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Beyond Hadoop: Recent Directions in Data Computing for Internet Services

Beyond Hadoop: Recent Directions in Data Computing for Internet Services

Zhiwei Xu, Bo Yan, Yongqiang Zou
Copyright: © 2011 |Volume: 1 |Issue: 1 |Pages: 17
ISSN: 2156-1834|EISSN: 2156-1826|EISBN13: 9781613505953|DOI: 10.4018/ijcac.2011010104
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MLA

Xu, Zhiwei, et al. "Beyond Hadoop: Recent Directions in Data Computing for Internet Services." IJCAC vol.1, no.1 2011: pp.45-61. https://doi.org/10.4018/ijcac.2011010104

APA

Xu, Z., Yan, B., & Zou, Y. (2011). Beyond Hadoop: Recent Directions in Data Computing for Internet Services. International Journal of Cloud Applications and Computing (IJCAC), 1(1), 45-61. https://doi.org/10.4018/ijcac.2011010104

Chicago

Xu, Zhiwei, Bo Yan, and Yongqiang Zou. "Beyond Hadoop: Recent Directions in Data Computing for Internet Services," International Journal of Cloud Applications and Computing (IJCAC) 1, no.1: 45-61. https://doi.org/10.4018/ijcac.2011010104

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Abstract

As a main subfield of cloud computing applications, internet services require large-scale data computing. Their workloads can be divided into two classes: customer-facing query-processing interactive tasks that serve hundreds of millions of users within a short response time and backend data analysis batch tasks that involve petabytes of data. Hadoop, an open source software suite, is used by many Internet services as the main data computing platform. Hadoop is also used by academia as a research platform and an optimization target. This paper presents five research directions for optimizing Hadoop; improving performance, utilization, power efficiency, availability, and different consistency constraints. The survey covers both backend analysis and customer-facing workloads. A total of 15 innovative techniques and systems are analyzed and compared, focusing on main research issues, innovative techniques, and optimized results.

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