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Apache Spark in 24 Hours, Sams Teach Yourself

Apache Spark in 24 Hours, Sams Teach Yourself
Author: Jeffrey Aven
Publisher: Sams Publishing
Total Pages: 1352
Release: 2016-08-31
Genre: Computers
ISBN: 0134445821

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Apache Spark is a fast, scalable, and flexible open source distributed processing engine for big data systems and is one of the most active open source big data projects to date. In 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. This book’s straightforward, step-by-step approach shows you how to deploy, program, optimize, manage, integrate, and extend Spark–now, and for years to come. You’ll discover how to create powerful solutions encompassing cloud computing, real-time stream processing, machine learning, and more. Every lesson builds on what you’ve already learned, giving you a rock-solid foundation for real-world success. Whether you are a data analyst, data engineer, data scientist, or data steward, learning Spark will help you to advance your career or embark on a new career in the booming area of Big Data. Learn how to • Discover what Apache Spark does and how it fits into the Big Data landscape • Deploy and run Spark locally or in the cloud • Interact with Spark from the shell • Make the most of the Spark Cluster Architecture • Develop Spark applications with Scala and functional Python • Program with the Spark API, including transformations and actions • Apply practical data engineering/analysis approaches designed for Spark • Use Resilient Distributed Datasets (RDDs) for caching, persistence, and output • Optimize Spark solution performance • Use Spark with SQL (via Spark SQL) and with NoSQL (via Cassandra) • Leverage cutting-edge functional programming techniques • Extend Spark with streaming, R, and Sparkling Water • Start building Spark-based machine learning and graph-processing applications • Explore advanced messaging technologies, including Kafka • Preview and prepare for Spark’s next generation of innovations Instructions walk you through common questions, issues, and tasks; Q-and-As, Quizzes, and Exercises build and test your knowledge; "Did You Know?" tips offer insider advice and shortcuts; and "Watch Out!" alerts help you avoid pitfalls. By the time you're finished, you'll be comfortable using Apache Spark to solve a wide spectrum of Big Data problems.


Apache Spark in 24 Hours

Apache Spark in 24 Hours
Author: Andrea Avena
Publisher:
Total Pages: 573
Release: 2017
Genre:
ISBN: 9780672338519

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Sams Teach Yourself Hadoop in 24 Hours

Sams Teach Yourself Hadoop in 24 Hours
Author: Jeffrey Aven
Publisher: Sams Publishing
Total Pages: 0
Release: 2017
Genre: Apache Hadoop
ISBN: 9780672338526

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Apache Hadoop is the technology at the heart of the Big Data revolution, and Hadoop skills are in enormous demand. Now, in just 24 lessons of one hour or less, students can learn all the skills and techniques they'll need to deploy each key component of a Hadoop platform in a local environment or in the cloud, building a fully functional Hadoop cluster and using it with real programs and datasets. Each short, easy lesson builds on all that's come before, helping students master all of Hadoop's essentials, and extend it to meet real-world challenges. Apache Hadoop in 24 Hours, Sams Teach Yourself covers all this, and much more: Understanding Hadoop and the Hadoop Distributed File System (HDFS) Importing data into Hadoop, and process it there Mastering basic MapReduce Java programming, and using advanced MapReduce API concepts Making the most of Apache Pig and Apache Hive Implementing and administering YARN Taking advantage of the full Hadoop ecosystem Managing Hadoop clusters with Apache Ambari Working with the Hadoop User Environment (HUE) Scaling, securing, and troubleshooting Hadoop environments Integrating Hadoop into the enterprise Deploying Hadoop in the cloud Getting started with Apache Spark Step-by-step instructions walk students through common questions, issues, and tasks; Q-and-As, Quizzes, and Exercises build and test your knowledge; Did You Know? tips offer insider advice and shortcuts; and Watch Out! alerts help avoid pitfalls. By the time they're finished, they'll be comfortable using Apache Hadoop to solve a wide spectrum of Big Data problems.


Hadoop in 24 Hours, Sams Teach Yourself

Hadoop in 24 Hours, Sams Teach Yourself
Author: Jeffrey Aven
Publisher: Sams Publishing
Total Pages: 496
Release: 2017-04-07
Genre: Computers
ISBN: 0134456726

Download Hadoop in 24 Hours, Sams Teach Yourself Book in PDF, ePub and Kindle

Apache Hadoop is the technology at the heart of the Big Data revolution, and Hadoop skills are in enormous demand. Now, in just 24 lessons of one hour or less, you can learn all the skills and techniques you'll need to deploy each key component of a Hadoop platform in your local environment or in the cloud, building a fully functional Hadoop cluster and using it with real programs and datasets. Each short, easy lesson builds on all that's come before, helping you master all of Hadoop's essentials, and extend it to meet your unique challenges. Apache Hadoop in 24 Hours, Sams Teach Yourself covers all this, and much more: Understanding Hadoop and the Hadoop Distributed File System (HDFS) Importing data into Hadoop, and process it there Mastering basic MapReduce Java programming, and using advanced MapReduce API concepts Making the most of Apache Pig and Apache Hive Implementing and administering YARN Taking advantage of the full Hadoop ecosystem Managing Hadoop clusters with Apache Ambari Working with the Hadoop User Environment (HUE) Scaling, securing, and troubleshooting Hadoop environments Integrating Hadoop into the enterprise Deploying Hadoop in the cloud Getting started with Apache Spark Step-by-step instructions walk you through common questions, issues, and tasks; Q-and-As, Quizzes, and Exercises build and test your knowledge; "Did You Know?" tips offer insider advice and shortcuts; and "Watch Out!" alerts help you avoid pitfalls. By the time you're finished, you'll be comfortable using Apache Hadoop to solve a wide spectrum of Big Data problems.


