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推出 Data+AI 开发 Notebook，集成 Spark、Ray、Hive 等引擎，支持 Python/SQL 混合编程，实现从数据处理到模型推理的一站式开发。结合 Copilot Agent 模式，提供任务自动执行、代码生成、作业调试等智能辅助功能，显著降低 AI 开发门槛。
，这一点在新收录的资料中也有详细论述
As a new user, ClickHouse can often seem like magic - every query is super fast, even on the largest datasets and most ambitious queries. Invariably though, real-world usage tests even the limits of ClickHouse. Queries exceeding memory can be the result of a number of causes. Most commonly, we see large joins or aggregations on high cardinality fields. If performance is critical, and these queries are required, we often recommend users simply scale up - something ClickHouse Cloud does automatically and effortlessly to ensure your queries remain responsive. In self-managed clusters, this is sometimes not trivial, and users have a few options:
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