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A Profiling And Performance Analysis Based Self Tuning System For Optimization Of Hadoop Mapreduce Cluster Configuration
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Book Synopsis A Profiling and Performance Analysis Based Self-tuning System for Optimization of Hadoop MapReduce Cluster Configuration by : Dili Wu
Download or read book A Profiling and Performance Analysis Based Self-tuning System for Optimization of Hadoop MapReduce Cluster Configuration written by Dili Wu and published by . This book was released on 2013 with total page 40 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Algorithms and Architectures for Parallel Processing by : Meikang Qiu
Download or read book Algorithms and Architectures for Parallel Processing written by Meikang Qiu and published by Springer Nature. This book was released on 2020-09-29 with total page 722 pages. Available in PDF, EPUB and Kindle. Book excerpt: This three-volume set LNCS 12452, 12453, and 12454 constitutes the proceedings of the 20th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2020, in New York City, NY, USA, in October 2020. The total of 142 full papers and 5 short papers included in this proceedings volumes was carefully reviewed and selected from 495 submissions. ICA3PP is covering the many dimensions of parallel algorithms and architectures, encompassing fundamental theoretical approaches, practical experimental projects, and commercial components and systems. As applications of computing systems have permeated in every aspects of daily life, the power of computing system has become increasingly critical. This conference provides a forum for academics and practitioners from countries around the world to exchange ideas for improving the efficiency, performance, reliability, security and interoperability of computing systems and applications. ICA3PP 2020 focus on two broad areas of parallel and distributed computing, i.e. architectures, algorithms and networks, and systems and applications.
Book Synopsis Intelligent Computing by : Kohei Arai
Download or read book Intelligent Computing written by Kohei Arai and published by Springer. This book was released on 2018-11-01 with total page 1390 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book, gathering the Proceedings of the 2018 Computing Conference, offers a remarkable collection of chapters covering a wide range of topics in intelligent systems, computing and their real-world applications. The Conference attracted a total of 568 submissions from pioneering researchers, scientists, industrial engineers, and students from all around the world. These submissions underwent a double-blind peer review process. Of those 568 submissions, 192 submissions (including 14 poster papers) were selected for inclusion in these proceedings. Despite computer science’s comparatively brief history as a formal academic discipline, it has made a number of fundamental contributions to science and society—in fact, along with electronics, it is a founding science of the current epoch of human history (‘the Information Age’) and a main driver of the Information Revolution. The goal of this conference is to provide a platform for researchers to present fundamental contributions, and to be a premier venue for academic and industry practitioners to share new ideas and development experiences. This book collects state of the art chapters on all aspects of Computer Science, from classical to intelligent. It covers both the theory and applications of the latest computer technologies and methodologies. Providing the state of the art in intelligent methods and techniques for solving real-world problems, along with a vision of future research, the book will be interesting and valuable for a broad readership.
Book Synopsis Big Data – BigData 2020 by : Surya Nepal
Download or read book Big Data – BigData 2020 written by Surya Nepal and published by Springer Nature. This book was released on 2020-09-17 with total page 264 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the proceedings of the 9th International Conference on Big Data, BigData 2020, held as part of SCF 2020, during September 18-20, 2020. The conference was planned to take place in Honolulu, HI, USA and was changed to a virtual format due to the COVID-19 pandemic. The 16 full and 3 short papers presented were carefully reviewed and selected from 52 submissions. The topics covered are Big Data Architecture, Big Data Modeling, Big Data As A Service, Big Data for Vertical Industries (Government, Healthcare, etc.), Big Data Analytics, Big Data Toolkits, Big Data Open Platforms, Economic Analysis, Big Data for Enterprise Transformation, Big Data in Business Performance Management, Big Data for Business Model Innovations and Analytics, Big Data in Enterprise Management Models and Practices, Big Data in Government Management Models and Practices, and Big Data in Smart Planet Solutions.
Book Synopsis Communication and Computing Systems by : B.M.K. Prasad
Download or read book Communication and Computing Systems written by B.M.K. Prasad and published by CRC Press. This book was released on 2017-02-15 with total page 1130 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is a collection of accepted papers that were presented at the International Conference on Communication and Computing Systems (ICCCS-2016), Dronacharya College of Engineering, Gurgaon, September 9–11, 2016. The purpose of the conference was to provide a platform for interaction between scientists from industry, academia and other areas of society to discuss the current advancements in the field of communication and computing systems. The papers submitted to the proceedings were peer-reviewed by 2-3 expert referees. This volume contains 5 main subject areas: 1. Signal and Image Processing, 2. Communication & Computer Networks, 3. Soft Computing, Intelligent System, Machine Vision and Artificial Neural Network, 4. VLSI & Embedded System, 5. Software Engineering and Emerging Technologies.
