Apache Spark Quick Start by Mehrotra Shrey (25 results)

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Condition: good. May show signs of wear, highlighting, writing, and previous use. This item may be a former library book with typical markings. No guarantee on products that contain supplements Your satisfaction is 100% guaranteed. Twenty-five year bookseller with shipments to over fifty million happy customers.

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paperback. Condition: Good. Ships in a BOX from Central Missouri! May not include working access code. Will not include dust jacket. Has used sticker(s) and some writing or highlighting. UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Paperback. Condition: new. Paperback. A practical guide for solving complex data processing challenges by applying the best optimizations techniques in Apache Spark.Key FeaturesLearn about the core concepts and the latest developments in Apache SparkMaster writing efficient big data applications with Sparks built-in modules for SQL, Streaming, Machine Learning and Graph analysisGet introduced to a variety of optimizations based on the actual experienceBook DescriptionApache 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 Sparks 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 learnLearn core concepts such as RDDs, DataFrames, transformations, and moreSet up a Spark development environmentChoose the right APIs for your applicationsUnderstand Sparks architecture and the execution flow of a Spark applicationExplore built-in modules for SQL, streaming, ML, and graph analysisOptimize your Spark job for better performanceWho this book is forIf 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 machine learning algorithms in Spark. You need to have a basic understanding of any one of the programming languages such as Scala, Python or Java. Apache Spark is a exible in-memory framework that allows processing of both batch and real-time data. Its unified engine has made it quite popular for big data use cases. This book will help you to quickly get started with Apache Spark 2.0 and write efficient big data applications for a variety of use cases. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

paperback. Condition: New. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Paperback. Condition: new. Paperback. A practical guide for solving complex data processing challenges by applying the best optimizations techniques in Apache Spark.Key FeaturesLearn about the core concepts and the latest developments in Apache SparkMaster writing efficient big data applications with Sparks built-in modules for SQL, Streaming, Machine Learning and Graph analysisGet introduced to a variety of optimizations based on the actual experienceBook DescriptionApache 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 Sparks 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 learnLearn core concepts such as RDDs, DataFrames, transformations, and moreSet up a Spark development environmentChoose the right APIs for your applicationsUnderstand Sparks architecture and the execution flow of a Spark applicationExplore built-in modules for SQL, streaming, ML, and graph analysisOptimize your Spark job for better performanceWho this book is forIf 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 machine learning algorithms in Spark. You need to have a basic understanding of any one of the programming languages such as Scala, Python or Java. Apache Spark is a exible in-memory framework that allows processing of both batch and real-time data. Its unified engine has made it quite popular for big data use cases. This book will help you to quickly get started with Apache Spark 2.0 and write efficient big data applications for a variety of use cases. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.

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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Apache Spark is a flexible in-memory framework that allows processing of both batch and real-time data. Its unified engine has made it quite popular for big data use cases. This book will help you to quickly get started with Apache Spark 2.0 and write effic.