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new b94807fd1b [DOCS] Draft SedonaDB 0.2.0 release post (#2540)
b94807fd1b is described below
commit b94807fd1b7f257abb0d8daa887512839930c729
Author: Dewey Dunnington <[email protected]>
AuthorDate: Fri Dec 5 16:01:20 2025 -0600
[DOCS] Draft SedonaDB 0.2.0 release post (#2540)
Co-authored-by: Jia Yu <[email protected]>
Co-authored-by: Copilot <[email protected]>
---
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+---
+date:
+ created: 2025-12-01
+links:
+ - SedonaDB: https://sedona.apache.org/sedonadb/
+authors:
+ - dewey
+ - kristin
+ - feng
+ - peter
+ - jess
+ - jia
+ - matt_powers
+title: "SedonaDB 0.2.0 Release"
+---
+
+<!--
+# Licensed to the Apache Software Foundation (ASF) under one
+# or more contributor license agreements. See the NOTICE file
+# distributed with this work for additional information
+# regarding copyright ownership. The ASF licenses this file
+# to you under the Apache License, Version 2.0 (the
+# "License"); you may not use this file except in compliance
+# with the License. You may obtain a copy of the License at
+#
+# http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing,
+# software distributed under the License is distributed on an
+# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
+# KIND, either express or implied. See the License for the
+# specific language governing permissions and limitations
+# under the License.
+-->
+
+The Apache Sedona community is excited to announce the release of
[SedonaDB](https://sedona.apache.org/sedonadb) version 0.2.0!
+
+SedonaDB is the first open-source, single-node analytical database engine that
treats spatial data as a first-class citizen. It is developed as a subproject
of Apache Sedona. This release consists of [136 resolved
issues](https://github.com/apache/sedona-db/milestone/1?closed=1) including 40
new functions from 17 contributors.
+
+Apache Sedona powers large-scale geospatial processing on distributed engines
like Spark (SedonaSpark), Flink (SedonaFlink), and Snowflake (SedonaSnow).
SedonaDB extends the Sedona ecosystem with a single-node engine optimized for
small-to-medium data analytics, delivering the simplicity and speed that
distributed systems often cannot.
+
+<!-- more -->
+
+## Release Highlights
+
+- Improved spatial function coverage
+- GDAL/OGR spatial file format read support
+- GeoParquet 1.1 write support
+- Python user-defined function support
+- Initial Raster data type implementation
+- Release on `crates.io`
+- Build system improvements
+
+For a complete list of changes since SedonaDB 0.1.0 see the [milestone for
0.2.0](https://github.com/apache/sedona-db/milestone/1?closed=1).
+
+## Improved spatial function coverage
+
+Since the 0.1.0 release we have been fortunate to work with contributors add
40 new `ST_` and `RS_` functions to our growing catalogue. Users of rs_height,
rs_scalex, rs_scaley, rs_skewx, rs_skewy, rs_upperleftx, rs_upperlefty,
rs_width, st_azimuth, st_boundary, st_crosses, st_dump, st_endpoint,
st_geometryfromtext, st_geometryn, st_isclosed, st_iscollection, st_isring,
st_issimple, st_isvalid, st_isvalidreason, st_makevalid, st_minimumclearance,
st_minimumclearanceline, st_npoints, st_n [...]
+
+Thank you to [Abeeujah](https://github.com/Abeeujah),
[ayushjariyal](https://github.com/ayushjariyal),
[jesspav](https://github.com/jesspav),
[joonaspessi](https://github.com/joonaspessi),
[petern48](https://github.com/petern48), and
[yutannihilation](https://github.com/yutannihilation) for these contributions!
(With a special thanks to [petern48](https://github.com/petern48) for reviewing
nearly all of them!)
+
+## GDAL/OGR spatial file format read support
+
+Whereas SedonaDB 0.1.0 launched with GeoParquet read support and GeoPandas
interoperability, support for file formats like GeoPackage, Shapefile,
FlatGeoBuf inherited the limitations of GeoPandas (notably, the materialization
of an entire layer in memory as a Pandas dataframe). The package powering
GeoPandas read support ([pyogrio](https://github.com/geopandas/pyogrio)) also
exposes the [underlying provider's (GDAL/OGR) native Arrow
interface](https://gdal.org/en/stable/development/rfc/r [...]
