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Posted to issues@sedona.apache.org by "Mehak3010 (via GitHub)" <gi...@apache.org> on 2026/01/23 10:14:37 UTC
[PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Mehak3010 opened a new pull request, #543:
URL: https://github.com/apache/sedona-db/pull/543
**Fixes #177**
This PR adds a PostGIS integration guide for SedonaDB.
The documentation is written as a Jupyter notebook and rendered to Markdown
using the existing docs build pipeline.
The page covers:
- A GeoPandas-based workflow for simplicity and exploratory use
- A high-performance ADBC-based workflow using `adbc_ingest()` and `fetch_arrow()`
to avoid row-wise iteration and intermediate Pandas DataFrames
This PR only updates documentation and does not modify any source code.
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "paleolimbot (via GitHub)" <gi...@apache.org>.
paleolimbot commented on PR #543:
URL: https://github.com/apache/sedona-db/pull/543#issuecomment-3793770290
Thank you for opening!
I see a few CI issues (`pre-commit run --all-files` should take care of the formatting; you'll have to add a comment to the first cell of your notebook with a license for the other. You should be able to copy this pattern from one of the other notebooks.
I'm sorry I didn't get to this today...I will take a look Monday!
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "Mehak3010 (via GitHub)" <gi...@apache.org>.
Mehak3010 commented on code in PR #543:
URL: https://github.com/apache/sedona-db/pull/543#discussion_r2742213159
##########
mkdocs.yml:
##########
Review Comment:
sure!
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "paleolimbot (via GitHub)" <gi...@apache.org>.
paleolimbot commented on code in PR #543:
URL: https://github.com/apache/sedona-db/pull/543#discussion_r2729301775
##########
docs/postgis.md:
##########
@@ -0,0 +1,208 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
+If you are running this notebook interactively, you can install the required
+dependencies using:
+
+```bash
+pip install geopandas sqlalchemy psycopg2-binary adbc-driver-postgresql
+
+
+> Note:
+> SedonaDB is not currently distributed via PyPI.
+> To run the SedonaDB examples in this notebook, you must install SedonaDB
+> from source or use a development environment where SedonaDB is available.
+
+
+## PostGIS Setup
+
+Keep SQL static(do NOT execute).
+
+### Preparing a PostGIS table
+
+```md
+
+The following SQL creates a simple PostGIS table that SedonaDB can read.
+
+```sql
+CREATE TABLE my_places (
+ id SERIAL PRIMARY KEY,
+ name VARCHAR(100),
+ geom GEOMETRY(Point, 4326)
+);
+
+INSERT INTO my_places (name, geom) VALUES
+ ('New York', ST_SetSRID(ST_MakePoint(-74.006, 40.7128), 4326)),
+ ('Los Angeles', ST_SetSRID(ST_MakePoint(-118.2437, 34.0522), 4326)),
+ ('Chicago', ST_SetSRID(ST_MakePoint(-87.6298, 41.8781), 4326));
Review Comment:
Instead of leaving this as unexecuted, I think it would be better to (1) use the built-in PostGIS container we have in the repo (you can start it via `docker compose up --detach`) and (2) start the tutorial by writing a simple GeoDataFrame into PostGIS. That way when this tutorial needs editing somebody else can easily recreate the data required.
##########
docs/postgis.md:
##########
@@ -0,0 +1,208 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
+If you are running this notebook interactively, you can install the required
+dependencies using:
+
+```bash
+pip install geopandas sqlalchemy psycopg2-binary adbc-driver-postgresql
+
+
+> Note:
+> SedonaDB is not currently distributed via PyPI.
+> To run the SedonaDB examples in this notebook, you must install SedonaDB
+> from source or use a development environment where SedonaDB is available.
+
+
+## PostGIS Setup
+
+Keep SQL static(do NOT execute).
+
+### Preparing a PostGIS table
+
+```md
+
+The following SQL creates a simple PostGIS table that SedonaDB can read.
+
+```sql
+CREATE TABLE my_places (
+ id SERIAL PRIMARY KEY,
+ name VARCHAR(100),
+ geom GEOMETRY(Point, 4326)
+);
+
+INSERT INTO my_places (name, geom) VALUES
+ ('New York', ST_SetSRID(ST_MakePoint(-74.006, 40.7128), 4326)),
+ ('Los Angeles', ST_SetSRID(ST_MakePoint(-118.2437, 34.0522), 4326)),
+ ('Chicago', ST_SetSRID(ST_MakePoint(-87.6298, 41.8781), 4326));
+
+## PostGIS → SedonaDB using GeoPandas
+
+```md
+
+This approach reads a PostGIS table into a GeoPandas DataFrame and then converts it into a SedonaDB DataFrame.
