)
  • --prefix-id: prefix each item's id with its hash, speeding up single-id lookups
  • --bucket-size BYTES: target size per output file (default 2 GB uncompressed)
  • --no-progress: log progress instead of showing a progress bar

Run uv run cosgp --help for the full list of options.

Benchmarks

We've done some benchmarking against files retrieved from the Microsoft Planetary Computer. To see the results, check out notebooks/duckdb-geoparquet-benchmarks.ipynb. Since they involve many remote queries the benchmarks take a while to run, but if you'd like to run them yourself:

scripts/sync-benchmark-data.sh
uv sync --group notebooks
uv run --group notebooks jupyter lab notebooks/duckdb-geoparquet-benchmarks.ipynb

License

MIT

关于 About

Create and benchmark cloud-optimized stac-geoparquet

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Jupyter Notebook79.8%
Python18.3%
Shell2.0%

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