Apache Spark Graph Processing
| Author | : | |
| Rating | : | 4.66 (964 Votes) |
| Asin | : | 1784391808 |
| Format Type | : | paperback |
| Number of Pages | : | 148 Pages |
| Publish Date | : | 2017-07-12 |
| Language | : | English |
DESCRIPTION:
MSastry said This book is easy to read with a promise to provide step by. This book is easy to read with a promise to provide step by step procedures to learn Apache Spark Graph Processing. To the most extent, Mr. Rindra Ramamonjison fulfills the promise. There are several errors in the book as such reader gets confused and can not be followed through the text. For example, spark-1.This book is easy to read with a promise to provide step by MSastry This book is easy to read with a promise to provide step by step procedures to learn Apache Spark Graph Processing. To the most extent, Mr. Rindra Ramamonjison fulfills the promise. There are several errors in the book as such reader gets confused and can not be followed through the text. For example, spark-1.4.1-bin-hadoop2.6.tgz does not have the directories: core, graphx, mllib, sql, and streaming in SPARKHO. .1-bin-hadoop"This book is easy to read with a promise to provide step by" according to MSastry. This book is easy to read with a promise to provide step by step procedures to learn Apache Spark Graph Processing. To the most extent, Mr. Rindra Ramamonjison fulfills the promise. There are several errors in the book as such reader gets confused and can not be followed through the text. For example, spark-1.This book is easy to read with a promise to provide step by MSastry This book is easy to read with a promise to provide step by step procedures to learn Apache Spark Graph Processing. To the most extent, Mr. Rindra Ramamonjison fulfills the promise. There are several errors in the book as such reader gets confused and can not be followed through the text. For example, spark-1.4.1-bin-hadoop2.6.tgz does not have the directories: core, graphx, mllib, sql, and streaming in SPARKHO. .1-bin-hadoop2.6.tgz does not have the directories: core, graphx, mllib, sql, and streaming in SPARKHO. .6.tgz does not have the directories: core, graphx, mllib, sql, and streaming in SPARKHO
The later chapters of this book cover more advanced topics such as clustering graphs, implementing graph-parallel iterative algorithms and learning methods from graph data.Style and approachA step-by-step guide that will walk you through the key ideas and techniques for processing big graph data at scale, with practical examples that will ensure an overall understanding of the concepts of Spark.. In addition, you will learn powerful operations that can be used to transform graph elements and graph structures. Furthermore, this book also teaches how to create custom graph operations that are tailored for specific needs with efficiency in mind. Build, process and analyze large-scale graph data effectively with SparkAbout This BookFind solutions for every stage of data processing from loading and transforming graph data toImprove the scalability of your graphs with a variety of real-world applications with complete Scala code.A concise guide to processing large-scale networks with Apache Spark.Who This Book Is ForThis book is for data scientists and big data developers who want to learn the processing and analyzing graph datasets at scale. Basic knowledge of Spark is
He has played various roles in many engineering companies, within telecom and finance industries. His primary research interests are machine learning, optimization, graph processing, and statistical signal processing. He received his master's degree from Tokyo Institute of Technology. Rindra RamamonjisonRindra Ramamonjison is a fourth year PhD student of electri
He has played various roles in many engineering companies, within telecom and finance industries. He received his master's degree from Tokyo Institute of Technology. Rindra is also the co-organizer of the Vancouver Spark Meetup.. About the AuthorRindra RamamonjisonRindra Ramamonjison is a fourth year PhD student of electrical engineering at the University of British Columbia, Vancouver. His primary research interests are machine learning, optimization, graph processing, and statistical signal processing