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Data-Intensive Text Processing With MapReduce

details, ranging from scheduling to synchronization to fault tolerance. This book focuses on MapReduce algorithm design, with an emphasis on text;

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Cloud Computing

As more and more data is generated at a faster-than-ever rate, processing large volumes of data is becoming a challenge for data analysis;

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Cloud Computing

As more and more data is generated at a faster-than-ever rate, processing large volumes of data is becoming a challenge for data analysis;

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Big Data with Hadoop MapReduce

The authors provide an understanding of big data and MapReduce by clearly presenting the basic terminologies and concepts. They have;

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Big Data with Hadoop MapReduce

The authors provide an understanding of big data and MapReduce by clearly presenting the basic terminologies and concepts. They have;

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Hadoop in Action

process large amounts of data offline. The book begins with several simple examples that illustrate the basic idea behind Hadoop;

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Distributed Processing of Large Remote Sensing Images Using Mapreduce

Advances in remote sensing technology and their ever increasing repositories of the collected data are revolutionizing the mechanisms these;

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Big Data

value for better business decision making Shows how and why data connectors are critical and necessary for Agile text analytics;

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Big Data

extract value for better business decision making Shows how and why data connectors are critical and necessary for Agile text;

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Programming Pig

projects on Hadoop. With Pig, you can analyze data without having to create a full-fledged application - making it easy for you to experiment with;

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Data Algorithms

solution with code that you can use in your projects. Dr. Mahmoud Parsian covers basic design patterns, optimization techniques, and data mining;

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Hadoop: The Definitive Guide

), then run distributed computations with MapReduce * Use Hadoop's data and I/O building blocks for compression, data integrity, serialization;

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Large scale data processing in Hadoop MapReduce scenario

network, Google initiated MapReduce model. This model is an implementation of Parallel Computing, which aims at processing large amount of data;

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Hbase in Action

When dealing with big data, traditional databases don't cut it. It's best to use the right tool for the job. HBase is a NoSQL storage;

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Learning Big Data with Amazon Elastic MapReduce

This book is aimed at developers and system administrators who want to learn about Big Data analysis using Amazon Elastic MapReduce. Basic;

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Programming MapReduce With Scalding

the Scalding framework. It is packed with examples featuring log-processing, ad-targeting, and machine learning. This book is for developers;

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Practical Concurrent Haskell

application development and portability with applications in cloud computing and big data. You'll use MapReduce and other, similar big data tools as;

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Hadoop 2 Essentials

, virtual 4-node Linux YARN cluster on a Windows laptop. Rather than filled with disjointed, piecemeal code snippets to show Hadoop MapReduce;

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Algorithmic Aspects of Parallel Data Processing

The last decade has seen a huge and growing interest in processing large data sets on large distributed clusters. This trend began with the;

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Programming Elastic MapReduce

Although you don't need a large computing infrastructure to process massive amounts of data with Apache Hadoop, it can still be difficult;

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An Architecture for Fast and General Data Processing on Large Clusters

, produce large and valuable data streams. However, the processing capabilities of single machines have not kept up with the size of data. As a;

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An Architecture for Fast and General Data Processing on Large Clusters

, produce large and valuable data streams. However, the processing capabilities of single machines have not kept up with the size of data. As a;

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Hadoop: The Definitive Guide

familiar with Hadoop's data and I/O building blocks for compression, data integrity, serialization, and persistence * Discover common pitfalls and;

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Hadoop The Definitive Guide

Ready to unlock the power of your data? With the fourth edition of this comprehensive guide, you'll learn how to build and maintain;

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Hadoop Application Architectures

Get expert guidance on architecting end-to-end data management solutions with Apache Hadoop. While many sources explain how to use various;

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Apache Hadoop 3 Quick Start Guide

Hadoop to get useful insights from large data sets Work with the different components of Hadoop such as MapReduce, HDFS and YARN Learn about the;

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Distributed Computing with Python

write data processing programs in Python that are highly available, reliable, and fault tolerant * Make use of Amazon Web Services along with;

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Einde inhoud

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