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new d709291c99 [DOCS] restructure navigation (#2519)
d709291c99 is described below
commit d709291c99a8c851bef132efa05d14d47aad0444
Author: Matthew Powers <[email protected]>
AuthorDate: Thu Dec 11 16:41:00 2025 -0500
[DOCS] restructure navigation (#2519)
---
docs-overrides/main.html | 248 +++++++++++++++++++++---------------------
docs/image/nyc_base_water.png | Bin 0 -> 426760 bytes
docs/sedonaflink.md | 111 +++++++++++++++++++
docs/sedonasnow.md | 55 ++++++++++
docs/sedonaspark.md | 137 +++++++++++++++++++++++
mkdocs.yml | 71 ++++++------
6 files changed, 464 insertions(+), 158 deletions(-)
diff --git a/docs-overrides/main.html b/docs-overrides/main.html
index f7d1cd6462..48ab95c1bd 100644
--- a/docs-overrides/main.html
+++ b/docs-overrides/main.html
@@ -165,7 +165,7 @@ docker run -d -p 8888:8888 -p 8085:8085 apache/sedona:latest
Install SedonaDB, or run Sedona on distributed systems when
you need additional scale.
</div>
<div class="bth-group">
- <a href="https://github.com/apache/sedona-db"; class="btn
btn-red">
+ <a href="sedonadb" class="btn btn-red">
<span class="caption">
Install SedonaDB
</span>
@@ -176,6 +176,130 @@ docker run -d -p 8888:8888 -p 8085:8085
apache/sedona:latest
</div>
</section>
+ <!-- Section Deploy -->
+ <section class="section-deploy">
+ <div class="container">
+ <h2 class="section-title">Deploy Sedona where you need it</h2>
+ <div class="section-description editor">Choose the right runtime for
your infrastructure, from local setups to distributed and cloud-native
systems.</div>
+ <div class="info-grid">
+
+ <div class="info-item">
+ <div class="info-item__tag">
+ <img src="image/home/deploy/desktop.svg" alt="" class="">
+ <div class="caption">
+ Local
+ </div>
+ </div>
+ <h3 class="info-item__title">SedonaDB</h3>
+ <div class="info-item__description editor">Standalone runtime
for local processing and development.</div>
+ <div class="info-item__cta">
+ <a href="sedonadb" class="btn-link">
+ <span class="caption">SedonaDB</span>
+ <span class="icon">
+ <svg width="19" height="19" viewBox="0 0 19 19"
fill="none" xmlns="http://www.w3.org/2000/svg";>
+ <path d="M3.95831 9.5H15.0416" stroke="#CA463A" stroke-width="1.5"
stroke-linecap="round" stroke-linejoin="round" />
+ <path d="M9.5 3.95825L15.0417 9.49992L9.5 15.0416" stroke="#CA463A"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" />
+ </svg>
+ </span>
+ </a>
+ </div>
+ </div>
+
+ <div class="info-item">
+ <div class="info-item__tag">
+ <img src="image/home/deploy/database.svg" alt="" class="">
+ <div class="caption">
+ Batch
+ </div>
+ </div>
+ <h3 class="info-item__title">SedonaSpark</h3>
+ <div class="info-item__description editor">Distributed batch
processing on Apache Spark clusters.</div>
+ <div class="info-item__cta">
+ <a href="sedonaspark" class="btn-link">
+ <span class="caption">SedonaSpark</span>
+ <span class="icon">
+ <svg width="19" height="19" viewBox="0 0 19 19"
fill="none" xmlns="http://www.w3.org/2000/svg";>
+ <path d="M3.95831 9.5H15.0416" stroke="#CA463A" stroke-width="1.5"
stroke-linecap="round" stroke-linejoin="round" />
+ <path d="M9.5 3.95825L15.0417 9.49992L9.5 15.0416" stroke="#CA463A"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" />
+ </svg>
+ </span>
+ </a>
+ </div>
+ </div>
+
+ <div class="info-item">
+ <div class="info-item__tag">
+ <img src="image/home/deploy/signal.svg" alt="" class="">
+ <div class="caption">
+ Streaming
+ </div>
+ </div>
+ <h3 class="info-item__title">SedonaFlink</h3>
+ <div class="info-item__description editor">Real-time spatial
analytics using Apache Flink.</div>
+ <div class="info-item__cta">
+ <a href="sedonaflink" class="btn-link">
+ <span class="caption">SedonaFlink</span>
+ <span class="icon">
+ <svg width="19" height="19" viewBox="0 0 19 19"
fill="none" xmlns="http://www.w3.org/2000/svg";>
+ <path d="M3.95831 9.5H15.0416" stroke="#CA463A" stroke-width="1.5"
stroke-linecap="round" stroke-linejoin="round" />
+ <path d="M9.5 3.95825L15.0417 9.49992L9.5 15.0416" stroke="#CA463A"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" />
+ </svg>
+ </span>
+ </a>
+ </div>
+ </div>
+
+ <div class="info-item">
+ <div class="info-item__tag">
+ <img src="image/home/deploy/snowflake.svg" alt="" class="">
+ <div class="caption">
+ Batch
+ </div>
+ </div>
+ <h3 class="info-item__title">SedonaSnow</h3>
+ <div class="info-item__description editor">
+ Native spatial support inside Snowflake environments.
