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Architecting HBase Applications

HBase is a remarkable tool for indexing mass volumes of data, but getting started with this distributed database and its ecosystem can be daunting. With this hands-on guide, you’ll learn how to architect, design, and deploy your own HBase applications by examining real-world solutions. Along with HBase principles and cluster deployment guidelines, this book includes in-depth case studies that demonstrate how large companies solved specific use cases with HBase. Authors Jean-Marc Spaggiari and Kevin O’Dell also provide draft solutions and code examples to help you implement your own versions of those use cases, from master data management (MDM) and document storage to near real-time event processing. You’ll also learn troubleshooting techniques to help you avoid common deployment mistakes. Learn exactly what HBase does, what its ecosystem includes, and how to set up your environment Explore how real-world HBase instances were deployed and put into production Examine documented use cases for tracking healthcare claims, digital advertising, data management, and product quality Understand how HBase works with tools and techniques such as Spark, Kafka, MapReduce, and the Java API Learn how to identify the causes and understand the consequences of the most common HBase issues

Data Visualization with Python and JavaScript

Learn how to turn raw data into rich, interactive web visualizations with the powerful combination of Python and JavaScript. With this hands-on guide, author Kyran Dale teaches you how build a basic dataviz toolchain with best-of-breed Python and JavaScript libraries—including Scrapy, Matplotlib, Pandas, Flask, and D3—for crafting engaging, browser-based visualizations. As a working example, throughout the book Dale walks you through transforming Wikipedia’s table-based list of Nobel Prize winners into an interactive visualization. You’ll examine steps along the entire toolchain, from scraping, cleaning, exploring, and delivering data to building the visualization with JavaScript’s D3 library. If you’re ready to create your own web-based data visualizations—and know either Python or JavaScript— this is the book for you. Learn how to manipulate data with Python Understand the commonalities between Python and JavaScript Extract information from websites by using Python’s web-scraping tools, BeautifulSoup and Scrapy Clean and explore data with Python’s Pandas, Matplotlib, and Numpy libraries Serve data and create RESTful web APIs with Python’s Flask framework Create engaging, interactive web visualizations with JavaScript’s D3 library

podcast_episode
by Michael Healy (Search Discovery) , Tim Wilson (Analytics Power Hour - Columbus (OH) , Michael Helbling (Search Discovery)

In this episode, we dive deep on a 1988 classic: Tom Hanks, under the direction of Penny Marshall, was a 12-year-old in a 30-year-old's body... Actually, that's a different "Big" from what we actually cover in this episode. In this instant classic, the star is BigQuery, the director is Google, and Michael Healy, a data scientist from Search Discovery, delivers an Oscar-worthy performance as Zoltar. In under 48 minutes, Michael (Helbling) and Tim drastically increased their understanding of what Google BigQuery is and where it fits in the analytics landscape. If you'd like to do the same, give it a listen! Technologies, books, and sites referenced in this episode were many, including: Google BigQuery and the BigQuery API Libraries, Google Cloud Services, Google Dremel, Apache Drill, Amazon Redshift (AWS), Rambo III (another 1988 movie!), Hadoop, Cloudera, the Observepoint Tag Debugger, Our Mathematical Universe by Max Tegmark, A Brief History of Time by Stephen Hawking, and a video of math savant Scott Flansburg.

Java XML and JSON

Java XML and JSON is your one-stop guide to mastering the XML metalanguage and JSON data format along with significant Java APIs for parsing and creating XML/JSON documents (and more). The first six chapters focus on XML along with the SAX, DOM, StAX, XPath, and XSLT APIs. The remaining four chapters focus on JSON along with the mJson, GSON, and JsonPath APIs. Each chapter ends with select exercises designed to challenge your grasp of the chapter's content. An appendix provides the answers to these exercises. What You'll Learn Master the XML language Learn how to validate XML documents Learn how to parse XML documents with the SAX, DOM, and StAX APIs Learn how to create XML documents with the DOM and StAX APIs Learn how to extract values from XML documents with the XPath API Learn how to transform XML documents with the XSLT API Master the JSON format Learn how to validate JSON documents Learn how to parse and create JSON documents with the mJson and Gson APIs Learn how to extract values from JSON documents with the JsonPath API Who This Book Is For Intermediate or advanced Java programmers/developers.

