OpenGL Data Visualization CookbookOpenGL is a great multi-platform, cross-language, and hardware-accelerated graphics interface for visualizing large 2D and 3D datasets. Data visualization has become increasingly challenging using conventional approaches as datasets become larger and larger, especially with the Big Data evolution. From a mobile device to a sophisticated high-performance computing cluster, OpenGL libraries provide developers with an easy-to-use interface to create stunning visuals in 3D in real time for a wide range of interactive applications.
This book provides a series of easy-to-follow, hands-on tutorials to create appealing OpenGL-based visualization tools with minimal development time. We will first illustrate how to quickly set up the development environment in Windows, Mac OS X, and Linux. Next, we will demonstrate how to visualize data for a wide range of applications using OpenGL, starting from simple 2D datasets to increasingly complex 3D datasets with more advanced techniques. Each chapte ...
Spark for Python DevelopersLooking for a cluster computing system that provides high-level APIs? Apache Spark is your answer—an open source, fast, and general purpose cluster computing system. Spark's multi-stage memory primitives provide performance up to 100 times faster than Hadoop, and it is also well-suited for machine learning algorithms.
Are you a Python developer inclined to work with Spark engine? If so, this book will be your companion as you create data-intensive app using Spark as a processing engine, Python visualization libraries, and web frameworks such as Flask.
To begin with, you will learn the most effective way to install the Python development environment powered by Spark, Blaze, and Bookeh. You will then find out how to connect with data stores such as MySQL, MongoDB, Cassandra, and Hadoop.
You'll expand your skills throughout, getting familiarized with the various data sources (Github, Twitter, Meetup, and Blogs), their data structures, and solutions to effectively tackle complex ...
Kafka: The Definitive GuideEvery enterprise application creates data, whether it's log messages, metrics, user activity, outgoing messages, or something else. And how to move all of this data becomes nearly as important as the data itself. If you're an application architect, developer, or production engineer new to Apache Kafka, this practical guide shows you how to use this open source streaming platform to handle real-time data feeds.
Engineers from Confluent and LinkedIn who are responsible for developing Kafka explain how to deploy production Kafka clusters, write reliable event-driven microservices, and build scalable stream-processing applications with this platform. Through detailed examples, you'll learn Kafka's design principles, reliability guarantees, key APIs, and architecture details, including the replication protocol, the controller, and the storage layer.Understand publish-subscribe messaging and how it fits in the big data ecosystem;Explore Kafka producers and consumers for wri ...
Pro Spark StreamingLearn the right cutting-edge skills and knowledge to leverage Spark Streaming to implement a wide array of real-time, streaming applications. This book walks you through end-to-end real-time application development using real-world applications, data, and code. Taking an application-first approach, each chapter introduces use cases from a specific industry and uses publicly available datasets from that domain to unravel the intricacies of production-grade design and implementation. The domains covered in the book include social media, the sharing economy, finance, online advertising, telecommunication, and IoT.
In the last few years, Spark has become synonymous with big data processing. DStreams enhance the underlying Spark processing engine to support streaming analysis with a novel micro-batch processing model. Pro Spark Streaming by Zubair Nabi will enable you to become a specialist of latency sensitive applications by leveraging the key features of DStreams, micro-batch processi ...
Data-oriented Development with AngularJSAngularJS is one of the most popular JavaScript frameworks used to write single page applications and is suitable for developing large-scale enterprise applications. With Firebase, you can easily store and sync data in real time. It has libraries for all the major web and mobile platforms (including AngularJS) and bindings for the most popular frameworks (such as Node.js).
Data-oriented Development with AngularJS is a systematic learning guide that covers important AngularJS concepts such as data binding, dependency injection, directives, and so on. It also covers the basics of Firebase and three-way data binding with AngularFire. You'll be able to create a small project and build a real-time application using Firebase and AngularJS. This project uses most of the concepts and best practices learned in the book so that you can apply the very same principles in real-world AngularJS development. ...
Fast Data Processing with Spark, 2nd EditionSpark is a framework used for writing fast, distributed programs. Spark solves similar problems as Hadoop MapReduce does, but with a fast in-memory approach and a clean functional style API. With its ability to integrate with Hadoop and built-in tools for interactive query analysis (Spark SQL), large-scale graph processing and analysis (GraphX), and real-time analysis (Spark Streaming), it can be interactively used to quickly process and query big datasets.
Fast Data Processing with Spark - Second Edition covers how to write distributed programs with Spark. The book will guide you through every step required to write effective distributed programs from setting up your cluster and interactively exploring the API to developing analytics applications and tuning them for your purposes. ...
SignalR BlueprintsSignalR is an ASP.NET library that enables web developers to add real-time web functionality to ASP.NET applications.
In this book, you'll learn the technical aspects of SignalR and understand why and when you should use SignalR in different use cases. The focus on quality combined with clear, real-world examples will enable you to successfully create your own maintainable software in no time. The book starts by covering the need for SignalR before moving on to its architecture. We'll then take you through the building of a forum that benefits from SignalR. You will also see how to connect your phone as a frontend for SignalR. We will then cover some of the out-of-the-box techniques that you can apply to find out why hosting your solution is vital. ...
Data Science on the Google Cloud PlatformLearn how easy it is to apply sophisticated statistical and machine learning methods to real-world problems when you build on top of the Google Cloud Platform (GCP). This hands-on guide shows developers entering the data science field how to implement an end-to-end data pipeline, using statistical and machine learning methods and tools on GCP. Through the course of the book, you'll work through a sample business decision by employing a variety of data science approaches.
Follow along by implementing these statistical and machine learning solutions in your own project on GCP, and discover how this platform provides a transformative and more collaborative way of doing data science.
Automate and schedule data ingest, using an App Engine application; Create and populate a dashboard in Google Data Studio; Build a real-time analysis pipeline to carry out streaming analytics; Conduct interactive data exploration with Google BigQuery; Create a Bayesian model on a Cloud Dataproc cluster; ...
Streaming DataAs humans, we're constantly filtering and deciphering the information streaming toward us. In the same way, streaming data applications can accomplish amazing tasks like reading live location data to recommend nearby services, tracking faults with machinery in real time, and sending digital receipts before your customers leave the shop. Recent advances in streaming data technology and techniques make it possible for any developer to build these applications if they have the right mindset. This book will let you join them.
Streaming Data is an idea-rich tutorial that teaches you to think about efficiently interacting with fast-flowing data. Through relevant examples and illustrated use cases, you'll explore designs for applications that read, analyze, share, and store streaming data. Along the way, you'll discover the roles of key technologies like Spark, Storm, Kafka, Flink, RabbitMQ, and more. This book offers the perfect balance between big-picture thinking and implementation deta ...
Defending IoT Infrastructures with the Raspberry PiApply a methodology and practical solutions for monitoring the behavior of the Internet of Things (IoT), industrial control systems (ICS), and other critical network devices with the inexpensive Raspberry Pi. With this book, you will master passive monitoring and detection of aberrant behavior, and learn how to generate early indications and warning of attacks targeting IoT, ICS, and other critical network resources.
Defending IoT Infrastructures with the Raspberry Pi provides techniques and scripts for the discovery of dangerous data leakage events emanating from IoT devices. Using Raspbian Linux and specialized Python scripts, the book walks through the steps necessary to monitor, detect, and respond to attacks targeting IoT devices.
There are several books that cover IoT, IoT security, Raspberry Pi, and Python separately, but this book is the first of its kind to put them all together. It takes a practical approach, providing an entry point and level playing field for a wide ...