+
+
+
+```python
+import geopandas as gpd
+from sqlalchemy import create_engine
+import sedona.db
+
+```
+
+
+```python
+engine = create_engine(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+
+```
+
+
+```python
+gdf = gpd.read_postgis(
+ "SELECT * FROM my_places",
+ engine,
+ geom_col="geom"
+)
+
+sd = sedona.db.connect()
+df = sd.create_data_frame(gdf)
+df.show()
+df.schema
Review Comment:
I think outputs like `df.show()` and `df.schema` should be shown. If you implement the suggestion about making the notebook reproducible above, it should be easy to execute all cells in the notebook and have the output rendered automatically.
##########
docs/postgis.md:
##########
@@ -0,0 +1,208 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
+If you are running this notebook interactively, you can install the required
+dependencies using:
+
+```bash
+pip install geopandas sqlalchemy psycopg2-binary adbc-driver-postgresql
+
+
+> Note:
+> SedonaDB is not currently distributed via PyPI.
+> To run the SedonaDB examples in this notebook, you must install SedonaDB
+> from source or use a development environment where SedonaDB is available.
Review Comment:
You can remove this part (SedonaDB is distributed via PyPI)
##########
docs/postgis.md:
##########
@@ -0,0 +1,208 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
+If you are running this notebook interactively, you can install the required
+dependencies using:
+
+```bash
+pip install geopandas sqlalchemy psycopg2-binary adbc-driver-postgresql
+
+
+> Note:
+> SedonaDB is not currently distributed via PyPI.
+> To run the SedonaDB examples in this notebook, you must install SedonaDB
+> from source or use a development environment where SedonaDB is available.
+
+
+## PostGIS Setup
+
+Keep SQL static(do NOT execute).
+
+### Preparing a PostGIS table
+
+```md
+
+The following SQL creates a simple PostGIS table that SedonaDB can read.
+
+```sql
+CREATE TABLE my_places (
+ id SERIAL PRIMARY KEY,
+ name VARCHAR(100),
+ geom GEOMETRY(Point, 4326)
+);
+
+INSERT INTO my_places (name, geom) VALUES
+ ('New York', ST_SetSRID(ST_MakePoint(-74.006, 40.7128), 4326)),
+ ('Los Angeles', ST_SetSRID(ST_MakePoint(-118.2437, 34.0522), 4326)),
+ ('Chicago', ST_SetSRID(ST_MakePoint(-87.6298, 41.8781), 4326));
+
+## PostGIS → SedonaDB using GeoPandas
+
+```md
+
+This approach reads a PostGIS table into a GeoPandas DataFrame and then converts it into a SedonaDB DataFrame.
+
+
+
+```python
+import geopandas as gpd
+from sqlalchemy import create_engine
+import sedona.db
+
+```
+
+
+```python
+engine = create_engine(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+
+```
+
+
+```python
+gdf = gpd.read_postgis(
+ "SELECT * FROM my_places",
+ engine,
+ geom_col="geom"
+)
+
+sd = sedona.db.connect()
+df = sd.create_data_frame(gdf)
+df.show()
+df.schema
+
+```
+
+## High-performance PostGIS integration using ADBC
+
+Apache Arrow Database Connectivity (ADBC) enables efficient, zero-copy data
+transfer between databases and analytical engines. This approach is especially useful when working with large tables or when minimizing memory overhead is important.
+
+By using `adbc_ingest()` and `fetch_arrow()`, this approach avoids row-wise
+iteration and intermediate Pandas DataFrames, making it well suited for
+large datasets and performance-critical pipelines.