Spark GraphX in Action

Spark GraphX in Action starts out with an overview of Apache Spark and the GraphX graph processing API. This example-based tutorial then teaches you how to configure GraphX and how to use it interactively. Along the way, you'll collect practical techniques for enhancing applications and applying machine learning algorithms to graph data. About the Technology GraphX is a powerful graph processing API for the Apache Spark analytics engine that lets you draw insights from large datasets. GraphX gives you unprecedented speed and capacity for running massively parallel and machine learning algorithms. About the Book Spark GraphX in Action begins with the big picture of what graphs can be used for. This example-based tutorial teaches you how to use GraphX interactively. You'll start with a crystal-clear introduction to building big data graphs from regular data, and then explore the problems and possibilities of implementing graph algorithms and architecting graph processing pipelines. Along the way, you'll collect practical techniques for enhancing applications and applying machine learning algorithms to graph data. What's Inside Understanding graph technology Using the GraphX API Developing algorithms for big graphs Machine learning with graphs Graph visualization About the Reader Readers should be comfortable writing code. Experience with Apache Spark and Scala is not required. About the Authors Michael Malak has worked on Spark applications for Fortune 500 companies since early 2013. Robin East has worked as a consultant to large organizations for over 15 years and is a data scientist at Worldpay. Quotes Learn complex graph processing from two experienced authors…A comprehensive guide. - Gaurav Bhardwaj, 3Pillar Global The best resource to go from GraphX novice to expert in the least amount of time. - Justin Fister, PaperRater A must-read for anyone serious about large-scale graph data mining! - Antonio Magnaghi, OpenMail Reveals the awesome and elegant capabilities of working with linked data for large-scale datasets. - Sumit Pal, Independent consultant

Spring Persistence with Hibernate, Second Edition

Learn how to use the core Hibernate APIs and tools as part of the Spring Framework. This book illustrates how these two frameworks can be best utilized. Other persistence solutions available in Spring are also shown including the Java Persistence API (JPA). Spring Persistence with Hibernate, Second Edition has been updated to cover Spring Framework version 4 and Hibernate version 5. After reading and using this book, you'll have the fundamentals to apply these persistence solutions into your own mission-critical enterprise Java applications that you build using Spring. Persistence is an important set of techniques and technologies for accessing and using data, and ensuring that data is mobile regardless of specific applications and contexts. In Java development, persistence is a key factor in enterprise, e-commerce, and other transaction-oriented applications. Today, the agile and open source Spring Framework is the leading out-of-the-box, open source solution for enterprise Java developers; in it, you can find a number of Java persistence solutions What You'll Learn Use Spring Persistence, including using persistence tools in Spring as well as choosing the best Java persistence frameworks outside of Spring Take advantage of Spring Framework features such as Inversion of Control (IoC), aspect-oriented programming (AOP), and more Work with Spring JDBC, use declarative transactions with Spring, and reap the benefits of a lightweight persistence strategy Harness Hibernate and integrate it into your Spring-based enterprise Java applications for transactions, data processing, and more Integrate JPA for creating a well-layered persistence tier in your enterprise Java application Who This Book Is For This book is ideal for developers interested in learning more about persistence framework options on the Java platform, as well as fundamental Spring concepts. Because the book covers several persistence frameworks, it is suitable for anyone interested in learning more about Spring or any of the frameworks covered. Lastly, this book covers advanced topics related to persistence architecture and design patterns, and is ideal for beginning developers looking to learn more in these areas.

Mastering the SAS DS2 Procedure

Enhance your SAS® data wrangling skills with high precision and parallel data manipulation using the new DS2 programming language.

This book addresses the new DS2 programming language from SAS, which combines the precise procedural power and control of the Base SAS DATA step language with the simplicity and flexibility of SQL. DS2 provides simple, safe syntax for performing complex data transformations in parallel and enables manipulation of native database data types at full precision. It also introduces PROC FEDSQL, a modernized SQL language that blends perfectly with DS2. You will learn to harness the power of parallel processing to speed up CPU-intensive computing processes in Base SAS and how to achieve even more speed by processing DS2 programs on massively parallel database systems. Techniques for leveraging Internet APIs to acquire data, avoiding large data movements when working with data from disparate sources, and leveraging DS2’s new data types for full-precision numeric calculations are presented, with examples of why these techniques are essential for the modern data wrangler.

