具有资源感知缓冲和图形压缩的流图摄取

2019 15th International Conference on eScience (eScience) Pub Date : 2019-09-01 DOI:10.1109/eScience.2019.00087

S. Dasgupta, A. Bagchi, Amarnath Gupta

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引用次数: 1

摘要

从社交媒体中摄取高速流数据到图形数据库必须克服三个问题:1)数据可能真的是突发的，2)数据必须转换成图形，3)图形数据库可能无法摄取高突发、高速的数据。我们已经开发了一种自适应缓冲机制和一种图形压缩技术，可以有效地缓解这个问题。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Streaming Graph Ingestion with Resource-Aware Buffering and Graph Compression

Ingesting high-speed streaming data from social media into a graph database must overcome three problems – 1) the data can be really bursty, 2) the data must be transformed into a graph and 3) the graph database may not be able to ingest high-burst, high-velocity data. We have developed an adaptive buffering mechanism and a graph compression technique that effectively mitigate the problem.

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2019 15th International Conference on eScience (eScience)

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