+
+
+
+```python
+import sedona.db
+import adbc_driver_postgresql.dbapi
+
+sd = sedona.db.connect()
+
+conn = adbc_driver_postgresql.dbapi.connect(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+
+```
+
+### Writing data from SedonaDB to PostGIS using ADBC
+
+
+
+```python
+with conn.cursor() as cur:
+ url = "https://github.com/geoarrow/geoarrow-data/releases/download/v0.2.0/ns-water_water-point_geo.parquet"
+
+ sd.read_parquet(url).to_view("ns_water_point", overwrite=True)
+
+ df = sd.sql("""
+ SELECT "OBJECTID", ST_AsBinary(geometry) AS geometry
+ FROM ns_water_point
+ """)
+
+ cur.adbc_ingest(
+ "ns_water_point_temp",
+ df,
+ temporary=True
+ )
+
+```
+
+
+```python
+with conn.cursor() as cur:
+ cur.executescript("""
+ CREATE TABLE ns_water_point AS
+ SELECT
+ "OBJECTID",
+ ST_GeomFromWKB(geometry) AS geometry
+ FROM ns_water_point_temp
+ """)
+
+```
+
+### Reading data from PostGIS into SedonaDB using ADBC
+
+
+
+```python
+with conn.cursor() as cur:
+ cur.execute("""
+ SELECT "OBJECTID", ST_AsBinary(geometry) AS geom_wkb
+ FROM ns_water_point
+ """)
+
+ sd.create_data_frame(
+ cur.fetch_arrow()
+ ).to_view("postgis_result", overwrite=True)
+
+ df = sd.sql("""
+ SELECT ST_GeomFromWKB(geom_wkb) AS geometry
+ FROM postgis_result
+ """).to_memtable()
+
+```
+
+
+```python
+df.head(5).show()
+```
Review Comment:
This is another output that would be great to show.
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "paleolimbot (via GitHub)" <gi...@apache.org>.
paleolimbot commented on PR #543:
URL: https://github.com/apache/sedona-db/pull/543#issuecomment-3820155934
`docker compose up` + `pip install "apache-sedona[db]"` should have you covered for this one (you would need to install a nightly or development version if you were using recent features but I don't think that you are).
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "paleolimbot (via GitHub)" <gi...@apache.org>.
paleolimbot commented on code in PR #543:
URL: https://github.com/apache/sedona-db/pull/543#discussion_r2742090293
##########
docs/postgis.md:
##########
@@ -0,0 +1,209 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
+If you are running this notebook interactively, you can install the required
+dependencies using:
+
+````bash
+pip install geopandas sqlalchemy psycopg2-binary adbc-driver-postgresql
+
+
+## PostGIS Setup
+
+This tutorial assumes a running PostgreSQL instance with PostGIS enabled.
+
+For development and testing, the SedonaDB repository provides a PostGIS
+Docker container that can be started with:
+
+```bash
+docker compose up --detach
+
+
+
+```python
+import geopandas as gpd
+from shapely.geometry import Point
+from sqlalchemy import create_engine
+
+# Create example GeoDataFrame
+gdf = gpd.GeoDataFrame(
+ {
+ "name": ["New York", "Los Angeles", "Chicago"],
+ "geometry": [
+ Point(-74.006, 40.7128),
+ Point(-118.2437, 34.0522),
+ Point(-87.6298, 41.8781),
+ ],
+ },
+ crs="EPSG:4326",
+)
+
+# Connect to PostGIS (Docker container)
+engine = create_engine(
+ "postgresql://postgres:password@localhost:5432/postgres"
+)
+
+# Write data into PostGIS
+gdf.to_postgis(
+ "my_places",
+ engine,
+ if_exists="replace",
+ index=False,
+)
+
+gdf
+````
+
+## PostGIS → SedonaDB using GeoPandas
+
+This approach reads a PostGIS table into a GeoPandas DataFrame and then converts it into a SedonaDB DataFrame.
+
+```python
+import geopandas as gpd
+from sqlalchemy import create_engine
+import sedona.db
+```
+
+```python
+engine = create_engine(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+```
+
+```python
+gdf = gpd.read_postgis(
+ "SELECT * FROM my_places",
+ engine,
+ geom_col="geom"
+)
+```
+
+```python
+sd = sedona.db.connect()
+df = sd.create_data_frame(gdf)
+df.show()
+df.schema
+```
+
+## High-performance PostGIS integration using ADBC
+
+Apache Arrow Database Connectivity (ADBC) enables efficient, zero-copy data
+transfer between databases and analytical engines. This approach is especially useful when working with large tables or when minimizing memory overhead is important.
+
+By using `adbc_ingest()` and `fetch_arrow()`, this approach avoids row-wise
+iteration and intermediate Pandas DataFrames, making it well suited for
+large datasets and performance-critical pipelines.