+ </div>
+ <div class="info-item__cta">
+ <a href="sedonasnow" class="btn-link">
+ <span class="caption">SedonaSnow</span>
+ <span class="icon">
+ <svg width="19" height="19" viewBox="0 0 19 19"
fill="none" xmlns="http://www.w3.org/2000/svg";>
+ <path d="M3.95831 9.5H15.0416" stroke="#CA463A" stroke-width="1.5"
stroke-linecap="round" stroke-linejoin="round" />
+ <path d="M9.5 3.95825L15.0417 9.49992L9.5 15.0416" stroke="#CA463A"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" />
+ </svg>
+ </span>
+ </a>
+ </div>
+ </div>
+
+ <div class="info-item info-item--wide">
+ <div class="info-item__tag">
+ <img src="image/home/deploy/cloud.svg" alt="" class="">
+ <div class="caption">
+ Cloud
+ </div>
+ </div>
+ <h3 class="info-item__title">Sedona in the Cloud</h3>
+ <div class="info-item__description editor">Integrated spatial
support in your preferred cloud environment</div>
+ <div class="info-item__cta">
+ <a href="setup/overview/" class="btn-link">
+ <span class="caption">Explore the ecosystem</span>
+ <span class="icon">
+ <svg width="19" height="19" viewBox="0 0 19 19"
fill="none" xmlns="http://www.w3.org/2000/svg";>
+ <path d="M3.95831 9.5H15.0416" stroke="#CA463A" stroke-width="1.5"
stroke-linecap="round" stroke-linejoin="round" />
+ <path d="M9.5 3.95825L15.0417 9.49992L9.5 15.0416" stroke="#CA463A"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" />
+ </svg>
+ </span>
+ </a>
+ </div>
+ </div>
+
+ </div>
+ </div>
+ </section>
+
+
<!-- Section Industries Tabs -->
<section class="section-industries-tabs">
<div class="container">
@@ -378,128 +502,6 @@ docker run -d -p 8888:8888 -p 8085:8085
apache/sedona:latest
</section>
-->
- <!-- Section Deploy -->
- <section class="section-deploy">
- <div class="container">
- <h2 class="section-title">Deploy Sedona where you need it</h2>
- <div class="section-description editor">Choose the right runtime for
your infrastructure, from local setups to distributed and cloud-native
systems.</div>
- <div class="info-grid">
-
- <div class="info-item">
- <div class="info-item__tag">
- <img src="image/home/deploy/desktop.svg" alt="" class="">
- <div class="caption">
- Local
- </div>
- </div>
- <h3 class="info-item__title">SedonaDB</h3>
- <div class="info-item__description editor">Standalone runtime
for local processing and development.</div>
- <div class="info-item__cta">
- <a href="https://github.com/apache/sedona-db"; class="btn-link">
- <span class="caption">SedonaDB</span>
- <span class="icon">
- <svg width="19" height="19" viewBox="0 0 19 19"
fill="none" xmlns="http://www.w3.org/2000/svg";>
- <path d="M3.95831 9.5H15.0416" stroke="#CA463A" stroke-width="1.5"
stroke-linecap="round" stroke-linejoin="round" />
- <path d="M9.5 3.95825L15.0417 9.49992L9.5 15.0416" stroke="#CA463A"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" />
- </svg>
- </span>
- </a>
- </div>
- </div>
-
- <div class="info-item">
- <div class="info-item__tag">
- <img src="image/home/deploy/database.svg" alt="" class="">
- <div class="caption">
- Batch
- </div>
- </div>
- <h3 class="info-item__title">SedonaSpark</h3>
- <div class="info-item__description editor">Distributed batch
processing on Apache Spark clusters.</div>
- <div class="info-item__cta">
- <a href="setup/overview/" class="btn-link">
- <span class="caption">SedonaSpark</span>
- <span class="icon">
- <svg width="19" height="19" viewBox="0 0 19 19"
fill="none" xmlns="http://www.w3.org/2000/svg";>
