chenquan

Today, with great excitement, we proudly introduce a revolutionary update to the ArkFlow stream processing engine: full support for Python processors! This is not just a simple feature iteration; it marks a solid step towards more intelligent, user-friendly, and powerful real-time data processing. We are keenly aware of Python's immense influence and its vast ecosystem in the fields of artificial intelligence and machine learning. Now, with ArkFlow, you can seamlessly integrate all of this into high-performance, real-time stream processing pipelines.

In the recently merged PR, ArkFlow supports Python processors, which allows us to call Python scripts directly in ArkFlow. Using the Pyarrow library allows users to write data processing logic more freely. At the same time, relying on Python's powerful AI ecosystem, ArkFlow will also be able to call any Python machine learning/deep learning library (TensorFlow, PyTorch, etc.) and large models. We will have more detailed articles to introduce relevant use cases in the future.

Hello, I am the founder of this project and I am very happy that a friend has shared it.

ArkFlow is positioned as a lightweight distributed stream processing engine that integrates streaming batches. With the help of datafusion's huge ecosystem and ArkFlow's scalable capabilities, we hope to build a huge data processing ecosystem to help the community simplify the threshold for data processing, because we always believe that flowing data can generate greater value.

Finally, thanks to everyone for their attention.

I’m grateful for your assistance.

Hi, then I'm curious what do you think people care most about in data processing and database workloads?

Yeah, I'm looking forward to having further conversations once I get to know tremor.

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I don't know it exists.

Hi, friend. How did you do it specifically?

> Stability and safety are the least of the concerns in data processing and database workloads.

I'm curious how you came to this conclusion?

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