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Big Data Benchmarks, Performance Optimization, and Emerging Hardware

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Cover of 'Big Data Benchmarks, Performance Optimization, and Emerging Hardware'

Table of Contents

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    Book Overview
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    Chapter 1 On Big Data Benchmarking
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    Chapter 2 A Micro-benchmark Suite for Evaluating Hadoop MapReduce on High-Performance Networks
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    Chapter 3 MemTest: A Novel Benchmark for In-memory Database
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    Chapter 4 DSIMBench: A Benchmark for Microarray Data Using R
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    Chapter 5 A Benchmark to Evaluate Mobile Video Upload to Cloud Infrastructures
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    Chapter 6 Benchmarking Replication and Consistency Strategies in Cloud Serving Databases: HBase and Cassandra
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    Chapter 7 I/O Characterization of Big Data Workloads in Data Centers
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    Chapter 8 Characterizing Workload of Web Applications on Virtualized Servers
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    Chapter 9 Performance Benefits of DataMPI: A Case Study with BigDataBench
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    Chapter 10 InvarNet-X : A Comprehensive Invariant Based Approach for Performance Diagnosis in Big Data Platform
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    Chapter 11 Tuning Hadoop Map Slot Value Using CPU Metric
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    Chapter 12 A Study of SQL-on-Hadoop Systems
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    Chapter 13 Predoop: Preempting Reduce Task for Job Execution Accelerations
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    Chapter 14 Record Placement Based on Data Skew Using Solid State Drives
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    Chapter 15 Efficient HTTP Based I/O on Very Large Datasets for High Performance Computing with the Libdavix Library
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    Chapter 16 Exploring Opportunities for Non-volatile Memories in Big Data Applications
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Citations

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59 Mendeley
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Title
Big Data Benchmarks, Performance Optimization, and Emerging Hardware
Published by
Springer International Publishing, November 2014
DOI 10.1007/978-3-319-13021-7
ISBNs
978-3-31-913020-0, 978-3-31-913021-7
Editors

Zhan, Jianfeng, Han, Rui, Weng, Chuliang

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 59 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Brazil 3 5%
Morocco 1 2%
Unknown 55 93%

Demographic breakdown

Readers by professional status Count As %
Student > Master 17 29%
Student > Ph. D. Student 15 25%
Student > Bachelor 7 12%
Researcher 7 12%
Student > Doctoral Student 5 8%
Other 3 5%
Unknown 5 8%
Readers by discipline Count As %
Computer Science 39 66%
Engineering 8 14%
Social Sciences 2 3%
Economics, Econometrics and Finance 1 2%
Arts and Humanities 1 2%
Other 2 3%
Unknown 6 10%