While working through the code samples provided with this book, you will build a library of custom, reusable, and easily shareable DS2 program modules, execute parallelized DATA step programs to speed up a CPU-intensive process, and conduct advanced data transformations using hash objects and matrix math operations.

NumPy Essentials

NumPy Essentials is your guide to mastering NumPy, the powerful Python library for scientific computing. In this book, you'll discover how to manipulate arrays, perform mathematical operations, and create advanced models. With its clear examples and practical exercises, you'll build the skills needed to efficiently tackle analytical challenges. What this Book will help me do Learn to manipulate data efficiently with NumPy array objects and universal functions. Gain proficiency in solving linear algebra problems using NumPy's powerful modules. Master regression techniques and curve fitting for statistical modeling. Apply Fourier Transform and spectral analysis in solving real-world problems. Integrate and optimize Python code using Cython and the NumPy C API for higher performance. Author(s) Jaidev Deshpande, None Chin, Tanmay Dutta, and Shane Holloway are seasoned developers passionate about Python and scientific computing. With experience across diverse projects, they bring practical insights and accessible explanations to their writing. Who is it for? This book is ideal for Python developers seeking to sharpen their numerical computing skills. Prior experience with Python is expected, as the content progresses quickly to advanced topics. Whether you're working in data analysis, scientific research, or machine learning, this book will provide valuable tools and insights.

IBM z13 and IBM z13s Technical Introduction

This IBM® Redbooks® publication introduces the latest IBM z Systems™ platforms, the IBM z13™ and IBM z13s. It includes information about the z Systems environment and how it can help integrate data, transactions, and insight for faster and more accurate business decisions. The z13 and z13s are state-of-the-art data and transaction systems that deliver advanced capabilities that are vital to modern IT infrastructures. These capabilities include: Accelerated data and transaction serving Integrated analytics Access to the API economy Agile development and operations Efficient, scalable, and secure cloud services End-to-end security for data and transactions This book explains how these systems use both new innovations and traditional z Systems strengths to satisfy growing demand for cloud, analytics, and mobile applications. With one of these z Systems platforms as the base, applications can run in a trusted, reliable, and secure environment that both improves operations and lessens business risk.

Data Wrangling with Python

How do you take your data analysis skills beyond Excel to the next level? By learning just enough Python to get stuff done. This hands-on guide shows non-programmers like you how to process information that’s initially too messy or difficult to access. You don't need to know a thing about the Python programming language to get started. Through various step-by-step exercises, you’ll learn how to acquire, clean, analyze, and present data efficiently. You’ll also discover how to automate your data process, schedule file- editing and clean-up tasks, process larger datasets, and create compelling stories with data you obtain. Quickly learn basic Python syntax, data types, and language concepts Work with both machine-readable and human-consumable data Scrape websites and APIs to find a bounty of useful information Clean and format data to eliminate duplicates and errors in your datasets Learn when to standardize data and when to test and script data cleanup Explore and analyze your datasets with new Python libraries and techniques Use Python solutions to automate your entire data-wrangling process

Elasticsearch Essentials

"Elasticsearch Essentials" provides a comprehensive introduction to Elasticsearch, the powerful search and analytics engine. This book delivers a fast-paced, practical guide to harnessing Elasticsearch for creating scalable search and analytics applications. What this Book will help me do Learn to effectively use Elasticsearch REST APIs for search and analytics. Understand and design schema and mappings with best practices. Master data modeling concepts for efficient data queries. Develop skills to create and manage Elasticsearch clusters in production. Learn techniques for ensuring high availability and handling large datasets. Author(s) Bharvi Dixit is a seasoned developer and expert in search technologies with hands-on experience in Elasticsearch and other search solutions. With extensive knowledge in data analytics and large-scale systems, Bharvi ensures readers gain practical skills and insights through well-structured examples and explanations. Who is it for? This book is perfect for developers looking to enhance their skills in building search and analytics solutions with Elasticsearch. It's particularly suited for those familiar with search technologies like Apache Lucene or Solr but new to Elasticsearch. Beginners to intermediate learners in big data and analytics will find the structured approach beneficial. It's ideal for professionals aspiring to develop advanced search implementations with modern tools.

