sedona
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apache
A cluster computing framework for processing large-scale geospatial data
A quick example which I created for `mruby` here: https://github.com/mruby/mruby/blob/8e074f185bd940f7dd52e3296f3c9bf70c830ba4/Dockerfile#L11 Apache Airflow uses Docker and pre-commit Airflow has 1700 lines of code in their pre-commit config: https://github.com/apache/airflow/blob/main/.pre-commit-config.yaml And now what...
A lot of text below, but I'll highlight the main difference first. Notice our version has extra nested `[ ]`. ``` # Our dataframe_to_arrow returns the following column geometry: [[0101...F03F],[0101...0040]]...
I use ST_MakePolygon(geom,holes) when not st_contains(geom,holes) that will return st_union(geom,holes)
I don't think the stats functions are compatible with spark connect today. I tried this in spark 3.5: ``` (python) ➜ python git:(graphframes-0.9.0) ✗ export SPARK_REMOTE=local (python) ➜ python git:(graphframes-0.9.0)...
``` spark.sql(""" SELECT ST_Within( ST_GeomFromText('POINT (1 1)'), ST_GeomFromText('POINT (1 1)') ), -- True ST_Within( ST_GeomFromText('POLYGON ((0 0, 1 0, 2 1, 3 1, 0 0))'), ST_GeomFromText('POLYGON ((0 0, 1 0,...
There is a `pip install apache-sedona[all]` command that pulls in all the optional dependencies: `spark`, `pydeck-map`, and `kepler-map`. I was reviewing the [Install on AWS EMR](https://sedona.apache.org/latest/setup/emr/) documentation, and it appears...
