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Shark:使用粗粒度的分布式内存进行数据的快速分析

Shark: Fast Data Analysis Using Coarse-grained Distributed Memory

作者:Clifford Engle 加工时间:2013-12-18 信息来源:EECS 索取原文[30 页]
关键词:分布式内存;快速分析;数据分析
摘 要:Shark is a research data analysis system built on a novel coarse-grained distributed shared-memory abstraction. Shark marries query processing with deep data analysis, providing a uni ed system for easy data manipulation using SQL and pushing sophisticated analysis closer to data. It scales to thousands of nodes in a fault-tolerant manner. Shark can answer queries 40X faster than Apache Hive and run machine learning programs 25X faster than MapReduce programs in Apache Hadoop on large datasets. This is a complete overview of the development of Shark, including design decisions, performance details, and comparison with existing data warehousing solutions. It demonstrates some of Shark's distinguishing features including its in-memory columnar caching and its uni ed machine learning interface.
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