Scalable Big Data Architecture: A Practitioner’s Guide to Choosing Relevant Big Data Architecture

This book highlights the different types of data architecture and illustrates the many possibilities hidden behind the term "Big Data", from the usage of No-SQL databases to the deployment of stream analytics architecture, machine learning, and governance. Scalable Big Data Architecture covers real-world, concrete industry use cases that leverage complex distributed applications , which involve web applications, RESTful API, and high throughput of large amount of data stored in highly scalable No-SQL data stores such as Couchbase and Elasticsearch. This book demonstrates how data processing can be done at scale from the usage of NoSQL datastores to the combination of Big Data distribution. When the data processing is too complex and involves different processing topology like long running jobs, stream processing, multiple data sources correlation, and machine learning, it’s often necessary to delegate the load to Hadoop or Spark and use the No-SQL to serve processed data in real time. This book shows you how to choose a relevant combination of big data technologies available within the Hadoop ecosystem. It focuses on processing long jobs, architecture, stream data patterns, log analysis, and real time analytics. Every pattern is illustrated with practical examples, which use the different open sourceprojects such as Logstash, Spark, Kafka, and so on. Traditional data infrastructures are built for digesting and rendering data synthesis and analytics from large amount of data. This book helps you to understand why you should consider using machine learning algorithms early on in the project, before being overwhelmed by constraints imposed by dealing with the high throughput of Big data. Scalable Big Data Architecture is for developers, data architects, and data scientists looking for a better understanding of how to choose the most relevant pattern for a Big Data project and which tools to integrate into that pattern.

Client-Side Data Storage

One of the most useful features of today’s modern browsers is the ability to store data right on the user’s computer or mobile device. Even as more people move toward the cloud, client-side storage can still save web developers a lot of time and money, if you do it right. This hands-on guide demonstrates several storage APIs in action. You’ll learn how and when to use them, their plusses and minuses, and steps for implementing one or more of them in your application.

Accelerating Data Transformation with IBM DB2 Analytics Accelerator for z/OS Understanding and Using Accelerator-only Tables

Transforming data from operational data models to purpose-oriented data structures has been commonplace for the last decades. Data transformations are heavily used in all types of industries to provide information to various users at different levels. Depending on individual needs, the transformed data is stored in various different systems. Sending operational data to other systems for further processing is then required, and introduces much complexity to an existing information technology (IT) infrastructure. Although maintenance of additional hardware and software is one component, potential inconsistencies and individually managed refresh cycles are others. For decades, there was no simple and efficient way to perform data transformations on the source system of operational data. With IBM® DB2® Analytics Accelerator, DB2 for z/OS is now in a unique position to complete these transformations in an efficient and well-performing way. DB2 for z/OS completes these while connecting to the same platform as for operational transactions, helping you to minimize your efforts to manage existing IT infrastructure. Real-time analytics on incoming operational transactions is another demand. Creating a comprehensive scoring model to detect specific patterns inside your data can easily require multiple iterations and multiple hours to complete. By enabling a first set of analytical functionality in DB2 Analytics Accelerator, those dedicated mining algorithms can now be run on an accelerator to efficiently perform these modeling tasks. Given the speed of query processing on an accelerator, these modeling tasks can now be performed much quicker compared to traditional relational database management systems. This speed enables you to keep your scoring algorithms more up-to-date, and ultimately adapt more quickly to constantly changing customer behaviors. This IBM Redbooks® publication describes the new table type that is introduced with DB2 Analytics Accelerator V4.1 PTF5 that enables more efficient data transformations. These tables are called accelerator-only tables, and can exist on an accelerator only. The tables benefit from the accelerator performance characteristics, while maintaining access through existing DB2 for z/OS application programming interfaces (APIs). Additionally, we describe the newly introduced analytical capabilities with DB2 Analytics Accelerator V5.1, putting you in the position to efficiently perform data modeling for online analytical requirements in your DB2 for z/OS environment. This book is intended for technical decision-makers who want to get a broad understanding about the analytical capabilities and accelerator-only tables of DB2 Analytics Accelerator. In addition, you learn about how these capabilities can be used to accelerate in-database transformations and in-database analytics in various environments and scenarios, including the following scenarios: Multi-step processing and reporting in IBM DB2 Query Management Facility™, IBM Campaign, or Microstrategy environments In-database transformations using IBM InfoSphere® DataStage® Ad hoc data analysis for data scientists In-database analytics using IBM SPSS® Modeler

