apache/sedona

feat: add to_sedonadb() method

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#2511 opened on Nov 19, 2025

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help wanted

Description

It would be nice to have an interface that converts a SedonaSpark DataFrame to a SedonaDB DataFrame easily. Here is a current solution that works:

import sedona.db
sd = sedona.db.connect()

df = sd.create_data_frame(dataframe_to_arrow(spark_df))

This could be nice:

spark_df.to_sedonadb()

But maybe we'd have to do this:

spark_df.to_sedonadb(sd)

This would allow for cool spatial workflows, like this:

  • Read an Iceberg table with SedonaSpark and perform big data operations with a filtering operation at the end to make the data small enough to fit on a single machine
  • Convert the SedonaSpark DataFrame to SedonaDB
  • Use a library that's compatible with SedonaDB, like lonboard, to create a graph

Let me know what you think!

Contributor guide

Tech stack
python
Domain
dataapi
Issue type
feature
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
3
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
fresh
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
Basic knowledge of Apache SedonaPython programmingSpark DataFrame API
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
50
Research direction
First, locate the Python source code for Sedona's Spark DataFrame wrapper, likely in `python/sedona/core/`. Look for existing conversion methods like `to geopandas()` or `to spatial rdd()`. The new `to sedonadb()` method should be added to the same class. It must accept a SedonaDB connection object and internally call `dataframe to arrow(spark df)` and `sd.create data frame()`. Ensure the method follows existing patterns for type hints and documentation. Review the issue comment for any additional insights from maintainers.