文件名称:
Big.Data.Benchmarks.Performance.Optimization.and.Emerging.Hardware
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上传时间: 2016-06-01
详细说明： Big Data Benchmarks, Performance Optimization, and Emerging Hardware: 6th Workshop, BPOE 2015, Kohala, HI, USA, August 31 - September 4, 2015. Revised ... Papers (Lecture Notes in Computer Science) This book constitutes the thoroughly revised selected papers of the 6th workshop on Big Data Benchmarks, Performance Optimization, and Emerging Hardware, BPOE 2015, held in Kohala Coast, HI, USA, in August/September 2015 as satellite event of VLDB 2015, the 41st International Conference on Very Large Data Bases. The 8 papers presented were carefully reviewed and selected from 10 submissions. The workshop focuses on architecture and system support for big data systems, aiming at bringing researchers and practitioners from data management, architecture, and systems research communities together to discuss the research issues at the intersection of these areas. This book also invites three papers from several industrial partners, including two papers describing tools used in system benchmarking and monitoring and one paper discussing principles and methodologies in existing big data benchmarks. Table of Contents Part 1 Benchmarking Chapter 1 Revisiting Benchmarking Principles and Methodologies for Big Data Benchmarking Chapter 2 BigDataBench-MT: A Benchmark Tool for Generating Realistic Mixed Data Center Workloads Part 2 Benchmarking and Workload Characterization Chapter 3 Towards a Big Data Benchmarking and Demonstration Suite for the Online Social Network Era with Realistic Workloads and Live Data Chapter 4 On Statistical Characteristics of Real-Life Knowledge Graphs Chapter 5 Mbench: Benchmarking a Multicore Operating System Using Mixed Workloads Part 3 Performance Optimization and Evaluation Chapter 6 Evolution from Shark to Spark SQL: Preliminary Analysis and Qualitative Evaluation Chapter 7 How Data Volume Affects Spark Based Data Analytics on a Scale-up Server Chapter 8 An Optimal Reduce Placement Algorithm for Data Skew Based on Sampling Chapter 9 AAA: A Massive Data Acquisition Approach in Large-Scale System Monitoring Part 4 Emerging Hardware Chapter 10 A Plugin-Based Approach to Exploit RDMA Benefits for Apache and Enterprise HDFS Chapter 11 Stream-Based Lossless Data Compression Hardware Using Adaptive Frequency Table Management ...展开收缩
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