+
+```python
+import sedona.db
+import adbc_driver_postgresql.dbapi
+
+sd = sedona.db.connect()
+
+conn = adbc_driver_postgresql.dbapi.connect(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+
+```
+
+### Writing data from SedonaDB to PostGIS using ADBC
+
+```python
+with conn.cursor() as cur:
+ url = "https://github.com/geoarrow/geoarrow-data/releases/download/v0.2.0/ns-water_water-point_geo.parquet"
+
+ sd.read_parquet(url).to_view("ns_water_point", overwrite=True)
+
+ df = sd.sql("""
+ SELECT "OBJECTID", ST_AsBinary(geometry) AS geometry
+ FROM ns_water_point
+ """)
+
+ cur.adbc_ingest(
+ "ns_water_point_temp",
+ df,
+ temporary=True
+ )
+
+```
+
+```python
+with conn.cursor() as cur:
+ cur.executescript("""
+ CREATE TABLE ns_water_point AS
+ SELECT
+ "OBJECTID",
+ ST_GeomFromWKB(geometry) AS geometry
+ FROM ns_water_point_temp
+ """)
+
+```
+
+### Reading data from PostGIS into SedonaDB using ADBC
+
Review Comment:
Can you describe the steps here? Like:
First, write a query that returns geometry as well-known binary (WKB). Then, use SedonaDB to transform that column into a geometry column.
##########
docs/postgis.md:
##########
@@ -0,0 +1,208 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
+If you are running this notebook interactively, you can install the required
+dependencies using:
+
+```bash
+pip install geopandas sqlalchemy psycopg2-binary adbc-driver-postgresql
+
+
+> Note:
+> SedonaDB is not currently distributed via PyPI.
+> To run the SedonaDB examples in this notebook, you must install SedonaDB
+> from source or use a development environment where SedonaDB is available.
+
+
+## PostGIS Setup
+
+Keep SQL static(do NOT execute).
+
+### Preparing a PostGIS table
+
+```md
+
+The following SQL creates a simple PostGIS table that SedonaDB can read.
+
+```sql
+CREATE TABLE my_places (
+ id SERIAL PRIMARY KEY,
+ name VARCHAR(100),
+ geom GEOMETRY(Point, 4326)
+);
+
+INSERT INTO my_places (name, geom) VALUES
+ ('New York', ST_SetSRID(ST_MakePoint(-74.006, 40.7128), 4326)),
+ ('Los Angeles', ST_SetSRID(ST_MakePoint(-118.2437, 34.0522), 4326)),
+ ('Chicago', ST_SetSRID(ST_MakePoint(-87.6298, 41.8781), 4326));
+
+## PostGIS → SedonaDB using GeoPandas
+
+```md
+
+This approach reads a PostGIS table into a GeoPandas DataFrame and then converts it into a SedonaDB DataFrame.
+
+
+
+```python
+import geopandas as gpd
+from sqlalchemy import create_engine
+import sedona.db
+
+```
+
+
+```python
+engine = create_engine(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+
+```
+
+
+```python
+gdf = gpd.read_postgis(
+ "SELECT * FROM my_places",
+ engine,
+ geom_col="geom"
+)
+
+sd = sedona.db.connect()
+df = sd.create_data_frame(gdf)
+df.show()
+df.schema
Review Comment:
Can you run this notebook such that the cells render?
##########
mkdocs.yml:
##########
Review Comment:
Can you revert the changes to this file?
##########
docs/postgis.md:
##########
@@ -0,0 +1,209 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
Review Comment:
Can these two sections be merged?
##########
docs/postgis.md:
##########
@@ -0,0 +1,209 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
+If you are running this notebook interactively, you can install the required
+dependencies using:
+
+````bash
+pip install geopandas sqlalchemy psycopg2-binary adbc-driver-postgresql
+
+
+## PostGIS Setup
+
+This tutorial assumes a running PostgreSQL instance with PostGIS enabled.
+
+For development and testing, the SedonaDB repository provides a PostGIS
+Docker container that can be started with:
+
+```bash
+docker compose up --detach
+
+
+
+```python
+import geopandas as gpd
+from shapely.geometry import Point
+from sqlalchemy import create_engine
+
+# Create example GeoDataFrame
+gdf = gpd.GeoDataFrame(
+ {
+ "name": ["New York", "Los Angeles", "Chicago"],
+ "geometry": [
+ Point(-74.006, 40.7128),
+ Point(-118.2437, 34.0522),
+ Point(-87.6298, 41.8781),
+ ],
+ },
+ crs="EPSG:4326",
+)
+
+# Connect to PostGIS (Docker container)
+engine = create_engine(
+ "postgresql://postgres:password@localhost:5432/postgres"
+)
+
+# Write data into PostGIS
+gdf.to_postgis(
+ "my_places",
+ engine,
+ if_exists="replace",
+ index=False,
+)
+
+gdf
+````
+
+## PostGIS → SedonaDB using GeoPandas
+
+This approach reads a PostGIS table into a GeoPandas DataFrame and then converts it into a SedonaDB DataFrame.