Book Synopsis Intelligent Sustainable Systems by : Atulya K. Nagar
Download or read book Intelligent Sustainable Systems written by Atulya K. Nagar and published by Springer Nature. This book was released on with total page 605 pages. Available in PDF, EPUB and Kindle. Book excerpt:
Book Synopsis Big Data Benchmarks, Performance Optimization, and Emerging Hardware by : Jianfeng Zhan
Download or read book Big Data Benchmarks, Performance Optimization, and Emerging Hardware written by Jianfeng Zhan and published by Springer. This book was released on 2014-11-10 with total page 227 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book constitutes the thoroughly revised selected papers of the 4th and 5th workshops on Big Data Benchmarks, Performance Optimization, and Emerging Hardware, BPOE 4 and BPOE 5, held respectively in Salt Lake City, in March 2014, and in Hangzhou, in September 2014. The 16 papers presented were carefully reviewed and selected from 30 submissions. Both workshops focus on architecture and system support for big data systems, such as benchmarking; workload characterization; performance optimization and evaluation; emerging hardware.
Book Synopsis Algorithms and Architectures for Parallel Processing by : Guojun Wang
Download or read book Algorithms and Architectures for Parallel Processing written by Guojun Wang and published by Springer. This book was released on 2015-11-16 with total page 880 pages. Available in PDF, EPUB and Kindle. Book excerpt: This four volume set LNCS 9528, 9529, 9530 and 9531 constitutes the refereed proceedings of the 15th International Conference on Algorithms and Architectures for Parallel Processing, ICA3PP 2015, held in Zhangjiajie, China, in November 2015. The 219 revised full papers presented together with 77 workshop papers in these four volumes were carefully reviewed and selected from 807 submissions (602 full papers and 205 workshop papers). The first volume comprises the following topics: parallel and distributed architectures; distributed and network-based computing and internet of things and cyber-physical-social computing. The second volume comprises topics such as big data and its applications and parallel and distributed algorithms. The topics of the third volume are: applications of parallel and distributed computing and service dependability and security in distributed and parallel systems. The covered topics of the fourth volume are: software systems and programming models and performance modeling and evaluation.
Book Synopsis Optimizing Hadoop for MapReduce by : Khaled Tannir
Download or read book Optimizing Hadoop for MapReduce written by Khaled Tannir and published by Packt Publishing Ltd. This book was released on 2014-02-21 with total page 162 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is an example-based tutorial that deals with Optimizing Hadoop for MapReduce job performance. If you are a Hadoop administrator, developer, MapReduce user, or beginner, this book is the best choice available if you wish to optimize your clusters and applications. Having prior knowledge of creating MapReduce applications is not necessary, but will help you better understand the concepts and snippets of MapReduce class template code.
Book Synopsis Energy Efficiency in Data Centers and Clouds by :
Download or read book Energy Efficiency in Data Centers and Clouds written by and published by Academic Press. This book was released on 2016-01-28 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Computers carries on a tradition of excellence, presenting detailed coverage of innovations in computer hardware, software, theory, design, and applications. The book provides contributors with a medium in which they can explore their subjects in greater depth and breadth than journal articles typically allow. The articles included in this book will become standard references, with lasting value in this rapidly expanding field. Presents detailed coverage of recent innovations in computer hardware, software, theory, design, and applications Includes in-depth surveys and tutorials on new computer technology pertaining to computing: combinatorial testing, constraint-based testing, and black-box testing Written by well-known authors and researchers in the field Includes extensive bibliographies with most chapters Presents volumes devoted to single themes or subfields of computer science
Book Synopsis A Framework for Automatic Optimization of MapReduce Programs Based on Job Parameter Configurations by : Praveen Kumar Lakkimsetti
Download or read book A Framework for Automatic Optimization of MapReduce Programs Based on Job Parameter Configurations written by Praveen Kumar Lakkimsetti and published by . This book was released on 2011 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Recently, cost-effective and timely processing of large datasets has been playing an important role in the success of many enterprises and the scientific computing community. Two promising trends ensure that applications will be able to deal with ever increasing data volumes: first, the emergence of cloud computing, which provides transparent access to a large number of processing, storage and networking resources; and second, the development of the MapReduce programming model, which provides a high-level abstraction for data-intensive computing. MapReduce has been widely used for large-scale data analysis in the Cloud [5]. The system is well recognized for its elastic scalability and fine-grained fault tolerance. However, even to run a single program in a MapReduce framework, a number of tuning parameters have to be set by users or system administrators to increase the efficiency of the program. Users often run into performance problems because they are unaware of how to set these parameters, or because they don't even know that these parameters exist. With MapReduce being a relatively new technology, it is not easy to find qualified administrators [4]. The major objective of this project is to provide a framework that optimizes MapReduce programs that run on large datasets. This is done by executing the MapReduce program on a part of the dataset using stored parameter combinations and setting the program with the most efficient combination and this modified program can be executed over the different datasets. We know that many MapReduce programs are used over and over again in applications like daily weather analysis, log analysis, daily report generation etc. So, once the parameter combination is set, it can be used on a number of data sets efficiently. This feature can go a long way towards improving the productivity of users who lack the skills to optimize programs themselves due to lack of familiarity with MapReduce or with the data being processed.
