mapreduce数据解析.pptVIP

大规模数据分析方法对比A Comparison of Approaches to Large-Scale Data Analysis Evaluation only. Created with Aspose.Slides for .NET 3.5 Client Profile 5.2.0.0. Copyright 2004-2011 Aspose Pty Ltd. 作者1：Andrew Pavlo ，Brown University 1 MapReduce and parallel DBMSs: friends or foes? 朋友还是冤家 2 A comparison of approaches to large-scale data analysis 3 H-store: a high-performance, distributed main memory transaction processing system 4 The NMI build test laboratory: continuous integration framework for distributed computing software 5 Smoother transitions between breadth-first-spanning-tree-based drawings 主要做Hadoop(Mapreduce)和并行数据库管理系统比较， 用于大规模数据集分析。 作者简介 Evaluation only. Created with Aspose.Slides for .NET 3.5 Client Profile 5.2.0.0. Copyright 2004-2011 Aspose Pty Ltd. 作者2 Erik Paulson， University of Wisconsin 1 MapReduce and parallel DBMSs: friends or foes? 2 A comparison of approaches to large-scale data analysis 3 Clustera: an integrated computation and data management system 和第一作者一样，主要做Hadoop(Mapreduce)和并行数据库管理系统比较，用于大规模数据集分析。 Evaluation only. Created with Aspose.Slides for .NET 3.5 Client Profile 5.2.0.0. Copyright 2004-2011 Aspose Pty Ltd. 作者3 Alexander Rasin ，Brown University 1 CORADD: correlation aware database designer for materialized views and indexes 2 MapReduce and parallel DBMSs: friends or foes? 3 HadoopDB: an architectural hybrid of MapReduce and DBMS technologies for analytical workloads 4 Correlation maps: a compressed access method for exploiting soft functional dependencies 5 A comparison of approaches to large-scale data analysis 6 H-store: a high-performance, distributed main memory transaction processing system 作者在本文的基础上，设计了HadoopDB系统，一个Mapreduce和并行数据库管理系统结合的系统。 Evaluation only. Created with Aspose.Slides for .NET 3.5 Client Profile 5.2.0.0. Copyright 2004-2011 Aspose Pty Ltd. 摘要 目前有相当大的兴趣在基于MapReduce（MR）模式的大规模数据分析。虽然这个框架的基本控制流已经存在于并行SQL数据库管理系统超过20年，也有人称MR为必威体育精装版的计算模型。在本文中，我们描述和比较这两个模式。此外，我们评估两个系统的性能和开发复杂度。最后，我们定义一个包含任务集的基准运行于MR开源平台和两个并行数据库管理系统上。对于每个任务，我们在10