Overview <overview> quickstart user-guide examples api/api data-internals
Ray Data is a scalable data processing library for ML workloads. It provides flexible and performant APIs for scaling Offline batch inference <batch_inference_overview> and Data preprocessing and ingest for ML training <ml_ingest_overview>. Ray Data uses streaming execution to efficiently process large datasets.
To install Ray Data, run:
$ pip install -U 'ray[data]'To learn more about installing Ray and its libraries, see Installing Ray <installation>.
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Ray Data Overview ^^^
Get an overview of Ray Data, the workloads that it supports, and how it compares to alternatives.
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Ray Data Overview
Quickstart ^^^
Understand the key concepts behind Ray Data. Learn what Datasets are and how they're used.
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Quickstart
User Guides ^^^
Learn how to use Ray Data, from basic usage to end-to-end guides.
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Learn how to use Ray Data
Examples ^^^
Find both simple and scaling-out examples of using Ray Data.
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Ray Data Examples
API ^^^
Get more in-depth information about the Ray Data API.
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Read the API Reference
Ray Blogs ^^^
Get the latest on engineering updates from the Ray team and how companies are using Ray Data.
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Read the Ray blogs