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Paperback. Get a jump start on using Azure HDInsight and Hadoop Ecosystem components. As most Hadoop and Big Data projects are written in either Java, Scala, or Python, this book minimizes the effort to learn another language and is written from the perspective of a .NET developer. Hadoop components are covered, including Hive, Pig, HBase, Storm, and Spark on Azure HDInsight, and code samples are written in .NET only.Processing Big Data with Azure HDInsight covers the fundamentals of big data, how businesses are using it to their advantage, and how Azure HDInsight fits into the big data world. This book introduces Hadoop and big data concepts and then dives into creating different solutions with HDInsight and the Hadoop Ecosystem. It covers concepts with real-world scenarios and code examples, making sure you get hands-on experience. The best way to utilize this book is to practice while reading. After reading this book you will be familiar with Azure HDInsight and how it can be utilized to build big data solutions, including batch processing, stream analytics, interactive processing, and storing and retrieving data in an efficient manner.What You'll LearnUnderstand the fundamentals of HDInsight and HadoopWork with HDInsight clusterQuery with Apache Hive and Apache PigStore and retrieve data with Apache HBaseStream data processing using Apache StormWork with Apache SparkWho This Book Is ForSoftware developers, technical architects, data scientists/analyts, and Hadoop administrators who want to develop on Microsofts managed Hadoop offering, HDInsight Get a jump start on using Azure HDInsight and Hadoop Ecosystem components. As most Hadoop and Big Data projects are written in Java, Scala or Python, this book minimizes the effort to learn another language and is written from the perspective of a .NET developer. Hadoop components are covered, and code samples are written in .NET only. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. N° de réf. du vendeur 9781484228685
Get a jump start on using Azure HDInsight and Hadoop Ecosystem components. As most Hadoop and Big Data projects are written in either Java, Scala, or Python, this book minimizes the effort to learn another language and is written from the perspective of a .NET developer. Hadoop components are covered, including Hive, Pig, HBase, Storm, and Spark on Azure HDInsight, and code samples are written in .NET only.
Processing Big Data with Azure HDInsight covers the fundamentals of big data, how businesses are using it to their advantage, and how Azure HDInsight fits into the big data world. This book introduces Hadoop and big data concepts and then dives into creating different solutions with HDInsight and the Hadoop Ecosystem. It covers concepts with real-world scenarios and code examples, making sure you get hands-on experience. The best way to utilize this book is to practice while reading. After reading this book you will be familiar with Azure HDInsight and how it can be utilized to build big data solutions, including batch processing, stream analytics, interactive processing, and storing and retrieving data in an efficient manner. What You'll Learn
À propos de l?auteur:
Vinit Yadav is Founder and CEO of Veloxcore. He started working with Azure when it first came out in 2010, and since then he has been continuously involved in designing solutions around the Microsoft Azure platform. At Veloxcore, he continues to build and deliver highly scalable big data solutions. He is also a machine learning and data science enthusiastic, passionate programmer, and has over 12 years of experience in designing and developing enterprise applications using various .NET technologies.
Titre : Processing Big Data with Azure HDInsight (...
Éditeur : APress, Berkley
Date d'édition : 2017
Reliure : Paperback
Etat : new
Edition : Edition originale
Vendeur : Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irlande
Etat : New. 2017. 1st ed. paperback. . . . . . N° de réf. du vendeur V9781484228685
Quantité disponible : 15 disponible(s)