The Vision of BigBench 2.0

T. Rabl, Michael Frank, Manuel Danisch, H. Jacobsen, B. Gowda
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引用次数: 14

Abstract

Data is one of the most important resources for modern enterprises. Better analytics allow for a better understanding of customer requirements and market dynamics. The more data is collected, the more information can be extracted. However, information value extraction is limited by data processing speeds. Due to fast technological advances in big data management there is an abundance of big data systems. This leaves users in the dilemma of choosing a system that features good end-to-end performance for the use case. To get a good understanding of the actual performance of a system, realistic application level workloads are required. To this end, we have developed BigBench, an application level benchmark focused only on big data analytics. In this paper, we present the vision of BigBench 2.0, a suite of benchmarks for all major aspects of big data processing in common business use cases. Unlike other efforts, BigBench 2.0 will have completely consistent and integrated model and workload, which will allow realistic end-to-end benchmarking of big data systems.
BigBench 2.0的愿景
数据是现代企业最重要的资源之一。更好的分析允许更好地理解客户需求和市场动态。收集的数据越多,提取的信息也就越多。然而,信息价值的提取受到数据处理速度的限制。由于大数据管理技术的快速发展,出现了大量的大数据系统。这让用户陷入两难的境地,需要为用例选择具有良好端到端性能的系统。为了更好地理解系统的实际性能,需要实际的应用程序级工作负载。为此,我们开发了BigBench,这是一个专注于大数据分析的应用级基准测试。在本文中,我们提出了BigBench 2.0的愿景,这是一套针对常见业务用例中大数据处理所有主要方面的基准测试。与其他版本不同的是,BigBench 2.0将拥有完全一致和集成的模型和工作负载,这将允许对大数据系统进行实际的端到端基准测试。
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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