- <path d="M3.95831 9.5H15.0416" stroke="#CA463A" stroke-width="1.5"
stroke-linecap="round" stroke-linejoin="round" />
- <path d="M9.5 3.95825L15.0417 9.49992L9.5 15.0416" stroke="#CA463A"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" />
- </svg>
- </span>
- </a>
- </div>
- </div>
-
- <div class="info-item">
- <div class="info-item__tag">
- <img src="image/home/deploy/signal.svg" alt="" class="">
- <div class="caption">
- Streaming
- </div>
- </div>
- <h3 class="info-item__title">SedonaFlink</h3>
- <div class="info-item__description editor">Real-time spatial
analytics using Apache Flink.</div>
- <div class="info-item__cta">
- <a href="setup/flink/install-scala/" class="btn-link">
- <span class="caption">SedonaFlink</span>
- <span class="icon">
- <svg width="19" height="19" viewBox="0 0 19 19"
fill="none" xmlns="http://www.w3.org/2000/svg";>
- <path d="M3.95831 9.5H15.0416" stroke="#CA463A" stroke-width="1.5"
stroke-linecap="round" stroke-linejoin="round" />
- <path d="M9.5 3.95825L15.0417 9.49992L9.5 15.0416" stroke="#CA463A"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" />
- </svg>
- </span>
- </a>
- </div>
- </div>
-
- <div class="info-item">
- <div class="info-item__tag">
- <img src="image/home/deploy/snowflake.svg" alt="" class="">
- <div class="caption">
- Batch
- </div>
- </div>
- <h3 class="info-item__title">SedonaSnow</h3>
- <div class="info-item__description editor">
- Native spatial support inside Snowflake environments.
- </div>
- <div class="info-item__cta">
- <a href="setup/snowflake/install/" class="btn-link">
- <span class="caption">SedonaSnow</span>
- <span class="icon">
- <svg width="19" height="19" viewBox="0 0 19 19"
fill="none" xmlns="http://www.w3.org/2000/svg";>
- <path d="M3.95831 9.5H15.0416" stroke="#CA463A" stroke-width="1.5"
stroke-linecap="round" stroke-linejoin="round" />
- <path d="M9.5 3.95825L15.0417 9.49992L9.5 15.0416" stroke="#CA463A"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" />
- </svg>
- </span>
- </a>
- </div>
- </div>
-
- <div class="info-item info-item--wide">
- <div class="info-item__tag">
- <img src="image/home/deploy/cloud.svg" alt="" class="">
- <div class="caption">
- Cloud
- </div>
- </div>
- <h3 class="info-item__title">Sedona in the Cloud</h3>
- <div class="info-item__description editor">Integrated spatial
support in your preferred cloud environment</div>
- <div class="info-item__cta">
- <a href="setup/overview/" class="btn-link">
- <span class="caption">Explore the ecosystem</span>
- <span class="icon">
- <svg width="19" height="19" viewBox="0 0 19 19"
fill="none" xmlns="http://www.w3.org/2000/svg";>
- <path d="M3.95831 9.5H15.0416" stroke="#CA463A" stroke-width="1.5"
stroke-linecap="round" stroke-linejoin="round" />
- <path d="M9.5 3.95825L15.0417 9.49992L9.5 15.0416" stroke="#CA463A"
stroke-width="1.5" stroke-linecap="round" stroke-linejoin="round" />
- </svg>
- </span>
- </a>
- </div>
- </div>
-
- </div>
- </div>
- </section>
<!-- Section Community -->
<section class="section-community">
diff --git a/docs/image/nyc_base_water.png b/docs/image/nyc_base_water.png
new file mode 100644
index 0000000000..7cea91b9bd
Binary files /dev/null and b/docs/image/nyc_base_water.png differ
diff --git a/docs/sedonaflink.md b/docs/sedonaflink.md
new file mode 100644
index 0000000000..a555aad5f4
--- /dev/null
+++ b/docs/sedonaflink.md
@@ -0,0 +1,111 @@
+<!--
+ 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.
