paleolimbot commented on issue #2586: URL: https://github.com/apache/iceberg/issues/2586#issuecomment-1817530680
I think there is a recording but I'm not sure if it has been posted yet. The slides are here: https://dewey.dunnington.ca/slides/geoarrow2023 and GeoArrow for Python is on pypi/conda and can generate examples of what Parquet files would look like and what the memory layout would be: ```python import geoarrow.pyarrow as ga import pyarrow as pa from geoarrow.pyarrow import io from pyarrow import parquet extension_array = ga.as_geoarrow(["POLYGON ((0 0, 1 0, 0 1, 0 0))"]) extension_array.type #> PolygonType(geoarrow.polygon) extension_array.type.storage_type #> ListType(list<rings: list<vertices: struct<x: double, y: double>>>) extension_array.geobuffers() #> [None, #> array([0, 1], dtype=int32), #> array([0, 4], dtype=int32), #> array([0., 1., 0., 0.]), #> array([0., 0., 1., 0.])] # Parquet with extension type table = pa.table([extension_array], names=["geometry"]) parquet.write_table(table, "ext.parquet") # GeoParquet (no extension type, but with 'geo' metadata for GeoParquet) io.write_geoparquet_table(table, "geo.parquet") ``` An example of how to find column statistics and use them is here: https://github.com/geoarrow/geoarrow-python/blob/main/geoarrow-pyarrow/src/geoarrow/pyarrow/dataset.py#L434-L468 -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected] --------------------------------------------------------------------- To unsubscribe, e-mail: [email protected] For additional commands, e-mail: [email protected]
