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tile-benchmarking

Tile benchmarking using titiler-xarray and titiler-pgstac.

Environment Setup

It is recommended to run this project on the VEDA JupyterHub if using datasets generated in 01-generate-datasets/. See instructions on getting an account on the VEDA JupyterHub docs page.

It is the intention of this project that it can also be used to benchmark tiling for arbitrary zarr datasets. Examples are forthcoming.

Use the requirements.txt or environment.yaml to setup a python environment.

conda|mamba env create -f environment.yaml
conda|mamba activate tile-benchmarking

What's here

This directory includes notebooks for generating:

  • "fake" zarr datasets: A notebook for generating Zarr datasets vary by chunk size (higher and higher spatial resolution for the spatial extent of a chunk) and number of chunks (same chunk size for higher and higher spatial resolutions of the array's spatial extent.
  • cmip6 kerchunk datasets: A notebook for generating a kerchunk reference for CMIP6 data.
  • cmip6 zarr datasets: A notebook for generating CMIP6 zarr data at varying chunk shapes.
  • cmip6-pgstac/: A directory with a notebook and instructions on generating STAC for CMIP6 COGs.

You can skip this directory entirely unless you are interested in how the datasets were generated and / or want to modify them for any reason.

See the notebooks in 02-run-tests/ for examples on how to run tests.

At this time, tests exists for timing tile code for xarray and COGs.

TODO: Provide example of how to run a test on a new dataset. TODO: Run many tests and provide examples of how to report results. TODO: Add tests to run against API TODO: Add sub-tile code block timings

Instructions on how to run e2e tests for titiler-xarray with locust and siege.

You can skip this directory unless you are interested in (re)deploying the pgSTAC database for this project.

The cdk/ directory at the root of this repository hosts the code for deploying a pgSTAC database into AWS RDS.

See eoapi-cdk if you are interested in the deployment of pgSTAC using CDK.

Python functions used more than once in this project are stored here.

A git submodule of the titiler-xarray project in order to profile that codebase.

Other TODOs:

About

Repo for configuring datasets and tests for benchmarking with a dynamic tiler

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