+ -->
+
+# SedonaFlink
+
+SedonaFlink integrates geospatial functions into Apache Flink, making it an
excellent option for streaming pipelines that utilize geospatial data.
+
+Here are some example SedonaFlink use cases:
+
+* Read geospatial data from Kafka and write to Iceberg
+* [Analyze real-time traffic
density](https://www.alibabacloud.com/help/en/flink/realtime-flink/use-cases/analyze-traffic-density-with-flink-and-apache-sedona)
+* Real-time network planning and optimization for telecommunication
+
+Here are some example code snippets:
+
+=== "Java"
+
+ ```java
+ sedona.createTemporaryView("myTable", tbl)
+ Table geomTbl = sedona.sqlQuery("SELECT ST_GeomFromWKT(geom_polygon) as
geom_polygon, name_polygon FROM myTable")
+ geomTbl.execute().print()
+ ```
+
+=== "PyFlink"
+
+ ```python
+ table_env.sql_query("SELECT ST_ASBinary(ST_Point(1.0,
2.0))").execute().collect()
+ ```
+
+## Key features
+
+* **Real-time geospatial stream processing** for low-latency processing needs.
+* **Scalable** processing suitable for large streaming pipelines.
+* **Event time processing** with Flink’s time-windowing.
+* **Exactly once** processing guarantees.
+* **Portable** and easy to run in any Flink runtime.
+* **Open source** and managed according to the Apache Software Foundation's
guidelines.
+
+## Why Sedona on Flink?
+
+Flink is built for streaming data, and Sedona enhances it with geospatial
functionality.
+
+Most geospatial processing occurs in batch systems such as Spark or PostGIS,
which is fine for lower-latency use cases.
+
+Sedona on Flink shines when you need to process geospatial data in real-time.
+
+Flink can deliver millisecond-level latency for geospatial queries.
+
+Flink has solid fault tolerance, so your geospatial pipelines won't lose data,
even when things break.
+
+Sedona on Flink runs anywhere Flink runs, including Kubernetes, YARN, and
standalone clusters.
+
+## How It Works
+
+Sedona integrates directly into Flink's Table API and SQL engine.
+
+You register Sedona's spatial functions when you set up your Flink
environment. Then, you can use functions such as `ST_Point`, `ST_Contains`, and
`ST_Distance` in your SQL queries.
+
+Sedona works with both Flink's DataStream API and Table API. Use whichever
fits your workflow.
+
+The spatial operations run as part of Flink's distributed execution, so your
geospatial computations are automatically parallelized across your cluster.
+
+Sedona stores geometries as binary data in Flink's internal format. This keeps
memory usage low and processing fast.
+
+When you perform spatial joins, Sedona utilizes spatial indexing under the
hood, enabling it to execute queries quickly.
+
+Flink's checkpointing system handles fault tolerance. If a node crashes, your
geospatial state is restored from the last checkpoint.
+
+You read geospatial data from sources such as Kafka or file systems, process
it using Sedona's spatial functions, and write the results to sinks such as
Iceberg.
+
+The entire SedonaFlink pipeline runs continuously, allowing new events to flow
through your spatial transformations in real-time.
+
+## Comparison with alternatives
+
+For small datasets, you may not need a distributed cluster and can use
SedonaDB.
+
+For large batch pipelines, you can use SedonaSpark.
+
+Here are some direct comparisons of SedonaFlink vs. streaming alternatives.
+
+**SedonaFlink vs. Sedona on Spark Structured Streaming**
+
+Spark Streaming uses micro-batches, whereas Flink processes events one at a
time. This can provide Flink with lower latency for some workflows.
+
+Flink's state management is also more sophisticated.
