LEADER 03772nam 2200433 450 001 9910795318503321 005 20200520144314.0 035 $a(CKB)4970000000061401 035 $a(MiAaPQ)EBC5675596 035 $a(CaSebORM)9781789349108 035 $a(Au-PeEL)EBL5675596 035 $a(OCoLC)1086054843 035 $a(EXLCZ)994970000000061401 100 $a20190220d2019 uy| 0 101 0 $aeng 135 $aurcn| ||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aApache Spark Quick Start guide $equickly learn the art of writing efficient big data applications with Apache Spark /$fShrey Mehrotra, Akash Grade 205 $a1st edition 210 1$aBirmingham :$cPackt,$d2019. 215 $a1 online resource (154 pages) 300 $aIncludes index. 311 $a1-78934-910-9 330 $aA practical guide for solving complex data processing challenges by applying the best optimizations techniques in Apache Spark. Key Features Learn about the core concepts and the latest developments in Apache Spark Master writing efficient big data applications with Spark's built-in modules for SQL, Streaming, Machine Learning and Graph analysis Get introduced to a variety of optimizations based on the actual experience Book Description Apache Spark is a flexible framework that allows processing of batch and real-time data. Its unified engine has made it quite popular for big data use cases. This book will help you to get started with Apache Spark 2.0 and write big data applications for a variety of use cases. It will also introduce you to Apache Spark ? one of the most popular Big Data processing frameworks. Although this book is intended to help you get started with Apache Spark, but it also focuses on explaining the core concepts. This practical guide provides a quick start to the Spark 2.0 architecture and its components. It teaches you how to set up Spark on your local machine. As we move ahead, you will be introduced to resilient distributed datasets (RDDs) and DataFrame APIs, and their corresponding transformations and actions. Then, we move on to the life cycle of a Spark application and learn about the techniques used to debug slow-running applications. You will also go through Spark's built-in modules for SQL, streaming, machine learning, and graph analysis. Finally, the book will lay out the best practices and optimization techniques that are key for writing efficient Spark applications. By the end of this book, you will have a sound fundamental understanding of the Apache Spark framework and you will be able to write and optimize Spark applications. What you will learn Learn core concepts such as RDDs, DataFrames, transformations, and more Set up a Spark development environment Choose the right APIs for your applications Understand Spark's architecture and the execution flow of a Spark application Explore built-in modules for SQL, streaming, ML, and graph analysis Optimize your Spark job for better performance Who this book is for If you are a big data enthusiast and love processing huge amount of data, this book is for you. If you are data engineer and looking for the best optimization techniques for your Spark applications, then you will find this book helpful. This book also helps data scientists who want to implement their mach... 606 $aBig data 606 $aData mining$xComputer programs 615 0$aBig data. 615 0$aData mining$xComputer programs. 700 $aMehrotra$b Shrey$01524290 702 $aGrade$b Akash 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910795318503321 996 $aApache Spark Quick Start guide$93765062 997 $aUNINA