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Practical Data Science with Hadoop and Spark

professionals who can solve real data science problems with Hadoop and Spark. Practical Data Science with Hadoop (R) and Spark is your complete guide to;

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Big Data Analytics

batch and real-time data analytics using Spark Core, Spark SQL, and Conventional and Structured Streaming * Get to grips with data science and;

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Big Data Analytics with Hadoop 3

effective big data analytics solutions on-premise and on cloud Integrate Hadoop with other big data tools such as R, Python, Apache Spark, and;

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Hadoop Application Architectures

system Data processing frameworks, including MapReduce, Spark, and Hive Common Hadoop processing patterns, such as removing duplicate records and;

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Hadoop in Practice

is constantly growing, and it's important they keep up with the new technologies and practices to stay productive and future-proof data systems;

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Beginning Apache Spark 2

Develop applications for the big data landscape with Spark and Hadoop. This book also explains the role of Spark in developing scalable;

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Processing Big Data with Azure HDInsight

Store and retrieve data with Apache HBase Stream data processing using Apache Storm Work with Apache Spark Who This Book Is For Software;

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Spark in Action, Second Edition

distributed datasets with Spark SQL For beginning to intermediate developers and data engineers comfortable programming in Java. No;

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Apache Hadoop 3 Quick Start Guide

streaming using Apache Storm, and data analytics using Apache Spark. By the end of the book, you will be well versed with different configurations;

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Big Data Analytics with R

meaningful results * Get a practical knowledge of R programming language while working on Big Data platforms like Hadoop, Spark, H2O and SQL/NoSQL;

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Hadoop For Dummies

companies and organizations of all sizes are struggling to find ways to retrieve valuable information from their massive data sets with becoming;

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OpenStack Sahara Essentials

data scientists, cloud developers and Devops Engineers who would like to become proficient with OpenStack Sahara. Ideally, this book is well;

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Practical Machine Learning

of other big data platforms including Spark, Hadoop, and Mahout. Practical Machine Learning is an essential resource for the modern data scientists;

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Hadoop Real-World Solutions Cookbook

Book Is For Readers who have a basic knowledge of big data systems and want to advance their knowledge with hands-on recipes. What You;

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Learning Apache Spark 2

* Exclusive guide that covers how to get up and running with fast data processing using Apache Spark * Explore and exploit various possibilities with;

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Hadoop

with libraries such as Mahout and Batch and Stream data processing using Apache Spark * Understand the changes involved in the process in the;

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Mastering Hadoop 3

capabilities of Hadoop 3 Crunch and process data using MapReduce, YARN, and a host of tools within the Hadoop ecosystem Sharpen your Hadoop skills with;

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Learning YARN

phases. This book will also help big data engineers explore YARN integration with real-time analytics technologies such as Spark and Storm;

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Big-Data Analytics for Cloud, IoT and Cognitive Computing

analytics and Hadoop and Spark programming. Part 1 focuses on data science, the roles of clouds and IoT devices and frameworks for big-data;

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Practical Big Data Analytics

theoretical world of technology with the practical ground reality of building corporate Big Data and data science platforms. You will get hands-on;

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Apache Oozie Essentials

in HDFS * Create and process data pipelines with Pig, hive scripts as per business requirements. * Run machine learning Spark jobs on Hadoop;

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Hadoop Blueprints

churn detection system using Java and MapReduce * Build an IoT-based data collection and visualization system * Get to grips with building a;

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Guide to High Performance Distributed Computing

basics of Spark, including resilient distributed datasets, and examines Hadoop streaming and working with Scalding; Provides detailed case;

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Mastering Spark for Data Science

familiarity with the Spark architecture and working with Data Science applications. Mastering Spark for Data Science is a practical tutorial that uses;

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Hands-On Data Science with R

the end, you will also learn how to integrate R with Spark and Hadoop and perform large-scale data analytics without much complexity. What you;

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Data Algorithms

algorithms and tools you need to build distributed MapReduce applications with Apache Hadoop or Apache Spark. Each chapter provides a recipe for;

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Practical Hadoop Security

. The book concludes with the most important aspect of Hadoop security - encryption. Both types of encryptions, for data in transit and data at;

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