+
+Use Spark if you're already invested in the Spark ecosystem and the Spark
Structured Streaming latency is sufficiently low for your use case. Use Flink
if you need very low latency.
+
+**Sedona on Flink vs. PostGIS**
+
+PostGIS is great for storing and querying geospatial data for OLTP workflows.
But it's not built for streaming.
+
+If you use PostGIS for streaming workflows, you need to constantly query the
database from your stream processor, which adds latency and puts load on your
database.
+
+SedonaFlink processes geospatial data in-flight, eliminating the need for
database round-trips.
diff --git a/docs/sedonasnow.md b/docs/sedonasnow.md
new file mode 100644
index 0000000000..28a5021ed5
--- /dev/null
+++ b/docs/sedonasnow.md
@@ -0,0 +1,55 @@
+<!--
+ 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.
+ -->
+
+# SedonaSnow
+
+SedonaSnow brings 200+ Apache Sedona geospatial functions directly into your
Snowflake environment to complement the native Snowflake spatial functions.
+
+## Key Advantages
+
+* **200+ spatial functions**: Such as 3D distance, geometry validation,
precision reduction
+* **Fast spatial joins**: Sedona has special optimizations for performant
spatial joins
+* **Seamless integration**: Works alongside Snowflake's native functions
+* **No data movement**: Everything stays in Snowflake
+
+## Get Started
+
+Here’s an example of how to run some queries on Snowflake tables with
SedonaSnow.
+
+```sql
+USE DATABASE SEDONASNOW;
+
+SELECT SEDONA.ST_GeomFromWKT(wkt) AS geom
+FROM your_table;
+
+SELECT SEDONA.ST_3DDistance(geom1, geom2) FROM spatial_data;
+```
+
+Here’s an example of a spatial join:
+
+```sql
+SELECT * FROM lefts, rights
+WHERE lefts.cellId = rights.cellId;
+```
+
+You can see how SedonaSnow seamlessly integrates into your current Snowflake
environment.
+
+## Next steps
+
+SedonaSnow is an excellent option if you're doing serious spatial analysis in
Snowflake. It is fast and provides a wide range of spatial functions.
SedonaSnow removes the limitations of Snowflake's built-in spatial functions
without forcing you to move your data to another platform.
diff --git a/docs/sedonaspark.md b/docs/sedonaspark.md
new file mode 100644
index 0000000000..3d67573c5e
--- /dev/null
+++ b/docs/sedonaspark.md
@@ -0,0 +1,137 @@
+<!--
+ 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.
+ -->
+
+# SedonaSpark
+
+SedonaSpark extends Apache Spark with a rich set of out-of-the-box distributed
Spatial Datasets and functions that efficiently load, process, and analyze
large-scale spatial data across machines. SedonaSpark is an excellent option
for datasets too large for a single machine.
+
+=== "SQL"
+
+ ```sql
+ SELECT superhero.name
+ FROM city, superhero
+ WHERE ST_Contains(city.geom, superhero.geom)
+ AND city.name = 'Gotham'
+ ```
+
+=== "PySpark"
+
+ ```python
+ sedona.sql(
+ """
+ SELECT superhero.name
+ FROM city, superhero
+ WHERE ST_Contains(city.geom, superhero.geom)
+ AND city.name = 'Gotham'
+ """
+ )
+ ```
+
+=== "Java"
+
+ ```java
+ Dataset<Row> result = spark.sql(
+ "SELECT superhero.name " +
+ "FROM city, superhero " +
+ "WHERE ST_Contains(city.geom, superhero.geom) " +
+ "AND city.name = 'Gotham'"
+ );
+ ```
+
+=== "Scala"
+
+ ```scala
+ sedona.sql("""
+ SELECT superhero.name
+ FROM city, superhero
+ WHERE ST_Contains(city.geom, superhero.geom)
+ AND city.name = 'Gotham'
+ """)
+ ```
+
+=== "R"
+
+ ```r
+ result <- sql("
+ SELECT superhero.name
+ FROM city, superhero
+ WHERE ST_Contains(city.geom, superhero.geom)
+ AND city.name = 'Gotham'
+ ")
+ ```
+
+## Key features
+
+* **Blazing fast**: SedonaSpark executes computations in parallel on many
nodes in a cluster so that large computations can run fast.
