TelegraphCQ: continuous dataflow processing-猫眼课题宝

DOI：

10.1145/872757.872857

发表时间：

2003-06

期刊：

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其他

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作者：

Sirish Chandrasekaran;Owen Cooper;A. Deshpande;M. Franklin;J. Hellerstein;W. Hong;S. Krishnamurthy;S. Madden;Frederick Reiss;Mehul A. Shah

在伯克利，我们正在开发TelegraphCQ [1，2]，这是一个用于处理数据流的连续查询的数据流系统。 TelegraphCQ基于一种新颖的，高度适应性的体系结构，该体系结构支持动态数据流环境中的动态查询工作负载。在此演示中，我们显示了当前版本的TelegraphCQ，我们通过利用开源PostgreSQL数据库系统的代码库来实现。尽管TelegraphCQ与传统的数据库系统有很大不同，但我们发现，PostgreSQL代码的很大一部分很容易重复使用。我们还发现PostgreSQL的可扩展功能非常有用，尤其是其丰富的数据类型以及加载用户开发功能的能力。挑战：如[1]中讨论的那样，共享和适应性是我们实施连续查询系统的主要技术。在常规数据库的代码库中执行此操作提出了许多挑战：

At Berkeley, we are developing TelegraphCQ [1, 2], a dataflow system for processing continuous queries over data streams. TelegraphCQ is based on a novel, highly-adaptive architecture supporting dynamic query workloads in volatile data streaming environments. In this demonstration we show our current version of TelegraphCQ, which we implemented by leveraging the code base of the open source PostgreSQL database system. Although TelegraphCQ differs significantly from a traditional database system, we found that a significant portion of the PostgreSQL code was easily reusable. We also found the extensibility features of PostgreSQL very useful, particularly its rich data types and the ability to load user-developed functions. Challenges: As discussed in [1], sharing and adaptivity are our main techniques for implementing a continuous query system. Doing this in the codebase of a conventional database posed a number of challenges:

TelegraphCQ: continuous dataflow processing

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