Beginning Apache Pig

Beginning Apache Pig
Author: Balaswamy Vaddeman
Publisher: Apress
Total Pages: 285
Release: 2016-12-10
Genre: Computers
ISBN: 1484223373

Learn to use Apache Pig to develop lightweight big data applications easily and quickly. This book shows you many optimization techniques and covers every context where Pig is used in big data analytics. Beginning Apache Pig shows you how Pig is easy to learn and requires relatively little time to develop big data applications.The book is divided into four parts: the complete features of Apache Pig; integration with other tools; how to solve complex business problems; and optimization of tools.You'll discover topics such as MapReduce and why it cannot meet every business need; the features of Pig Latin such as data types for each load, store, joins, groups, and ordering; how Pig workflows can be created; submitting Pig jobs using Hue; and working with Oozie. You'll also see how to extend the framework by writing UDFs and custom load, store, and filter functions. Finally you'll cover different optimization techniques such as gathering statistics about a Pig script, joining strategies, parallelism, and the role of data formats in good performance. What You Will Learn• Use all the features of Apache Pig• Integrate Apache Pig with other tools• Extend Apache Pig• Optimize Pig Latin code• Solve different use cases for Pig LatinWho This Book Is ForAll levels of IT professionals: architects, big data enthusiasts, engineers, developers, and big data administrators

Programming Pig

Programming Pig
Author: Alan Gates
Publisher: "O'Reilly Media, Inc."
Total Pages: 223
Release: 2011-10-06
Genre: Computers
ISBN: 1449302645

This guide is an ideal learning tool and reference for Apache Pig, the programming language that helps programmers describe and run large data projects on Hadoop. With Pig, they can analyze data without having to create a full-fledged application--making it easy for them to experiment with new data sets.

Programming Pig

Programming Pig
Author: Alan Gates
Publisher: "O'Reilly Media, Inc."
Total Pages: 387
Release: 2016-11-09
Genre: Computers
ISBN: 1491937041

For many organizations, Hadoop is the first step for dealing with massive amounts of data. The next step? Processing and analyzing datasets with the Apache Pig scripting platform. With Pig, you can batch-process data without having to create a full-fledged application, making it easy to experiment with new datasets. Updated with use cases and programming examples, this second edition is the ideal learning tool for new and experienced users alike. You’ll find comprehensive coverage on key features such as the Pig Latin scripting language and the Grunt shell. When you need to analyze terabytes of data, this book shows you how to do it efficiently with Pig. Delve into Pig’s data model, including scalar and complex data types Write Pig Latin scripts to sort, group, join, project, and filter your data Use Grunt to work with the Hadoop Distributed File System (HDFS) Build complex data processing pipelines with Pig’s macros and modularity features Embed Pig Latin in Python for iterative processing and other advanced tasks Use Pig with Apache Tez to build high-performance batch and interactive data processing applications Create your own load and store functions to handle data formats and storage mechanisms

Beginning Apache Hadoop Administration

Beginning Apache Hadoop Administration
Author: Prashant Nair
Publisher: Notion Press
Total Pages: 146
Release: 2017-09-07
Genre: Computers
ISBN: 1947752073

Bigdata is one of the most demanding markets in the IT sector. If you are an administrator or a have a passion for knowing the internal configurations of Hadoop, then this book is for you. This book enables a professional to learn about Hadoop in terms of installation, configuration, and management. This book will help the reader to jumpstart with Hadoop frameworks, its eco-system components and slowly progress towards learning the administration part of Hadoop. The level of this book goes from beginner to intermediate with 70% hands-on exercises. Some of the techniques that you will learn include, • Installation and configuration of Hadoop cluster • Performing Hadoop Cluster Upgrade • Understanding and implementing HDFS Federation • Understanding and Implementing High Availability • Implementing HA on a Federated Cluster • Zookeeper CLI • Apache Hive Installation and Security • HBase Multi-master setup • Oozie installation, configuration and job submission • Setting up HDFS Quotas • Setting up HDFS NFS gateway • Understanding and implementing rolling upgrade and much more.

Beginning Apache Cassandra Development

Beginning Apache Cassandra Development
Author: Vivek Mishra
Publisher: Apress
Total Pages: 235
Release: 2014-12-12
Genre: Computers
ISBN: 1484201426

Beginning Apache Cassandra Development introduces you to one of the most robust and best-performing NoSQL database platforms on the planet. Apache Cassandra is a document database following the JSON document model. It is specifically designed to manage large amounts of data across many commodity servers without there being any single point of failure. This design approach makes Apache Cassandra a robust and easy-to-implement platform when high availability is needed. Apache Cassandra can be used by developers in Java, PHP, Python, and JavaScript—the primary and most commonly used languages. In Beginning Apache Cassandra Development, author and Cassandra expert Vivek Mishra takes you through using Apache Cassandra from each of these primary languages. Mishra also covers the Cassandra Query Language (CQL), the Apache Cassandra analog to SQL. You'll learn to develop applications sourcing data from Cassandra, query that data, and deliver it at speed to your application's users. Cassandra is one of the leading NoSQL databases, meaning you get unparalleled throughput and performance without the sort of processing overhead that comes with traditional proprietary databases. Beginning Apache Cassandra Development will therefore help you create applications that generate search results quickly, stand up to high levels of demand, scale as your user base grows, ensure operational simplicity, and—not least—provide delightful user experiences.

Computational Methods and Data Engineering

Computational Methods and Data Engineering
Author: Vijendra Singh
Publisher: Springer Nature
Total Pages: 559
Release: 2020-11-04
Genre: Technology & Engineering
ISBN: 9811579075

This book gathers selected high-quality research papers from the International Conference on Computational Methods and Data Engineering (ICMDE 2020), held at SRM University, Sonipat, Delhi-NCR, India. Focusing on cutting-edge technologies and the most dynamic areas of computational intelligence and data engineering, the respective contributions address topics including collective intelligence, intelligent transportation systems, fuzzy systems, data privacy and security, data mining, data warehousing, big data analytics, cloud computing, natural language processing, swarm intelligence, and speech processing.

