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Jun 18, 2025
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Update Roadmap documentation #16399

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Update Roadmap documentation
alamb Jun 13, 2025
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Merge remote-tracking branch 'apache/main' into alamb/roadmap
alamb Jun 17, 2025
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alamb Jun 17, 2025
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83 changes: 7 additions & 76 deletions docs/source/contributor-guide/roadmap.md
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Expand Up @@ -46,81 +46,12 @@ make review efficient and avoid surprises.

# Quarterly Roadmap

A quarterly roadmap will be published to give the DataFusion community
visibility into the priorities of the projects contributors. This roadmap is not
binding and we would welcome any/all contributions to help keep this list up to
date.
The DataFusion roadmap is driven the priorities of the contributors rather than
any single organization or coordinating committee. We typically discuss roadmap
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should we define the way of We typically discuss roadmap ? weekly meetings, slack, GH, etc?

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From my perspective what happens today is we discuss roadmap for specific items on the related github tickets, and more generally on "Discussion" tickets once every quarter or two

I am not sure if you are suggesting we try and invest more effort into new / different processes.

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Nvm, I was just thinking it would be more clear to the reader to know where exactly the roadmap is discussed in case they want to participate as well.

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Thanks -- I tried to make it clearer and explicitly invited the reader to join the discussion

approximately quarterly in GitHub issues.

## 2023 Q4
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these items are quite old and I don't think they are serving much purpose anymore. Links to the more recent discussions I think are far more useful

For more information:

- Improve data output (`COPY`, `INSERT` and DataFrame) output capability [#6569](https://github.com/apache/datafusion/issues/6569)
- Implementation of `ARRAY` types and related functions [#6980](https://github.com/apache/datafusion/issues/6980)
- Write an industrial paper about DataFusion for SIGMOD [#6782](https://github.com/apache/datafusion/issues/6782)

## 2022 Q2

### DataFusion Core

- IO Improvements
- Reading, registering, and writing more file formats from both DataFrame API and SQL
- Additional options for IO including partitioning and metadata support
- Work Scheduling
- Improve predictability, observability and performance of IO and CPU-bound work
- Develop a more explicit story for managing parallelism during plan execution
- Memory Management
- Add more operators for memory limited execution
- Performance
- Incorporate row-format into operators such as aggregate
- Add row-format benchmarks
- Explore JIT-compiling complex expressions
- Explore LLVM for JIT, with inline Rust functions as the primary goal
- Improve performance of Sort and Merge using Row Format / JIT expressions
- Documentation
- General improvements to DataFusion website
- Publish design documents
- Streaming
- Create `StreamProvider` trait

### Ballista

- Make production ready
- Shuffle file cleanup
- Fill functional gaps between DataFusion and Ballista
- Improve task scheduling and data exchange efficiency
- Better error handling
- Task failure
- Executor lost
- Schedule restart
- Improve monitoring and logging
- Auto scaling support
- Support for multi-scheduler deployments. Initially for resiliency and fault tolerance but ultimately to support sharding for scalability and more efficient caching.
- Executor deployment grouping based on resource allocation

### Extensions ([datafusion-contrib](https://github.com/datafusion-contrib))

### [DataFusion-Python](https://github.com/datafusion-contrib/datafusion-python)

- Add missing functionality to DataFrame and SessionContext
- Improve documentation

### [DataFusion-S3](https://github.com/datafusion-contrib/datafusion-objectstore-s3)

- Create Python bindings to use with datafusion-python

### [DataFusion-Tui](https://github.com/datafusion-contrib/datafusion-tui)

- Create multiple SQL editors
- Expose more Context and query metadata
- Support new data sources
- BigTable, HDFS, HTTP APIs

### [DataFusion-BigTable](https://github.com/datafusion-contrib/datafusion-bigtable)

- Python binding to use with datafusion-python
- Timestamp range predicate pushdown
- Multi-threaded partition aware execution
- Production ready Rust SDK

### [DataFusion-Streams](https://github.com/datafusion-contrib/datafusion-streams)

- Create experimental implementation of `StreamProvider` trait
1. [Search for issues labeled `roadmap`](https://github.com/apache/datafusion/issues?q=is%3Aissue%20%20%20roadmap)
2. [DataFusion Road Map: Q3-Q4 2025](https://github.com/apache/datafusion/issues/15878)
3[2024 Q4 / 2025 Q1 Roadmap](https://github.com/apache/datafusion/issues/13274)