Randoms sampling from data streams is a problem with a long history of studies, starting from the famous reservoir sampling algorithm that is at least 50 years old [2]. The reservoir sampling algorithm maintains a random sample over all data items that have ever been received from the stream. This is not suitable for many of today's applications on evolving data streams, where recent data is more important than older ones.

中文翻译：

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技术视角

从数据流中随机采样是一个有着悠久研究历史的问题，从至少有 50 年历史的著名的油藏采样算法开始 [2]。水库采样算法对曾经从流中接收到的所有数据项进行随机采样。这不适用于当今关于不断发展的数据流的许多应用程序，在这些应用程序中，最近的数据比旧的数据更重要。