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Apache Spark Graph Processing

Build, process and analyze large-scale graph data effectively with Spark About This Book * Find solutions for every stage of data;

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Apache Spark 2.x for Java Developers

so you understand various graph-based analytics that can be performed with Spark In Detail Apache Spark is the buzzword in the big data;

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Spark GraphX in Action

difficult and computationally expensive to explore, query, and analyze. GraphX, a powerful graph processing API for the Apache Spark analytics;

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Mastering Apache Spark 2.x -

Apache Spark is an in-memory cluster-based parallel processing system that provides a wide range of functionalities such as graph processing;

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Spark in Action

data sets. But Spark goes much further than other frameworks. By including machine learning and graph processing capabilities, it makes;

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Apache Spark Quick Start Guide

architecture and the execution flow of a Spark application Explore built-in modules for SQL, streaming, ML, and graph analysis Optimize your Spark job;

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Apache Spark 2.x Cookbook

Over 70 recipes to help you use Apache Spark as your single big data computing platform and master its libraries About This Book;

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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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Learning Apache Spark 2

capabilities in the form of Spark SQL, Spark Streaming, Spark ML and Graph X all accessible via Java, Scala, Python and R. Deploying the key;

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Graph Algorithms Practical Examples in Apache Spark and Neo4j

and improving machine learning predictions. You'll walk through hands-on examples that show you how to use graph algorithms in Apache Spark;

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Apache Spark 2

to optimize your work by using many features of Spark 2.x and Scala Book DescriptionApache Spark is an in-memory, cluster-based data;

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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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PySpark Cookbook

solve graph-processing problems. Finally, you will explore how to deploy your applications to the cloud using the spark-submit command. By the;

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Mastering Spark with R The Complete Guide to LargeScale Analysis and Modeling

with ease from within Spark Learn about alternative modeling frameworks for graph processing, geospatial analysis, and genomics at scale Dive;

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Large-Scale Graph Processing Using Apache Giraph

This book takes its reader on a journey through Apache Giraph, a popular distributed graph processing platform designed to bring the power;

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Beginning Apache Spark 3

Take a journey toward discovering, learning, and using Apache Spark 3.0. In this book, you will gain expertise on the powerful and;

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Modern Data Engineering with Apache Spark

Leverage Apache Spark within a modern data engineering ecosystem. This hands-on guide will teach you how to write fully functional;

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Practical Apache Spark

Work with Apache Spark using Scala to deploy and set up single-node, multi-node, and high-availability clusters. This book discusses;

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Frank Kane's Taming Big Data with Apache Spark and Python

Frank Kane's hands-on Spark training course, based on his bestselling Taming Big Data with Apache Spark and Python video, now available;

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Learning PySpark

Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0 About This Book;

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Apache Spark for Data Science Cookbook

Over insightful 90 recipes to get lightning-fast analytics with Apache Spark About This Book * Use Apache Spark for data processing;

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Learning Spark SQL

Design, implement, and deliver successful streaming applications, machine learning pipelines and graph applications using Spark SQL API;

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Fast Data Processing with Spark 2 - Third Edition

statistical language, to work with Spark * Apply interesting graph algorithms and graph processing with GraphX In Detail When people want a way;

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Processing Big Data with Azure HDInsight

components are covered, including Hive, Pig, HBase, Storm, and Spark on Azure HDInsight, and code samples are written in .NET only. Processing Big;

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Beginning Apache Spark Using Azure Databricks

Analyze vast amounts of data in record time using Apache Spark with Databricks in the Cloud. Learn the fundamentals, and more, of running;

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Apache Spark Machine Learning Blueprints

Develop a range of cutting-edge machine learning projects with Apache Spark using this actionable guide About This Book * Customize;

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Big Data Analytics

Pipelines and SparkR and Graph Analytics are covered with GraphX and GraphFrames components of Spark. Readers will also get an opportunity to get;

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