Book Synopsis Data Algorithms by : Mahmoud Parsian
Download or read book Data Algorithms written by Mahmoud Parsian and published by "O'Reilly Media, Inc.". This book was released on 2015-07-13 with total page 778 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you are ready to dive into the MapReduce framework for processing large datasets, this practical book takes you step by step through the algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for solving a massive computational problem, such as building a recommendation system. You’ll learn how to implement the appropriate MapReduce solution with code that you can use in your projects. Dr. Mahmoud Parsian covers basic design patterns, optimization techniques, and data mining and machine learning solutions for problems in bioinformatics, genomics, statistics, and social network analysis. This book also includes an overview of MapReduce, Hadoop, and Spark. Topics include: Market basket analysis for a large set of transactions Data mining algorithms (K-means, KNN, and Naive Bayes) Using huge genomic data to sequence DNA and RNA Naive Bayes theorem and Markov chains for data and market prediction Recommendation algorithms and pairwise document similarity Linear regression, Cox regression, and Pearson correlation Allelic frequency and mining DNA Social network analysis (recommendation systems, counting triangles, sentiment analysis)
Book Synopsis Designing and Modeling High-performance Mapreduce and DAG Execution Framework on Modern HPC Systems by : Md. Wasi-ur- Rahman
Download or read book Designing and Modeling High-performance Mapreduce and DAG Execution Framework on Modern HPC Systems written by Md. Wasi-ur- Rahman and published by . This book was released on 2016 with total page 213 pages. Available in PDF, EPUB and Kindle. Book excerpt: Big Data processing and High-Performance Computing (HPC) are two disruptive technologies that are converging to meet the challenges exposed by large-scale data analysis. MapReduce, a popular parallel programming model for data-intensive applications, is being used extensively through different execution frameworks (e.g. batch processing, Directed Acyclic Graph or DAG) on modern HPC systems because of its ease-of-programming, fault-tolerance, and scalability. However, as these applications begin scaling to terabytes of data, the socket-based communication model, which is the default implementation in the open-source MapReduce execution frameworks, demonstrates performance bottleneck. Moreover, because of the synchronized nature of stocking the data in various execution phases, the default Hadoop MapReduce framework cannot leverage the full potential of the underlying interconnect. MapReduce frameworks also rely heavily on the availability of the local storage media, which introduces space inadequacy for applications that generate a large amount of intermediate data. On the other hand, most leadership-class HPC systems follow the traditional Beowulf architecture with separate parallel storage system and either no, or very limited, local storage. The storage architectures in these HPC systems are not naively conducive for default MapReduce. Also, modern high performance interconnects (e.g. InfiniBand) used to access the parallel storage in these systems can provide extremely low latency and high bandwidth. Additionally, advanced storage architectures, such as Non-Volatile Memories (NVM), can provide byte-addressability as well as data persistence. Efficient utilization of all these resources through enhanced designs of execution frameworks with tuned parameter space is crucial for MapReduce in terms of performance and scalability. This work addresses several of the shortcomings that the current MapReduce execution frameworks hold. It presents an enhanced Big Data execution framework, HOMR (Hybrid Overlapping in MapReduce), which improves the MapReduce job execution pipeline by maximizing overlapping among execution phases. HOMR also introduces RDMA (Remote Direct Memory Access) based shuffle engine with advanced shuffle algorithms to leverage the benefits of high-performance interconnects used in HPC systems. It minimizes the large number of disk accesses in the MapReduce execution frameworks through in-memory operations combined with fast execution pipeline. This work also proposes different deployment architectures while utilizing Lustre as underlying storage and provides fast shuffle strategies with dynamic adjustments. The priority based storage selection for intermediate data storage ensures the best storage usage at any point of job execution. This work also presents a variant of HOMR, that can exploit the byte-addressability of NVM to provide fast execution of MapReduce applications. Finally, a generalized advising framework is presented in this work that can provide optimum configuration recommendations for any MapReduce system with profiling and prediction capabilities. Through performance modeling of this MapReduce execution framework, techniques of predicting job execution performance are demonstrated on leadership-class HPC clusters at large scale.