Sams Teach Yourself Apache 2 in 24 Hours

Sams Teach Yourself Apache 2 in 24 Hours
Author: Daniel López Ridruejo
Publisher: Sams Publishing
Total Pages: 498
Release: 2002
Genre: Computers
ISBN: 9780672323553

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Sams Teach Yourself Apache in 24 Hours covers the installation, configuration, and ongoing administration of the Apache Web server, the most popular Internet Web server. It covers both the 1.3 and the new 2.0 versions of Apache. Using a hands-on, task-oriented format, it concentrates on the most popular features and common quirks of the server. The first part of the book helps the reader build, configure, and get started with Apache. After completing these chapters the reader will be able to start, stop, and monitor the Web server. He also will be able to serve both static content and dynamic content, customize the logs, and restrict access to certain parts of the Web server. The second part of the book explains in detail the architecture of Apache and how to extend the server via third-party modules like PHP and Tomcat. It covers server performance and scalability, content management, and how to set up a secure server with SSL.


Learning Spark

Learning Spark
Author: Jules S. Damji
Publisher: O'Reilly Media
Total Pages: 400
Release: 2020-07-16
Genre: Computers
ISBN: 1492050016

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Data is bigger, arrives faster, and comes in a variety of formats—and it all needs to be processed at scale for analytics or machine learning. But how can you process such varied workloads efficiently? Enter Apache Spark. Updated to include Spark 3.0, this second edition shows data engineers and data scientists why structure and unification in Spark matters. Specifically, this book explains how to perform simple and complex data analytics and employ machine learning algorithms. Through step-by-step walk-throughs, code snippets, and notebooks, you’ll be able to: Learn Python, SQL, Scala, or Java high-level Structured APIs Understand Spark operations and SQL Engine Inspect, tune, and debug Spark operations with Spark configurations and Spark UI Connect to data sources: JSON, Parquet, CSV, Avro, ORC, Hive, S3, or Kafka Perform analytics on batch and streaming data using Structured Streaming Build reliable data pipelines with open source Delta Lake and Spark Develop machine learning pipelines with MLlib and productionize models using MLflow


Sams Teach Yourself Java in 24 Hours

Sams Teach Yourself Java in 24 Hours
Author: Rogers Cadenhead
Publisher: Sams Publishing
Total Pages: 432
Release: 2012
Genre: Computers
ISBN: 0672335751

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Offers an updated tutorial for beginners explaining how to use Java to create desktop and Web programs, applications, and web services.


Sams Teach Yourself PHP in 24 Hours

Sams Teach Yourself PHP in 24 Hours
Author: Matt Zandstra
Publisher: Sams Publishing
Total Pages: 578
Release: 2004
Genre: Computers
ISBN: 9780672326196

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Think of all the things you could do in 24 hours. Go sightseeing. Read a book. Learn PHP. Sams Teach Yourself PHP in 24 Hours is a unique learning tool that is divided into 24 one-hour lessons over five sections. Starting with the basics, you will discover the fundamentals of PHP and how to apply that knowledge to create dynamic websites with forms, cookies and authentication functions. You will also find out how to access databases, as well as how to integrate system components, e-mail, LDAP, network sockets and more. A support website includes access to source code, PHP updates, errata and links to other relevant websites. Sams Teach Yourself PHP in 24 Hours is a quick and easy way to learn how to create interactive websites for your end user.


Spark: The Definitive Guide

Spark: The Definitive Guide
Author: Bill Chambers
Publisher: "O'Reilly Media, Inc."
Total Pages: 712
Release: 2018-02-08
Genre: Computers
ISBN: 1491912294

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Learn how to use, deploy, and maintain Apache Spark with this comprehensive guide, written by the creators of the open-source cluster-computing framework. With an emphasis on improvements and new features in Spark 2.0, authors Bill Chambers and Matei Zaharia break down Spark topics into distinct sections, each with unique goals. Youâ??ll explore the basic operations and common functions of Sparkâ??s structured APIs, as well as Structured Streaming, a new high-level API for building end-to-end streaming applications. Developers and system administrators will learn the fundamentals of monitoring, tuning, and debugging Spark, and explore machine learning techniques and scenarios for employing MLlib, Sparkâ??s scalable machine-learning library. Get a gentle overview of big data and Spark Learn about DataFrames, SQL, and Datasetsâ??Sparkâ??s core APIsâ??through worked examples Dive into Sparkâ??s low-level APIs, RDDs, and execution of SQL and DataFrames Understand how Spark runs on a cluster Debug, monitor, and tune Spark clusters and applications Learn the power of Structured Streaming, Sparkâ??s stream-processing engine Learn how you can apply MLlib to a variety of problems, including classification or recommendation


High Performance Spark

High Performance Spark
Author: Holden Karau
Publisher: "O'Reilly Media, Inc."
Total Pages: 356
Release: 2017-05-25
Genre: Computers
ISBN: 1491943173

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Apache Spark is amazing when everything clicks. But if you haven’t seen the performance improvements you expected, or still don’t feel confident enough to use Spark in production, this practical book is for you. Authors Holden Karau and Rachel Warren demonstrate performance optimizations to help your Spark queries run faster and handle larger data sizes, while using fewer resources. Ideal for software engineers, data engineers, developers, and system administrators working with large-scale data applications, this book describes techniques that can reduce data infrastructure costs and developer hours. Not only will you gain a more comprehensive understanding of Spark, you’ll also learn how to make it sing. With 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 transformations How to work around performance issues in Spark’s key/value pair paradigm Writing high-performance Spark code without Scala or the JVM How to test for functionality and performance when applying suggested improvements Using Spark MLlib and Spark ML machine learning libraries Spark’s Streaming components and external community packages