Distributed Publish/Subscribe Query Processing on the Spatio-Textual Data Stream
Distributed Publish/Subscribe Query Processing on the Spatio-Textual Data Stream
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DOI：
10.1109/icde.2017.154
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发表时间：
2016-12
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影响因子：
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通讯作者：
Zhida Chen;G. Cong;Zhenjie Zhang;T. Fu;Lisi Chen
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文献类型：
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作者：
Zhida Chen;G. Cong;Zhenjie Zhang;T. Fu;Lisi Chen
包含空间和文本信息的大量数据，例如，带有地理标签的推特在网上泛滥这样的空间文本数据流包含有价值的信息，数以百万计的用户与不同的关键字和位置的各种利益。发布/订阅系统通过允许用户注册具有空间和文本约束的连续查询来实现高效和有效的信息分发。然而，数据规模和用户群的爆炸性增长对现有的空间文本数据流集中发布/订阅系统提出了挑战。在本文中，我们提出了我们的分布式发布/订阅系统，称为PS2 Stream，它提供了一个巨大的空间文本数据流，并将流定向到目标用户注册的兴趣。与现有系统相比，PS2 Stream在最小化工作负载总量和平衡工作人员负载方面实现了更好的工作负载分配。为了实现这一目标，我们提出了一种新的工作负载分配算法，同时考虑数据的空间和文本属性。此外，PS2 Stream支持动态负载调整，以适应工作负载的变化，这使得PS2 Stream自适应。在商用云计算平台上，通过对真实的数据进行大量的实证评估，验证了系统设计的优越性和技术在系统性能提升方面的优势。
Huge amount of data with both space and text information, e.g., geo-tagged tweets, is flooding on the Internet. Such spatio-textual data stream contains valuable information for millions of users with various interests on different keywords and locations. Publish/subscribe systems enable efficient and effective information distribution by allowing users to register continuous queries with both spatial and textual constraints. However, the explosive growth of data scale and user base has posed challenges to the existing centralized publish/subscribe systems for spatiotextual data streams. In this paper, we propose our distributed publish/subscribe system, called PS2Stream, which digests a massive spatio-textual data stream and directs the stream to target users with registered interests. Compared with existing systems, PS2Stream achieves a better workload distribution in terms of both minimizing the total amount of workload and balancing the load of workers. To achieve this, we propose a new workload distribution algorithm considering both space and text properties of the data. Additionally, PS2Stream supports dynamic load adjustments to adapt to the change of the workload, which makes PS2Stream adaptive. Extensive empirical evaluation, on commercial cloud computing platform with real data, validates the superiority of our system design and advantages of our techniques on system performance improvement.