+* Supports **various file formats**, including GeoJSON, Shapefile, GeoParquet,
STAC, JDBC, OSM PBF, CSV, and PostGIS.
+* Exposes several **language APIs,** including SQL, Python, Java, Scala, and R.
+* **Scalable**: Horizontally scale to tens, hundreds, or thousands of nodes
depending on the size of your data. You can process massive spatial datasets
with SedonaSpark.
+* **Portable**: Easy to run in a custom environment, locally or in the cloud
with AWS EMR, Microsoft Fabric, or Google DataProc.
+* **Extensible**: You can extend SedonaSpark with your custom logic that suits
your specific geospatial data analysis needs.
+* **Open source**: Apache Sedona is an open-source project managed in
accordance with the Apache Software Foundation's guidelines.
+* Extra functionality like [nearest neighbor
searching](https://sedona.apache.org/latest/api/sql/NearestNeighbourSearching/)
and geostats like
[DBSCAN](https://sedona.apache.org/latest/tutorial/sql/#cluster-with-dbscan)
+
+## Portability
+
+It’s easy to run SedonaSpark locally, with Docker, or on any popular cloud.
+
+SedonaSpark is designed to be run in any environment where Spark can run.
Many cloud vendors have Spark runtimes, and Sedona can be added as a library
dependency.
+
+Running Sedona locally is handy, allowing you to iterate on code before
deploying it to production datasets.
+
+## Spark and Sedona example with vector data
+
+Let’s take a look at how to perform a workflow on a vector dataset with Spark
and Sedona.
+
+Let’s use the base water data supplied by the Overture Maps Foundation to map
all the bodies of water in the New York City area. Start by reading the data
and creating a view:
+
+```
+base_water = sedona.table("open_data.overture_maps_foundation.base_water")
+base_water.createOrReplaceTempView("base_water_view")
+```
+
+Now filter the dataset to include the bodies of water in the New York City
area.
+
+```python
+spot = "POLYGON ((-74.174194 40.509623, -73.635864 40.509623, -73.635864
40.93634, -74.174194 40.93634, -74.174194 40.509623))"
+query = f"""
+select id, geometry from base_water_view
+where ST_Contains(ST_GeomFromWKT('{spot}'), geometry)
+"""
+res = sedona.sql(query)
+```
+
+Sedona integrates seamlessly with popular graphing libraries, making it easy
to create graphs from a Sedona DataFrame. You can build a map with just two
lines of code:
+
+```python
+kepler_map = SedonaKepler.create_map()
+SedonaKepler.add_df(kepler_map, df=res, name="Tri-state water")
+```
+
+The map looks amazing!
+
+
+
+You can easily see all of the rivers, lakes, and swimming pools in the New
York City area with this map.
+
+## Have questions?
+
+Feel free to start a GitHub Discussion or join the Discord community to ask
the developers any questions you may have.
+
+We look forward to collaborating with you!
diff --git a/mkdocs.yml b/mkdocs.yml
index b87c504fc0..e53a0231f3 100644
--- a/mkdocs.yml
+++ b/mkdocs.yml
@@ -20,19 +20,10 @@ site_url: https://sedona.apache.org
site_description: Apache Sedona is a cluster computing system for processing
large-scale spatial data. Sedona extends existing cluster computing systems,
such as Apache Spark, Apache Flink, and Snowflake, with a set of out-of-the-box
distributed Spatial Datasets and Spatial SQL that efficiently load, process,
and analyze large-scale spatial data across machines.