Elasticsearch in Action

Elasticsearch in Action teaches you how to build scalable search applications using Elasticsearch. You'll ramp up fast, with an informative overview and an engaging introductory example. Within the first few chapters, you'll pick up the core concepts you need to implement basic searches and efficient indexing. With the fundamentals well in hand, you'll go on to gain an organized view of how to optimize your design. Perfect for developers and administrators building and managing search-oriented applications. About the Technology Modern search seems like magic'you type a few words and the search engine appears to know what you want. With the Elasticsearch real-time search and analytics engine, you can give your users this magical experience without having to do complex low-level programming or understand advanced data science algorithms. You just install it, tweak it, and get on with your work. About the Book Elasticsearch in Action teaches you how to write applications that deliver professional quality search. As you read, you'll learn to add basic search features to any application, enhance search results with predictive analysis and relevancy ranking, and use saved data from prior searches to give users a custom experience. This practical book focuses on Elasticsearch's REST API via HTTP. Code snippets are written mostly in bash using cURL, so they're easily translatable to other languages. What's Inside What is a great search application? Building scalable search solutions Using Elasticsearch with any language Configuration and tuning About the Reader This book is for developers and administrators building and managing search-oriented applications. About the Authors Radu Gheorghe is a search consultant and software engineer. Matthew Lee Hinman develops highly available, cloud-based systems. Roy Russo is a specialist in predictive analytics. Quotes To understand how a modern search infrastructure works is a daunting task. Radu, Matt, and Roy make it an engaging, hands-on experience. - Sen Xu, Twitter Inc. An indispensable guide to the challenges of search of semi-structured data. - Artur Nowak, Evidence Prime The best resource for a complex topic. Highly recommended. - Daniel Beck, juris GmbH Took me from confused to confident in a week. - Alan McCann, Givsum.com

Web Development with MongoDB and NodeJS - Second Edition

Discover how to build a full-featured, interactive web application from scratch using Node.js and MongoDB in this comprehensive guide. You will learn to set up your development environment, create a web server with Express.js, and integrate MongoDB for data persistence. By the end of this book, you will have the knowledge and skills to develop and deploy robust web applications ready for the cloud. What this Book will help me do Set up a Node.js development environment and connect it to MongoDB. Develop a web server using Express.js and write integrated APIs. Implement dynamic HTML pages leveraging the Handlebars template engine. Build efficient and scalable data-driven features using Mongoose ODM. Deploy web applications seamlessly to cloud platforms like Heroku, AWS, or Azure. Author(s) This book was co-authored by experts None Satheesh, None Joseph D'mello, and Jason Krol, who bring years of experience in software development and expertise in modern web technologies. With a focus on practical application and best practices, the authors aim to empower readers to succeed in real-world development projects using the innovative Node.js and MongoDB stack. Who is it for? This book is tailored for developers who have a basic understanding of JavaScript and HTML and wish to advance their web development skills. If you are motivated to learn how to leverage Node.js and MongoDB for full-stack development or are curious about building and deploying complete web applications, this book is ideal for you. It addresses learners from early career to experienced developers looking to strengthen their skills in modern development stacks.

Hadoop with Python

Hadoop is mostly written in Java, but that doesn't exclude the use of other programming languages with this distributed storage and processing framework, particularly Python. With this concise book, you’ll learn how to use Python with the Hadoop Distributed File System (HDFS), MapReduce, the Apache Pig platform and Pig Latin script, and the Apache Spark cluster-computing framework. Authors Zachary Radtka and Donald Miner from the data science firm Miner & Kasch take you through the basic concepts behind Hadoop, MapReduce, Pig, and Spark. Then, through multiple examples and use cases, you'll learn how to work with these technologies by applying various Python tools. Use the Python library Snakebite to access HDFS programmatically from within Python applications Write MapReduce jobs in Python with mrjob, the Python MapReduce library Extend Pig Latin with user-defined functions (UDFs) in Python Use the Spark Python API (PySpark) to write Spark programs with Python Learn how to use the Luigi Python workflow scheduler to manage MapReduce jobs and Pig scripts Zachary Radtka, a platform engineer at Miner & Kasch, has extensive experience creating custom analytics that run on petabyte-scale data sets.

Learning Android Google Maps

Learning Android Google Maps is the ultimate guide to integrating Google Maps into your Android applications. This book takes you through the process of setting up, customizing, and leveraging this powerful feature. By the end, you'll be adept at creating engaging map functionalities applicable for any Android project. What this Book will help me do Understand how to set up the Android development environment and obtain the Google API key to start using Maps. Gain the skills to add features to Google Maps, such as markers, overlays, and custom information windows. Learn how to work with various types of maps, enabling specific applications. Master the ability to connect your map with real-time GPS data, offering user location-based services. Discover how to implement Google Street View and other interactive geographic features into your apps. Author(s) This book is meticulously compiled by developers with extensive experience in building Android applications and implementing Google Maps. Their combined years of hands-on development ensure the instructions are clear, comprehensive, and practical. Their passion for teaching shines as they break down complex topics into easy-to-understand explanations. Who is it for? This book is ideal for Android developers looking to integrate map functionalities into their apps. Beginners can follow along due to its detailed, step-by-step approach, while intermediate developers will appreciate the customization techniques and advanced features covered. If you aim to master Google Maps API in Android development, this book is for you.

Oracle API Management 12c Implementation

Unlock the full potential of Oracle's API Management Solution 12c with this comprehensive guide. Through a practical case study, you'll master how to implement API strategies, develop and manage APIs, and leverage Oracle's tools for API governance and community management. This book equips you with the knowledge needed to align API functionality with business goals. What this Book will help me do Master the principles of API management and the differences between API Management and SOA Governance. Learn how to define and implement an API management strategy aligned with business drivers. Understand the intricacies of Oracle's API Management Solution components: OAC, OAPIM, and OAG. Explore hands-on use cases for applying API management in organizational scenarios. Acquire skills in deploying Oracle API Management products with tips for real-world implementation. Author(s) None Carrasco is an experienced technical architect specializing in SOA Governance and API Management. With a career dedicated to exploring Oracle's solutions, they bring hands-on expertise in applying technical concepts to solve real-world problems. Known for their clear and structured teaching, None ensures readers gain practical knowledge to drive value through technology. Who is it for? This book is ideal for Enterprise Architects, Solution Architects, Technical Architects, and API consultants seeking to deepen their understanding of API management with the Oracle 12c suite. If you're familiar with basic IT infrastructure concepts and looking to integrate business priorities with API development processes, this guide is tailored for you.

Mastering ArcGIS Server Development with JavaScript

Learn how to create interactive and stylish web mapping applications with "Mastering ArcGIS Server Development with JavaScript." By focusing on the ArcGIS JavaScript API along with modern development practices, this book provides you with practical examples and insights to build functional, visually appealing GIS applications for the web. What this Book will help me do Integrate and display data from multiple sources into a single-page application using mapping tools. Customize widgets and maps to ensure user engagement and optimal functionality. Use charts and graphs to intuitively represent geographic data insights. Combine the ArcGIS JavaScript API with popular JavaScript libraries for advanced map-making features. Develop web maps suitable for multiple devices and test for platform compatibility. Author(s) None Doman is a seasoned GIS developer with extensive experience in the ArcGIS ecosystem. Specializing in integrating cutting-edge JavaScript techniques with GIS solutions, Doman focuses on empowering developers through comprehensive and insightful learning materials. Their approachable writing style ensures even complex concepts are accessible and engaging. Who is it for? This book is aimed at professional developers looking to enhance their GIS application development skills. Ideal readers have a fundamental understanding of ArcGIS Server and some experience with developing using JavaScript. It is especially beneficial for those eager to apply GIS solutions in web development scenarios. It's perfect for those ready to deepen their expertise in GIS programming and create impactful web mapping applications.