Each recipe provides samples you can use right away. This revised edition covers the regular expression flavors used by C#, Java, JavaScript, Perl, PHP, Python, Ruby, and VB.NET. Spark 2 also adds improved programming APIs, better performance, and countless other upgrades. About the Book Spark in Action teaches you the theory and skills you need to effectively handle batch and streaming data using Spark. In this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. Found insideWith this book, you’ll explore: How Spark SQL’s new interfaces improve performance over SQL’s RDD data structure The choice between data joins in Core Spark and Spark SQL Techniques for getting the most out of standard RDD ... Found insideThis practical guide provides nearly 200 self-contained recipes to help you solve machine learning challenges you may encounter in your daily work. Develop large-scale distributed data processing applications using Spark 2 in Scala and PythonAbout This Book- This book offers an easy introduction to the Spark framework published on the latest version of Apache Spark 2- Perform efficient ... Found insideWith this hands-on guide, author and architect Tom Marrs shows you how to build enterprise-class applications and services by leveraging JSON tooling and message/document design. About the book Spark in Action, Second Edition, teaches you to create end-to-end analytics applications. Found insideIn a world driven by mass data creation and consumption, this book combines the latest scalable technologies with advanced analytical algorithms using real-world use-cases in order to derive actionable insights from Big Data in real-time. Found insideThe definitive guide for statisticians and data scientists who understand the advantages of becoming proficient in both R and Python The first book of its kind, Python for R Users: A Data Science Approach makes it easy for R programmers to ... This book covers relevant data science topics, cluster computing, and issues that should interest even the most advanced users. Found insideThe book also discusses Google Colab, which makes it possible to write Python code in the cloud. This book is perfect for you: * If you're coming to Python from another programming language * If you're learning Python as a first programming language * If you're looking to increase the readability, maintainability, and correctness of ... Found insideLearn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. Found insideThis edition includes new information on Spark SQL, Spark Streaming, setup, and Maven coordinates. Written by the developers of Spark, this book will have data scientists and engineers up and running in no time. Found inside – Page 1In just 24 lessons of one hour or less, Sams Teach Yourself Apache Spark in 24 Hours helps you build practical Big Data solutions that leverage Spark’s amazing speed, scalability, simplicity, and versatility. Presents an introduction to the new programming language for the Java Platform. Software keeps changing, but the fundamental principles remain the same. With this book, software engineers and architects will learn how to apply those ideas in practice, and how to make full use of data in modern applications. Packed with real-world scenarios, this book provides recipes for: Strings, numeric types, and control structures Classes, methods, objects, traits, and packaging Functional programming in a variety of situations Collections covering Scala's ... If you are a data analyst, developer, or simply someone who wants to use Hive to explore and analyze data in Hadoop, this is the book for you. Found inside – Page iThis book explains how the confluence of these pivotal technologies gives you enormous power, and cheaply, when it comes to huge datasets. Build data-intensive applications locally and deploy at scale using the combined powers of Python and Spark 2.0 About This Book Learn why and how you can efficiently use Python to process data and build machine learning models in Apache ... This book will help object-oriented programmers build on their existing skills, allowing them to immediately construct useful applications as they gradually master advanced programming techniques. Found inside – Page 1This guide is ideal if you want to learn about Hadoop 2 without getting mired in technical details. Found insideUnleash the data processing and analytics capability of Apache Spark with the language of choice: Java About This Book Perform big data processing with Spark—without having to learn Scala! Found inside – Page 1This book will focus on how to analyze large and complex sets of data. Starting with installing and configuring Apache Spark with various cluster managers, you will cover setting up development environments. Found insideAnyone who is using Spark (or is planning to) will benefit from this book. The book assumes you have a basic knowledge of Scala as a programming language. Found insideSummary Play for Scala shows you how to build Scala-based web applications using the Play 2 framework. This book starts by introducing Play through a comprehensive overview example. Found inside – Page 1In this book, you'll learn how ANTLR automatically builds a data structure representing the input (parse tree) and generates code that can walk the tree (visitor). Found inside – Page 142def summary(statistics: String*): DataFrame Computes specified statistics for ... (You can check on the HadoopExam.com whether cheat sheet is available, ... Found insideWhat you will learn Configure a local instance of PySpark in a virtual environment Install and configure Jupyter in local and multi-node environments Create DataFrames from JSON and a dictionary using pyspark.sql Explore regression and ... This book is an anthology of the results of research and development in database query processing during the past decade. The relational model of data provided tremendous impetus for research into query processing. Found insideIn this book, you’ll learn how many of the most fundamental data science tools and algorithms work by implementing them from scratch. If you are a Scala, Java, or Python developer with an interest in machine learning and data analysis and are eager to learn how to apply common machine learning techniques at scale using the Spark framework, this is the book for you. Found insideIn this book you'll find patterns for messaging, flow control, resource management, and concurrency, along with practical issues like test-friendly designs. All patterns include concrete examples using Scala and Akka. Found insideThis file contains new detailed instructions on how to use Spark shells, ... For details on the deployment modes, see the cheat sheet in Table 1-1 in ... ScalaCheck: The Definitive Guide explains the big ideas behind ScalaCheck, and shows how to use it effectively to write tests at the higher level of property specifications."-- tbd Unlock deeper insights into Machine Leaning with this vital guide to cutting-edge predictive analytics About This Book Leverage Python's most powerful open-source libraries for deep learning, data wrangling, and data visualization Learn ... Found insideAbout this Book Scala in Action is a comprehensive tutorial that introduces the language through clear explanations and numerous hands-on examples. Found inside – Page iThis friendly guide charts a path through the fundamentals of data science and then delves into the actual work: linear regression, logical regression, machine learning, neural networks, recommender engines, and cross-validation of models. About the book Spark in Action, Second Edition, teaches you to create end-to-end analytics applications. This book helps you use SQL and Excel to extract business information from relational databases and use that data to define business dimensions, store transactions about customers, produce results, and more. You’ll learn the latest versions of pandas, NumPy, IPython, and Jupyter in the process. Written by Wes McKinney, the creator of the Python pandas project, this book is a practical, modern introduction to data science tools in Python. Found insideAbout This Book Understand how Spark can be distributed across computing clusters Develop and run Spark jobs efficiently using Python A hands-on tutorial by Frank Kane with over 15 real-world examples teaching you Big Data processing with ... Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. 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