nav:
- Home: index.md
- - Setup:
- - Overview: setup/overview.md
- - Supported platforms:
- - Sedona with Apache Spark:
- - Modules: setup/modules.md
- - Language wrappers: setup/platform.md
- - Sedona with Apache Flink:
- - Modules: setup/flink/modules.md
- - Language wrappers: setup/flink/platform.md
- - Sedona with Snowflake:
- - Modules: setup/snowflake/modules.md
- - Maven Central coordinate: setup/maven-coordinates.md
- - Install with Apache Spark:
+ - SedonaDB: 'https://sedona.apache.org/sedonadb/'
+ - SedonaSpark:
+ - Home: sedonaspark.md
+ - Install:
- Install Sedona Scala/Java: setup/install-scala.md
- Install Sedona Python: setup/install-python.md
- Install Sedona R: api/rdocs
@@ -46,15 +37,11 @@ nav:
- Install on Microsoft Fabric: setup/fabric.md
- Set up Spark cluster manually: setup/cluster.md
- Install on Azure Synapse Analytics:
setup/azure-synapse-analytics.md
- - Install with Apache Flink:
- - Install Sedona Scala/Java: setup/flink/install-scala.md
- - Install Sedona Python: setup/flink/install-python.md
- - Install with Snowflake:
- - Install Sedona SQL: setup/snowflake/install.md
- - Release notes: setup/release-notes.md
- - Download: download.md
- - Programming Guides:
- - Sedona with Apache Spark:
+ - Overview: setup/overview.md
+ - Modules: setup/modules.md
+ - Language wrappers: setup/platform.md
+ - Maven Central coordinate: setup/maven-coordinates.md
+ - Programming Guide:
- Spatial DataFrame / SQL app: tutorial/sql.md
- Raster DataFrame / SQL app: tutorial/raster.md
- Pure SQL environment: tutorial/sql-pure-sql.md
@@ -81,16 +68,7 @@ nav:
- Benchmark: tutorial/benchmark.md
- Tune RDD application:
tutorial/Advanced-Tutorial-Tune-your-Application.md
- Storing large raster geometries in Parquet files:
tutorial/storing-blobs-in-parquet.md
- - Sedona with Apache Flink:
- - Spatial SQL app (Flink): tutorial/flink/sql.md
- - Spatial SQL app (PyFlink): tutorial/flink/pyflink-sql.md
- - Sedona with Snowflake:
- - Spatial SQL app (Snowflake): tutorial/snowflake/sql.md
- - Examples:
- - Scala/Java: tutorial/demo.md
- - Python: tutorial/jupyter-notebook.md
- - API Docs:
- - Sedona with Apache Spark:
+ - API:
- SQL:
- Quick start: api/sql/Overview.md
- Vector data:
@@ -130,24 +108,47 @@ nav:
- RDD: api/viz/java-api.md
- Sedona R: api/rdocs
- Sedona Python: api/pydocs
- - Sedona with Apache Flink:
+
+ - SedonaFlink:
+ - Home: sedonaflink.md
+ - Install:
+ - Install Sedona Scala/Java: setup/flink/install-scala.md
+ - Install Sedona Python: setup/flink/install-python.md
+ - Modules: setup/flink/modules.md
+ - Language wrappers: setup/flink/platform.md
+ - Programming Guides:
+ - Sedona with Apache Flink:
+ - Spatial SQL app (Flink): tutorial/flink/sql.md
+ - Spatial SQL app (PyFlink): tutorial/flink/pyflink-sql.md
+ - Examples:
+ - Scala/Java: tutorial/demo.md
+ - Python: tutorial/jupyter-notebook.md
+ - API:
- SQL:
- Overview (Flink): api/flink/Overview.md
- Constructor (Flink): api/flink/Constructor.md
- Function (Flink): api/flink/Function.md
- Aggregator (Flink): api/flink/Aggregator.md
- Predicate (Flink): api/flink/Predicate.md
- - Sedona with Snowflake:
+
+ - SedonaSnow:
+ - Home: sedonasnow.md
+ - Install:
+ - Install Sedona SQL: setup/snowflake/install.md
+ - Spatial SQL app (Snowflake): tutorial/snowflake/sql.md
+ - Modules: setup/snowflake/modules.md
+ - API:
- SQL:
- Overview (Snowflake): api/snowflake/vector-data/Overview.md
- Constructor (Snowflake):
api/snowflake/vector-data/Constructor.md
- Function (Snowflake): api/snowflake/vector-data/Function.md
- Aggregate Function (Snowflake):
api/snowflake/vector-data/AggregateFunction.md
- Predicate (Snowflake): api/snowflake/vector-data/Predicate.md
- - SedonaDB: 'https://sedona.apache.org/sedonadb/'
- SpatialBench: 'https://sedona.apache.org/spatialbench/'
- Blog: blog/index.md
- Community:
+ - Download: download.md
+ - Release notes: setup/release-notes.md
- Compile the code: setup/compile.md
- Community: community/contact.md
- Contributor Guide:
