I am very supportive of this donation. I know of at least one other DataFusion-based project, blaze-rs[1], which has the same design goal and bringing this project into the ASF may help consolidate these efforts
As Andy said, I believe it was very valuable to have a major consumer project (e.g. DataFusion) to help drive the definition and implementation of arrow-rs implementation. We never achieved the same synergy with Ballista and DataFusion but I think it is more likely with a more actively maintained Spark accelerator. I am not sure it affects this discussion, but the Gluten project, based on Velox, was accepted yesterday[2] into the Apache Incubator[2]. While the functionality may be similar, the technology (Rust vs C/C++) and the communities are different so having both in the same (big) tent of the ASF doesn't seem concerning to me. Also, as Chao says, I think this new sub project would naturally move to a new DataFusion top level project when we get there (we plan a proposed resolution April ASF board meeting) Looking forward to seeing more! Andrew [1]: https://github.com/blaze-init/blaze [2]: https://lists.apache.org/thread/6lrozds10jn9gknj9rf74lqbh7j55pq6 On Wed, Jan 10, 2024 at 5:10 PM Andy Grove <andygrov...@gmail.com> wrote: > Hi Chao, > > This sounds like a really interesting project. I am interested in seeing > how it compares to Spark RAPIDS (the project that I work on at NVIDIA) and > Intel's Gluten project (that works with Velox). > > I can see the following benefits of having this project being under Apache > Arrow governance: > > - Assuming that this is a drop-in replacement that doesn't require users to > change their code (as I imagine is the case), then it could lead to greater > adoption of DataFusion, especially for more demanding use cases where > processing on a single node is not possible. > - Given that it has a deep integration with the Rust implementation of > Arrow as well as DataFusion, and given the overlap of committers between > these projects, having them under the same governance and communication > channels will generally be more efficient than if this project is separate. > - Hopefully this leads to more upstream contributions to DataFusion, > perhaps even allowing other projects such as Ballista to benefit from > Spark-compatible operators and expressions in the future. > - Having another project that uses DataFusion as a dependency could help > with stabilizing the public APIs and generally driving more innovation. > > Given these points, I would be supportive of a donation. I see it as being > similar to the Ballista project, which is already part of Arrow (and we > plan to move along with DataFusion once it becomes a top-level project). > > Thanks, > > Andy. > > On Wed, Jan 10, 2024 at 2:28 PM Chao Sun <sunc...@apache.org> wrote: > > > Hi all, > > > > We have been working on a native execution engine for Apache Spark > > that is heavily based on DataFusion and Arrow. Our goal is to > > accelerate Spark query execution via delegating Spark's physical plan > > execution to DataFusion's highly modular execution framework, while > > still maintaining the same semantics to Spark users (i.e., no Spark > > behavior change from the end users' point of view). Several of us are > > Spark and/or Arrow committers. At the moment, the project is under > > active development and not yet feature complete. However, some of the > > existing functionalities are relatively mature and have been put in > > production for a while now. > > > > Given the current momentum towards accelerating Spark through native > > vectorized execution, we believe open sourcing this work will benefit > > other Spark users too. In addition, we think the project itself can > > also leverage the vibrant and strong community behind Arrow and > > DataFusion, and grow faster. Because of this, we are exploring the > > possibility of contributing this project to the Apache Software > > Foundation (ASF) under the Apache Arrow project umbrella. > > > > We'd very much like to hear your opinion on this. Thanks. > > > > Best, > > Chao > > >