+
+```python
+# pip install "apache-sedona[db]"
+import sedona.db
+
+sd = sedona.db.connect()
+url =
"https://raw.githubusercontent.com/geoarrow/geoarrow-data/v0.2.0/example-crs/files/example-crs_vermont-utm.fgb";
+sd.read_pyogrio(url).to_pandas().plot()
+```
+
+This works for local files, `https://` urls (via `/vsicurl/`), and zipped
files (via `/vsizip/`). Globs (i.e., `sd.read_pyogrio("path/to/*.gpkg")`)
resolving to 1 or more local files are also supported.
+
+Like SedonaDB's GeoParquet support, spatial filters like `ST_Intersects()` are
translated into the GDAL/OGR scan where possible to take advantage of embedded
spatial indexes in formats like GeoPackage, FlatGeoBuf, and Shapefile. For
example, we can query small areas of a [huge FlatGeoBuf file hosted
elsewhere](https://flatgeobuf.org/examples/maplibre/large.html) without
scanning the entire file:
+
+```python
+# 12 GB file
+url = "https://flatgeobuf.septima.dk/population_areas.fgb";
+sd.read_pyogrio(url).to_view("population_areas")
+
+wkt = "POLYGON ((-73.978329 40.767412, -73.950005 40.767412, -73.950005
40.795098, -73.978329 40.795098, -73.978329 40.767412))"
+sd.sql(
+ f"""
+SELECT sum(population::INTEGER) FROM population_areas
+WHERE ST_Intersects(wkb_geometry, ST_SetSRID(ST_GeomFromWKT('{wkt}'), 4326))
+"""
+).show()
+# > ┌──────────────────────────────────┐
+# > │ sum(population_areas.population) │
+# > │ int64 │
+# > ╞══════════════════════════════════╡
+# > │ 256251 │
+# > └──────────────────────────────────┘
+```
+
+## GeoParquet 1.1 Write Support
+
+Whereas the initial version of SedonaDB launched with basic write support for
GeoParquet files, the latest version of the specification that enables readers
to read small portions of the resulting Parquet file was not supported. With
the latest release, `DataFrame.to_parquet("path/to/parquet",
geoparquet_version="1.1")` will add a `bbox` column enabling functions like
`sd.read_parquet()` with a `WHERE ST_Intersects()` query to read only a portion
of the input file.
+
+```python
+# pip install "apache-sedona[db]"
+import sedona.db
+
+sd = sedona.db.connect()
+url =
"https://github.com/geoarrow/geoarrow-data/releases/download/v0.2.0/ns-water_water-point.fgb";
+
+sd.read_pyogrio(url).to_parquet("water_point.parquet",
geoparquet_version="1.1")
+```
+
+Shrinking the default row group size to ~100,000 and applying a spatial sort
may improve read performance by ensuring that row groups contain related
features.
+
+```python
+sd.sql("SET datafusion.execution.parquet.max_row_group_size = 100000")
+
+sd.read_parquet(url).to_view("water_point")
+
+sd.sql(
+ """
+SELECT * FROM water_point
+ORDER BY sd_order(geometry)
+"""
+).to_parquet("water_point.parquet", geoparquet_version="1.1")
+```
+
+## Python User-Defined Function Support
+
+User-defined functions (UDFs) are essential components of many workflows in
modern DataFrame engines like Spark, DataFusion, and DuckDB to capture
user-specific logic that is difficult or impossible to implement by simply
composing existing functions. Just as [SedonaSpark provides a vectorized UDF
framework for geometry
types](https://sedona.apache.org/latest/tutorial/sql/#spatial-vectorized-udfs-python-only),
SedonaDB 0.2.0 exposes a framework that allows user-specific logic (including
[...]
+
+```python
+import pyarrow as pa
+import sedona.db
+from sedonadb import udf
+import shapely
+import geoarrow.pyarrow as ga
+
+sd = sedona.db.connect()
+
+
[email protected]_udf(ga.wkb(), [udf.GEOMETRY, udf.NUMERIC])
+def shapely_udf(geom, distance):
+ geom_wkb = pa.array(geom.storage.to_array())
+ distance = pa.array(distance.to_array())
+ geom = shapely.from_wkb(geom_wkb)
+ result_shapely = shapely.buffer(geom, distance)
+ return pa.array(shapely.to_wkb(result_shapely))
+
+
+sd.register_udf(shapely_udf)
+sd.sql("SELECT shapely_udf(ST_Point(0, 0), 2.0) as col").show()
+# >
┌──────────────────────────────────────────────────────────────────────────────────────────────────┐
+# > │ col
│
+# > │ geometry
│
+# >
╞══════════════════════════════════════════════════════════════════════════════════════════════════╡
+# > │ POLYGON((2 0,1.9615705608064609 -0.3901806440322565,1.8477590650225735
-0.7653668647301796,1.66… │
+# >
└──────────────────────────────────────────────────────────────────────────────────────────────────┘
+```
+
+See the [documentation page for
`arrow_udf()`](https://sedona.apache.org/sedonadb/latest/reference/python/#sedonadb.udf.arrow_udf)
for more examples and documentation.
