the project is still alpha, but the core is getting more solid with each release. would love feedback, especially from anyone who has experience tuning io_uring-based servers. i'm sure there's still a lot of room to squeeze more out of it. :)
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Melissa Etheridge
在 AI 场景中，Apache Spark 凭借其强大的批处理能力与 Python 生态兼容性，广泛用于大模型训练前的数据清洗、特征工程与推理任务。而 Ray 因其低延迟、高并发特性，被 OpenAI 等头部机构用于分布式训练与强化学习。两者共同构成 Data + AI 的核心计算底座，支持从数据准备到模型推理的全流程高效执行。