Hadoop: The Definitive Guide

Hadoop: The Definitive Guide
Author: Tom White
Publisher: "O'Reilly Media, Inc."
Total Pages: 687
Release: 2012-05-10
Genre: Computers
ISBN: 1449338771

Ready to unlock the power of your data? With this comprehensive guide, you’ll learn how to build and maintain reliable, scalable, distributed systems with Apache Hadoop. This book is ideal for programmers looking to analyze datasets of any size, and for administrators who want to set up and run Hadoop clusters. You’ll find illuminating case studies that demonstrate how Hadoop is used to solve specific problems. This third edition covers recent changes to Hadoop, including material on the new MapReduce API, as well as MapReduce 2 and its more flexible execution model (YARN). Store large datasets with the Hadoop Distributed File System (HDFS) Run distributed computations with MapReduce Use Hadoop’s data and I/O building blocks for compression, data integrity, serialization (including Avro), and persistence Discover common pitfalls and advanced features for writing real-world MapReduce programs Design, build, and administer a dedicated Hadoop cluster—or run Hadoop in the cloud Load data from relational databases into HDFS, using Sqoop Perform large-scale data processing with the Pig query language Analyze datasets with Hive, Hadoop’s data warehousing system Take advantage of HBase for structured and semi-structured data, and ZooKeeper for building distributed systems

Apache Hadoop YARN

Apache Hadoop YARN
Author: Arun C. Murthy
Publisher: Pearson Education
Total Pages: 336
Release: 2014
Genre: Computers
ISBN: 0321934504

"Apache Hadoop is helping drive the Big Data revolution. Now, its data processing has been completely overhauled: Apache Hadoop YARN provides resource management at data center scale and easier ways to create distributed applications that process petabytes of data. And now in Apache HadoopTM YARN, two Hadoop technical leaders show you how to develop new applications and adapt existing code to fully leverage these revolutionary advances." -- From the Amazon

Beginning Apache Spark 3

Beginning Apache Spark 3
Author: Hien Luu
Publisher: Apress
Total Pages: 438
Release: 2021-10-23
Genre: Computers
ISBN: 9781484273821

Take a journey toward discovering, learning, and using Apache Spark 3.0. In this book, you will gain expertise on the powerful and efficient distributed data processing engine inside of Apache Spark; its user-friendly, comprehensive, and flexible programming model for processing data in batch and streaming; and the scalable machine learning algorithms and practical utilities to build machine learning applications. Beginning Apache Spark 3 begins by explaining different ways of interacting with Apache Spark, such as Spark Concepts and Architecture, and Spark Unified Stack. Next, it offers an overview of Spark SQL before moving on to its advanced features. It covers tips and techniques for dealing with performance issues, followed by an overview of the structured streaming processing engine. It concludes with a demonstration of how to develop machine learning applications using Spark MLlib and how to manage the machine learning development lifecycle. This book is packed with practical examples and code snippets to help you master concepts and features immediately after they are covered in each section. After reading this book, you will have the knowledge required to build your own big data pipelines, applications, and machine learning applications. What You Will Learn Master the Spark unified data analytics engine and its various components Work in tandem to provide a scalable, fault tolerant and performant data processing engine Leverage the user-friendly and flexible programming model to perform simple to complex data analytics using dataframe and Spark SQL Develop machine learning applications using Spark MLlib Manage the machine learning development lifecycle using MLflow Who This Book Is For Data scientists, data engineers and software developers.

Resilience in the Digital Age

Resilience in the Digital Age
Author: Fred S. Roberts
Publisher: Springer Nature
Total Pages: 199
Release: 2021-02-19
Genre: Computers
ISBN: 3030703703

The growth of a global digital economy has enabled rapid communication, instantaneous movement of funds, and availability of vast amounts of information. With this come challenges such as the vulnerability of digitalized sociotechnological systems (STSs) to destructive events (earthquakes, disease events, terrorist attacks). Similar issues arise for disruptions to complex linked natural and social systems (from changing climates, evolving urban environments, etc.). This book explores new approaches to the resilience of sociotechnological and natural-social systems in a digital world of big data, extraordinary computing capacity, and rapidly developing methods of Artificial Intelligence. Most of the book’s papers were presented at the Workshop on Big Data and Systems Analysis held at the International Institute for Applied Systems Analysis in Laxenburg, Austria in February, 2020. Their authors are associated with the Task Group “Advanced mathematical tools for data-driven applied systems analysis” created and sponsored by CODATA in November, 2018. The world-wide COVID-19 pandemic illustrates the vulnerability of our healthcare systems, supply chains, and social infrastructure, and confronts our notions of what makes a system resilient. We have found that use of AI tools can lead to problems when unexpected events occur. On the other hand, the vast amounts of data available from sensors, satellite images, social media, etc. can also be used to make modern systems more resilient. Papers in the book explore disruptions of complex networks and algorithms that minimize departure from a previous state after a disruption; introduce a multigrammatical framework for the technological and resource bases of today’s large-scale industrial systems and the transformations resulting from disruptive events; and explain how robotics can enhance pre-emptive measures or post-disaster responses to increase resiliency. Other papers explore current directions in data processing and handling and principles of FAIRness in data; how the availability of large amounts of data can aid in the development of resilient STSs and challenges to overcome in doing so. The book also addresses interactions between humans and built environments, focusing on how AI can inform today’s smart and connected buildings and make them resilient, and how AI tools can increase resilience to misinformation and its dissemination.