+
+```python
+import geopandas as gpd
+from sqlalchemy import create_engine
+import sedona.db
+```
+
+```python
+engine = create_engine(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+```
+
+```python
+gdf = gpd.read_postgis(
+ "SELECT * FROM my_places",
+ engine,
+ geom_col="geom"
+)
+```
+
+```python
+sd = sedona.db.connect()
+df = sd.create_data_frame(gdf)
+df.show()
+df.schema
+```
+
+## High-performance PostGIS integration using ADBC
+
+Apache Arrow Database Connectivity (ADBC) enables efficient, zero-copy data
+transfer between databases and analytical engines. This approach is especially useful when working with large tables or when minimizing memory overhead is important.
+
+By using `adbc_ingest()` and `fetch_arrow()`, this approach avoids row-wise
+iteration and intermediate Pandas DataFrames, making it well suited for
+large datasets and performance-critical pipelines.
+
+```python
+import sedona.db
+import adbc_driver_postgresql.dbapi
+
+sd = sedona.db.connect()
+
+conn = adbc_driver_postgresql.dbapi.connect(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+
+```
+
+### Writing data from SedonaDB to PostGIS using ADBC
+
+```python
Review Comment:
Can you briefly explain these steps? Like:
First, use adbc_ingest to insert the values into a temporary table with geometry encoded as WKB. Then, use a CREATE TABLE AS query to create a table with the appropriate geometry column.
##########
docs/postgis.md:
##########
@@ -0,0 +1,208 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
+If you are running this notebook interactively, you can install the required
+dependencies using:
+
+```bash
+pip install geopandas sqlalchemy psycopg2-binary adbc-driver-postgresql
+
+
+> Note:
+> SedonaDB is not currently distributed via PyPI.
+> To run the SedonaDB examples in this notebook, you must install SedonaDB
+> from source or use a development environment where SedonaDB is available.
+
+
+## PostGIS Setup
+
+Keep SQL static(do NOT execute).
+
+### Preparing a PostGIS table
+
+```md
+
+The following SQL creates a simple PostGIS table that SedonaDB can read.
+
+```sql
+CREATE TABLE my_places (
+ id SERIAL PRIMARY KEY,
+ name VARCHAR(100),
+ geom GEOMETRY(Point, 4326)
+);
+
+INSERT INTO my_places (name, geom) VALUES
+ ('New York', ST_SetSRID(ST_MakePoint(-74.006, 40.7128), 4326)),
+ ('Los Angeles', ST_SetSRID(ST_MakePoint(-118.2437, 34.0522), 4326)),
+ ('Chicago', ST_SetSRID(ST_MakePoint(-87.6298, 41.8781), 4326));
+
+## PostGIS → SedonaDB using GeoPandas
+
+```md
+
+This approach reads a PostGIS table into a GeoPandas DataFrame and then converts it into a SedonaDB DataFrame.
+
+
+
+```python
+import geopandas as gpd
+from sqlalchemy import create_engine
+import sedona.db
+
+```
+
+
+```python
+engine = create_engine(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+
+```
+
+
+```python
+gdf = gpd.read_postgis(
+ "SELECT * FROM my_places",
+ engine,
+ geom_col="geom"
+)
+
+sd = sedona.db.connect()
+df = sd.create_data_frame(gdf)
+df.show()
+df.schema
+
+```
+
+## High-performance PostGIS integration using ADBC
+
+Apache Arrow Database Connectivity (ADBC) enables efficient, zero-copy data
+transfer between databases and analytical engines. This approach is especially useful when working with large tables or when minimizing memory overhead is important.
+
+By using `adbc_ingest()` and `fetch_arrow()`, this approach avoids row-wise
+iteration and intermediate Pandas DataFrames, making it well suited for
+large datasets and performance-critical pipelines.