+
+## Initial Raster data type implementation
+
+The [raster data type support in Sedona
Spark](https://sedona.apache.org/latest/tutorial/raster) is a popular feature
and in SedonaDB 0.2.0 we are pleased to offer a raster data type and a few
basic functions!
+
+```python
+import sedona.db
+
+sd = sedona.db.connect()
+
+sd.sql("SELECT RS_Width(RS_Example()) as width").show()
+# > ┌────────┐
+# > │ width │
+# > │ uint64 │
+# > ╞════════╡
+# > │ 64 │
+# > └────────┘
+```
+
+For more information or to get involved see the [raster support umbrella
issue](https://github.com/apache/sedona-db/issues/246). Thank you to
[jesspav](https://github.com/jesspav) for driving this work!
+
+## Release on `crates.io`
+
+Because our initial development of SedonaDB was closely tied to improvements
we were experimenting with in some of our dependency crates from the GeoRust
ecosystem, our first release of SedonaDB contained git dependencies and
references to the forks we had used in our experiments. While the first release
*could* be used in Rust projects via a git dependency, this prevented any
downstream project from releasing to crates.io themselves and did not make
clear that we do expose a public Rust [...]
+
+SedonaDB 0.2.0, in addition to being [released to
crates.io](https://crates.io/crates/sedona) includes [a Rust
example](https://github.com/apache/sedona-db/tree/main/examples/sedonadb-rust)
to get interested Rust projects started:
+
+```toml
+[package]
+# ...
+
+[dependencies]
+datafusion = { version = "50.2.0"}
+sedona = { version = "0.2.0" }
+# ...
+```
+
+```rust
+use datafusion::{common::Result, prelude::*};
+use sedona::context::{SedonaContext, SedonaDataFrame};
+
+#[tokio::main]
+async fn main() -> Result<()> {
+ let ctx = SedonaContext::new_local_interactive().await?;
+ let url =
"https://raw.githubusercontent.com/geoarrow/geoarrow-data/v0.2.0/natural-earth/files/natural-earth_cities_geo.parquet";;
+ let df = ctx.read_parquet(url, Default::default()).await?;
+ let output = df
+ .sort_by(vec![col("name")])?
+ .show_sedona(&ctx, Some(5), Default::default())
+ .await?;
+ println!("{output}");
+ Ok(())
+}
+```
+
+We're still learning about how or if downstream projects are interested in
using components from Rust, so feel free to [open an
issue](https://github.com/apache/sedona-db/issues/new) with ideas or questions.
+
+Special thanks to [kylebarron](https://github.com/kylebarron) for reviewing
our PRs upstream into the [geo-index](https://github.com/kylebarron/geo-index)
and [wkb](https://github.com/georust/wkb) crates!
+
+## Build System Improvements
+
+Build system improvements are some of the least glorious but most important
tasks included in the SedonaDB 0.2.0 release; however, we are pleased to be
able to release SedonaDB 0.2.0 Python binaries with support for PROJ, GEOS, and
S2Geography on MacOS, Windows, and Linux (Python 3.9 to 3.14, including
free-threaded variants of Python 3.13 and 3.14). [SedonaDB 0.2.0 for R may be
installed via R-Universe](https://apache.r-universe.dev/sedonadb), which now
includes pre-built binaries for M [...]
+
+Special thanks to [yutannihilation](https://github.com/yutannihilation) for
contributing fixes to the R build system!
+
+## Contributors
+
+This release consists of contributions from 17 contributors. Thank you for
your contributions!
+
+```
+git shortlog -sn apache-sedona-db-0.2.0.dev..apache-sedona-db-0.2.0
+ 25 Dewey Dunnington
+ 16 Abeeujah
+ 13 Hiroaki Yutani
+ 13 Peter Nguyen
+ 12 Kristin Cowalcijk
+ 8 jp
+ 6 Feng Zhang
+ 4 Joonas Pessi
+ 3 Matthew Powers
+ 2 Cancai Cai
+ 2 Jia Yu
+ 1 L_Sowmya
+ 1 Liang Geng
+ 1 Peter Von der Porten
+ 1 Yongting You
+ 1 ayushjariyal
+ 1 dentiny
+```
