作者
Peter Alvaro, Tyson Condie, Neil Conway, Khaled Elmeleegy, Joseph M Hellerstein, Russell C Sears
发表日期
2009/7/9
期刊
EECS Department, University of California, Berkeley, Tech. Rep. UCB/EECS-2009-113
简介
Cloud computing makes datacenter clusters a commodity, potentially enabling a wide range of programmers to develop new scalable services. However, current cloud platforms do little to simplify truly distributed systems development. In this paper, we explore the use of a declarative, data-centric programming model to achieve this simplicity. We describe our experience using Overlog and Java to implement a “Big Data” analytics stack that is API-compatible with Hadoop and HDFS, with equivalent performance. We extended the system with complex features not yet available in Hadoop, including availability, scalability, and unique monitoring and debugging facilities. We present our experience to validate the enhanced programmer productivity afforded by declarative programming, and inform the design of new development environments for distributed programming.
引用总数
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学术搜索中的文章
P Alvaro, T Condie, N Conway, K Elmeleegy… - EECS Department, University of California, Berkeley …, 2009