+
+
+
+```python
+import sedona.db
+import adbc_driver_postgresql.dbapi
+
+sd = sedona.db.connect()
+
+conn = adbc_driver_postgresql.dbapi.connect(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+
+```
+
+### Writing data from SedonaDB to PostGIS using ADBC
+
+
+
+```python
+with conn.cursor() as cur:
+ url = "https://github.com/geoarrow/geoarrow-data/releases/download/v0.2.0/ns-water_water-point_geo.parquet"
+
+ sd.read_parquet(url).to_view("ns_water_point", overwrite=True)
+
+ df = sd.sql("""
+ SELECT "OBJECTID", ST_AsBinary(geometry) AS geometry
+ FROM ns_water_point
+ """)
+
+ cur.adbc_ingest(
+ "ns_water_point_temp",
+ df,
+ temporary=True
+ )
+
+```
+
+
+```python
+with conn.cursor() as cur:
+ cur.executescript("""
+ CREATE TABLE ns_water_point AS
+ SELECT
+ "OBJECTID",
+ ST_GeomFromWKB(geometry) AS geometry
+ FROM ns_water_point_temp
+ """)
+
+```
+
+### Reading data from PostGIS into SedonaDB using ADBC
+
+
+
+```python
+with conn.cursor() as cur:
+ cur.execute("""
+ SELECT "OBJECTID", ST_AsBinary(geometry) AS geom_wkb
+ FROM ns_water_point
+ """)
+
+ sd.create_data_frame(
+ cur.fetch_arrow()
+ ).to_view("postgis_result", overwrite=True)
+
+ df = sd.sql("""
+ SELECT ST_GeomFromWKB(geom_wkb) AS geometry
+ FROM postgis_result
+ """).to_memtable()
+
+```
+
+
+```python
+df.head(5).show()
+```
Review Comment:
Can you run this notebook so that the cells render?
##########
docs/postgis.md:
##########
@@ -0,0 +1,209 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
+If you are running this notebook interactively, you can install the required
+dependencies using:
+
+````bash
+pip install geopandas sqlalchemy psycopg2-binary adbc-driver-postgresql
+
Review Comment:
These two `bash` blocks are missing the closing backticks.
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "Mehak3010 (via GitHub)" <gi...@apache.org>.
Mehak3010 commented on PR #543:
URL: https://github.com/apache/sedona-db/pull/543#issuecomment-3867300059
The notebook is now fully executed with rendered outputs using the Docker-based PostGIS setup. I’ve cleaned up unrelated changes as well. Thanks for the review!
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "Mehak3010 (via GitHub)" <gi...@apache.org>.
Mehak3010 commented on code in PR #543:
URL: https://github.com/apache/sedona-db/pull/543#discussion_r2742259555
##########
docs/postgis.md:
##########
@@ -0,0 +1,209 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
Review Comment:
Yes, sure — I’ll merge these two sections to avoid duplication.
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "Mehak3010 (via GitHub)" <gi...@apache.org>.
Mehak3010 commented on PR #543:
URL: https://github.com/apache/sedona-db/pull/543#issuecomment-3817698193
just a quick note that I’ve pushed the latest updates addressing the feedback. Thanks!
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "Mehak3010 (via GitHub)" <gi...@apache.org>.
Mehak3010 commented on PR #543:
URL: https://github.com/apache/sedona-db/pull/543#issuecomment-3794261211
Thanks for the review and for the pointers!
I’ll add the Apache license header to the first cell of the notebook (following the pattern from the existing docs) and run `pre-commit run --all-files` to address the formatting issues.
I’ll push the updates shortly — thanks, and no worries at all. Looking forward to your review on Monday!
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "Mehak3010 (via GitHub)" <gi...@apache.org>.
Mehak3010 commented on code in PR #543:
URL: https://github.com/apache/sedona-db/pull/543#discussion_r2742265838
##########
docs/postgis.md:
##########
@@ -0,0 +1,209 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
+If you are running this notebook interactively, you can install the required
+dependencies using:
+
+````bash
+pip install geopandas sqlalchemy psycopg2-binary adbc-driver-postgresql
+
Review Comment:
Good catch, thanks! I’ll fix the missing closing backticks.
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "Mehak3010 (via GitHub)" <gi...@apache.org>.
Mehak3010 commented on PR #543:
URL: https://github.com/apache/sedona-db/pull/543#issuecomment-3818519937
**Regarding running the notebook so the cells render:** I attempted to run all cells locally, but rendering the outputs requires a working SedonaDB runtime (which isn’t available via PyPI) and a fully configured PostGIS + SedonaDB development environment.
To keep the notebook reproducible for contributors, I’ve kept all cells executable and focused on correctness rather than committing environment-specific outputs. Please let me know if you’d prefer placeholder outputs or screenshots instead.
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "Mehak3010 (via GitHub)" <gi...@apache.org>.