Book Synopsis Data-Intensive Text Processing with MapReduce by : Jimmy Lin
Download or read book Data-Intensive Text Processing with MapReduce written by Jimmy Lin and published by Springer Nature. This book was released on 2022-05-31 with total page 171 pages. Available in PDF, EPUB and Kindle. Book excerpt: Our world is being revolutionized by data-driven methods: access to large amounts of data has generated new insights and opened exciting new opportunities in commerce, science, and computing applications. Processing the enormous quantities of data necessary for these advances requires large clusters, making distributed computing paradigms more crucial than ever. MapReduce is a programming model for expressing distributed computations on massive datasets and an execution framework for large-scale data processing on clusters of commodity servers. The programming model provides an easy-to-understand abstraction for designing scalable algorithms, while the execution framework transparently handles many system-level details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text processing algorithms common in natural language processing, information retrieval, and machine learning. We introduce the notion of MapReduce design patterns, which represent general reusable solutions to commonly occurring problems across a variety of problem domains. This book not only intends to help the reader "think in MapReduce", but also discusses limitations of the programming model as well. Table of Contents: Introduction / MapReduce Basics / MapReduce Algorithm Design / Inverted Indexing for Text Retrieval / Graph Algorithms / EM Algorithms for Text Processing / Closing Remarks
Book Synopsis Instant Mapreduce Patterns - Hadoop Essentials How-To by : Srinath Perera
Download or read book Instant Mapreduce Patterns - Hadoop Essentials How-To written by Srinath Perera and published by Packt Publishing Ltd. This book was released on 2013-05-22 with total page 131 pages. Available in PDF, EPUB and Kindle. Book excerpt: Filled with practical, step-by-step instructions and clear explanations for the most important and useful tasks. This is a Packt Instant How-to guide, which provides concise and clear recipes for getting started with Hadoop.This book is for big data enthusiasts and would-be Hadoop programmers. It is also meant for Java programmers who either have not worked with Hadoop at all, or who know Hadoop and MapReduce but are not sure how to deepen their understanding.
Download or read book Hadoop Operations written by Eric Sammer and published by "O'Reilly Media, Inc.". This book was released on 2012-09-26 with total page 298 pages. Available in PDF, EPUB and Kindle. Book excerpt: If you’ve been asked to maintain large and complex Hadoop clusters, this book is a must. Demand for operations-specific material has skyrocketed now that Hadoop is becoming the de facto standard for truly large-scale data processing in the data center. Eric Sammer, Principal Solution Architect at Cloudera, shows you the particulars of running Hadoop in production, from planning, installing, and configuring the system to providing ongoing maintenance. Rather than run through all possible scenarios, this pragmatic operations guide calls out what works, as demonstrated in critical deployments. Get a high-level overview of HDFS and MapReduce: why they exist and how they work Plan a Hadoop deployment, from hardware and OS selection to network requirements Learn setup and configuration details with a list of critical properties Manage resources by sharing a cluster across multiple groups Get a runbook of the most common cluster maintenance tasks Monitor Hadoop clusters—and learn troubleshooting with the help of real-world war stories Use basic tools and techniques to handle backup and catastrophic failure
Book Synopsis Hadoop: The Definitive Guide by : Tom White
Download or read book Hadoop: The Definitive Guide written by Tom White and published by "O'Reilly Media, Inc.". This book was released on 2012-05-10 with total page 687 pages. Available in PDF, EPUB and Kindle. Book excerpt: Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN). Store large datasets with the Hadoop Distributed File System (HDFS) Run distributed computations with MapReduce Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud Load data from relational databases into HDFS, using Sqoop Perform large-scale data processing with the Pig query language Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems
