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这项由上海交通大学主导，联合清华大学、新加坡国立大学以及蚂蚁集团共同开展的研究，发表于2026年6月的ACM数据管理顶级期刊《Proceedings of the ACM on Management of Data》第4卷第3期（SIGMOD 2026），论文编号为Article 141，DOI为10.1145/3802018。

本文并非官方文档的简单翻译，而是结合多方信息源和实战经验，对 Spark 3 到 Spark 4 的迁移进行一次系统性梳理。我们将从"必须改"、"容易踩坑"、"值得利用"三个维度，帮助你制定一个清晰的迁移路线图。

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现在的 LLM 就像一个只有瞬时记忆的聪明人，每一次 API 调用都是一次“转世”。你觉得它记得你，其实是因为你在每次请求时都把之前的聊天记录重新塞了回去。这种做法在简单的闲聊里没问题，但一旦进入复杂的任务流，Agent 就会开始频繁“断片”：问它昨天说了什么，它一脸茫然；遇到多步任务，中间状态直接丢失。

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