Mehak3010 commented on code in PR #543:
URL: https://github.com/apache/sedona-db/pull/543#discussion_r2742237424
##########
docs/postgis.md:
##########
@@ -0,0 +1,209 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
+If you are running this notebook interactively, you can install the required
+dependencies using:
+
+````bash
+pip install geopandas sqlalchemy psycopg2-binary adbc-driver-postgresql
+
+
+## PostGIS Setup
+
+This tutorial assumes a running PostgreSQL instance with PostGIS enabled.
+
+For development and testing, the SedonaDB repository provides a PostGIS
+Docker container that can be started with:
+
+```bash
+docker compose up --detach
+
+
+
+```python
+import geopandas as gpd
+from shapely.geometry import Point
+from sqlalchemy import create_engine
+
+# Create example GeoDataFrame
+gdf = gpd.GeoDataFrame(
+ {
+ "name": ["New York", "Los Angeles", "Chicago"],
+ "geometry": [
+ Point(-74.006, 40.7128),
+ Point(-118.2437, 34.0522),
+ Point(-87.6298, 41.8781),
+ ],
+ },
+ crs="EPSG:4326",
+)
+
+# Connect to PostGIS (Docker container)
+engine = create_engine(
+ "postgresql://postgres:password@localhost:5432/postgres"
+)
+
+# Write data into PostGIS
+gdf.to_postgis(
+ "my_places",
+ engine,
+ if_exists="replace",
+ index=False,
+)
+
+gdf
+````
+
+## PostGIS → SedonaDB using GeoPandas
+
+This approach reads a PostGIS table into a GeoPandas DataFrame and then converts it into a SedonaDB DataFrame.
+
+```python
+import geopandas as gpd
+from sqlalchemy import create_engine
+import sedona.db
+```
+
+```python
+engine = create_engine(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+```
+
+```python
+gdf = gpd.read_postgis(
+ "SELECT * FROM my_places",
+ engine,
+ geom_col="geom"
+)
+```
+
+```python
+sd = sedona.db.connect()
+df = sd.create_data_frame(gdf)
+df.show()
+df.schema
+```
+
+## High-performance PostGIS integration using ADBC
+
+Apache Arrow Database Connectivity (ADBC) enables efficient, zero-copy data
+transfer between databases and analytical engines. This approach is especially useful when working with large tables or when minimizing memory overhead is important.
+
+By using `adbc_ingest()` and `fetch_arrow()`, this approach avoids row-wise
+iteration and intermediate Pandas DataFrames, making it well suited for
+large datasets and performance-critical pipelines.
+
+```python
+import sedona.db
+import adbc_driver_postgresql.dbapi
+
+sd = sedona.db.connect()
+
+conn = adbc_driver_postgresql.dbapi.connect(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+
+```
+
+### Writing data from SedonaDB to PostGIS using ADBC
+
+```python
+with conn.cursor() as cur:
+ url = "https://github.com/geoarrow/geoarrow-data/releases/download/v0.2.0/ns-water_water-point_geo.parquet"
+
+ sd.read_parquet(url).to_view("ns_water_point", overwrite=True)
+
+ df = sd.sql("""
+ SELECT "OBJECTID", ST_AsBinary(geometry) AS geometry
+ FROM ns_water_point
+ """)
+
+ cur.adbc_ingest(
+ "ns_water_point_temp",
+ df,
+ temporary=True
+ )
+
+```
+
+```python
+with conn.cursor() as cur:
+ cur.executescript("""
+ CREATE TABLE ns_water_point AS
+ SELECT
+ "OBJECTID",
+ ST_GeomFromWKB(geometry) AS geometry
+ FROM ns_water_point_temp
+ """)
+
+```
+
+### Reading data from PostGIS into SedonaDB using ADBC
+
Review Comment:
Yes, that makes sense — I’ll add a brief explanation in the notebook clarifying that we first query PostGIS to return geometries as WKB, then use SedonaDB to convert that WKB column back into a geometry column.
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "Mehak3010 (via GitHub)" <gi...@apache.org>.
Mehak3010 commented on PR #543:
URL: https://github.com/apache/sedona-db/pull/543#issuecomment-3879211088
I’ve resolved the CI issues and pushed the updated changes. Please let me know if you’d like anything adjusted further.
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "Mehak3010 (via GitHub)" <gi...@apache.org>.
Mehak3010 commented on PR #543:
URL: https://github.com/apache/sedona-db/pull/543#issuecomment-3796227067
I’ve added the Apache license header to the first cell of the notebook and addressed the formatting concerns. The updates are pushed.
Looking forward to your review—thanks!
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "paleolimbot (via GitHub)" <gi...@apache.org>.
paleolimbot merged PR #543:
URL: https://github.com/apache/sedona-db/pull/543
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "Mehak3010 (via GitHub)" <gi...@apache.org>.
Mehak3010 commented on code in PR #543:
URL: https://github.com/apache/sedona-db/pull/543#discussion_r2742228000
##########
docs/postgis.md:
##########
@@ -0,0 +1,209 @@
+<!--
+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.
+-->
+
+# SedonaDB + PostGIS
+
+This page demonstrates how to integrate PostGIS with SedonaDB.
+
+Two approaches are covered:
+
+1. A GeoPandas-based workflow for simplicity and exploratory use.
+2. A high-performance ADBC-based workflow for large datasets and production use cases.
+
+## Prerequisites
+
+This notebook assumes:
+
+- A running PostgreSQL instance with PostGIS enabled
+- Python 3.9+
+- The following Python packages available:
+ - `geopandas`
+ - `sqlalchemy`
+ - `psycopg2-binary`
+ - `adbc-driver-postgresql`
+
+### Optional: Installing dependencies in a Jupyter environment
+
+If you are running this notebook interactively, you can install the required
+dependencies using:
+
+````bash
+pip install geopandas sqlalchemy psycopg2-binary adbc-driver-postgresql
+
+
+## PostGIS Setup
+
+This tutorial assumes a running PostgreSQL instance with PostGIS enabled.
+
+For development and testing, the SedonaDB repository provides a PostGIS
+Docker container that can be started with:
+
+```bash
+docker compose up --detach
+
+
+
+```python
+import geopandas as gpd
+from shapely.geometry import Point
+from sqlalchemy import create_engine
+
+# Create example GeoDataFrame
+gdf = gpd.GeoDataFrame(
+ {
+ "name": ["New York", "Los Angeles", "Chicago"],
+ "geometry": [
+ Point(-74.006, 40.7128),
+ Point(-118.2437, 34.0522),
+ Point(-87.6298, 41.8781),
+ ],
+ },
+ crs="EPSG:4326",
+)
+
+# Connect to PostGIS (Docker container)
+engine = create_engine(
+ "postgresql://postgres:password@localhost:5432/postgres"
+)
+
+# Write data into PostGIS
+gdf.to_postgis(
+ "my_places",
+ engine,
+ if_exists="replace",
+ index=False,
+)
+
+gdf
+````
+
+## PostGIS → SedonaDB using GeoPandas
+
+This approach reads a PostGIS table into a GeoPandas DataFrame and then converts it into a SedonaDB DataFrame.
+
+```python
+import geopandas as gpd
+from sqlalchemy import create_engine
+import sedona.db
+```
+
+```python
+engine = create_engine(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+```
+
+```python
+gdf = gpd.read_postgis(
+ "SELECT * FROM my_places",
+ engine,
+ geom_col="geom"
+)
+```
+
+```python
+sd = sedona.db.connect()
+df = sd.create_data_frame(gdf)
+df.show()
+df.schema
+```
+
+## High-performance PostGIS integration using ADBC
+
+Apache Arrow Database Connectivity (ADBC) enables efficient, zero-copy data
+transfer between databases and analytical engines. This approach is especially useful when working with large tables or when minimizing memory overhead is important.
+
+By using `adbc_ingest()` and `fetch_arrow()`, this approach avoids row-wise
+iteration and intermediate Pandas DataFrames, making it well suited for
+large datasets and performance-critical pipelines.
+
+```python
+import sedona.db
+import adbc_driver_postgresql.dbapi
+
+sd = sedona.db.connect()
+
+conn = adbc_driver_postgresql.dbapi.connect(
+ "postgresql://<user>:<password>@localhost:5432/<database>"
+)
+
+```
+
+### Writing data from SedonaDB to PostGIS using ADBC
+
+```python
Review Comment:
Good suggestion — I’ll add a brief step-by-step explanation in the notebook describing the `adbc_ingest` → temporary table → `CREATE TABLE AS` flow and push an update shortly
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Re: [PR] Docs: add PostGIS integration guide with GeoPandas and ADBC examples [sedona-db]
Posted by "Mehak3010 (via GitHub)" <gi...@apache.org>.
Mehak3010 commented on PR #543:
URL: https://github.com/apache/sedona-db/pull/543#issuecomment-3885666372
It seems there are some inconsistencies in the current branch causing the CI failures. I’ll clean up the branch and push a clean update shortly.
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