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Applied Akka Patterns
Applied Akka Patterns

When it comes to big data processing, we can no longer ignore concurrency or try to add it in after the fact. Fortunately, the solution is not a new paradigm of development, but rather an old one. With this hands-on guide, Java and Scala developers will learn how to embrace concurrent and distributed applications with the open source Akka toolkit. You'll learn how to put the actor model and its associated patterns to immediate and practical use. Throughout the book, you'll deal with an analogous workforce problem: how to schedule a group of people across a variety of projects while optimizing their time and skillsets. This example will help you understand how Akka uses actors, streams, and other tools to stitch your application together.Model software that reflects the real world with domain-driven design;Learn principles and practices for implementing individual actors;Unlock the real potential of Akka with patterns for combining multiple actors;Und ...
High Performance Spark
High Performance Spark

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. 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 parad ...
Advanced Analytics with Spark, 2nd Edition
Advanced Analytics with Spark, 2nd Edition

In the second edition of this practical book, four Cloudera data scientists present a set of self-contained patterns for performing large-scale data analysis with Spark. The authors bring Spark, statistical methods, and real-world data sets together to teach you how to approach analytics problems by example. Updated for Spark 2.1, this edition acts as an introduction to these techniques and other best practices in Spark programming. You'll start with an introduction to Spark and its ecosystem, and then dive into patterns that apply common techniques - including classification, clustering, collaborative filtering, and anomaly detection - to fields such as genomics, security, and finance. If you have an entry-level understanding of machine learning and statistics, and you program in Java, Python, or Scala, you'll find the book's patterns useful for working on your own data applications. Familiarize yourself with the Spark programming model; Become comfortable within the Spark ec ...
Reactive Application Development
Reactive Application Development

Mission-critical applications have to respond instantly to changes in load, recover gracefully from failure, and satisfy exacting requirements for performance, cost, and reliability. That's no small task! Reactive designs make it easier to meet these demands through modular, message-driven architecture, innovative tooling, and cloud-based infrastructure. Reactive Application Development teaches you how to build reliable enterprise applications using reactive design patterns. This hands-on guide begins by exposing you to the reactive mental model, along with a survey of core technologies like the Akka actors framework. Then, you'll build a proof-of-concept system in Scala, and learn to use patterns like CQRS and Event Sourcing. You'll master the principles of reactive design as you implement elasticity and resilience, integrate with traditional architectures, and learn powerful testing techniques. ...
Learning Spark
Learning Spark

Data in all domains is getting bigger. How can you work with it efficiently? Recently updated for Spark 1.3, this book introduces Apache Spark, the open source cluster computing system that makes data analytics fast to write and fast to run. With Spark, you can tackle big datasets quickly through simple APIs in Python, Java, and Scala. This 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. You'll learn how to express parallel jobs with just a few lines of code, and cover applications from simple batch jobs to stream processing and machine learning. Quickly dive into Spark capabilities such as distributed datasets, in-memory caching, and the interactive shell; Leverage Spark's powerful built-in libraries, including Spark SQL, Spark Streaming, and MLlib; Use one programming paradigm instead of mixing and matching tools like Hiv ...
Machine Learning Systems
Machine Learning Systems

If you're building machine learning models to be used on a small scale, you don't need this book. But if you're a developer building a production-grade ML application that needs quick response times, reliability, and good user experience, this is the book for you. It collects principles and practices of machine learning systems that are dramatically easier to run and maintain, and that are reliably better for users. Machine Learning Systems: Designs that scale teaches you to design and implement production-ready ML systems. You'll learn the principles of reactive design as you build pipelines with Spark, create highly scalable services with Akka, and use powerful machine learning libraries like MLib on massive datasets. The examples use the Scala language, but the same ideas and tools work in Java as well. ...
Mastering Functional Programming
Mastering Functional Programming

In large projects, it can get difficult keeping track of all the interdependencies of the code base and how its state changes at runtime. Functional Programming helps us solve these problems. It is a paradigm specifically designed to deal with the complexity of software development. This book will show you how the right abstractions can reduce complexity and make your code easy to read and understand. Mastering Functional Programming begins by touching upon the basics such as what lambdas are and how to write declarative code with the help of functions. It then moves on to more advanced concepts such as pure functions and type classes, the problems they aim to solve, and how to use them in real-world scenarios. You will also explore some of the more advanced patterns in the world of functional programming, such as monad transformers and Tagless Final. In the concluding chapters, you will be introduced to the actor model, implement it in modern functional languages, and explore the s ...
Reactive Web Applications
Reactive Web Applications

Reactive Web Applications teaches web developers how to benefit from the reactive application architecture and presents hands-on examples using the Play framework. Reactive applications build on top of components that communicate asynchronously as they react to user and system events. As a result, they become scalable, responsive, and fault-tolerant. Java and Scala developers can use the Play Framework and the Akka concurrency toolkit to easily implement reactive applications without building everything from scratch. Reactive Web Applications teaches web developers how to benefit from the reactive application architecture and presents hands-on examples using Play, Akka, Scala, and Reactive Streams. This book starts by laying out the fundamentals required for writing functional and asynchronous applications and quickly introduces Play as a framework to handle the plumbing of your application. The book alternates between chapters that introduce reactive ideas (asynchronous programm ...
Just Enough R
Just Enough R

If your job involves working with data in any manner, you cannot afford to ignore the R revolution! If your domain is called data analysis, analytics, informatics, data science, reporting, business intelligence, data management, big data, or visualization, you just have to learn R as this programming language is a game-changing sledgehammer. However, if you have looked at a standard text on R or read some of the online discussions, you might feel that there is a steep learning curve of six months or more to grok the language. I will debunk this myth through my book by focusing on practical essentials instead of theory. If you have programmed in some language in the past (whether that language be SAS, SPSS, C, C++, C#, Java, Python, Perl, Visual Basic, Ruby, Scala, shell scripts, or plain old SQL), even if you are rusty, this book will get you up and running with R in a single day, writing programs for data analysis and visualization. ...
Learning Go
Learning Go

This is an introduction to the Go language from Google. Its aim is to provide a guide to this new and innovative language. The intended audience of this book is people who are familiar with programming and know multiple programming languages,be it C, C++, Perl, Java, Erlang, Scala or Haskell. This is not a book which teaches you how to program, this is a bookthat just teaches you how to use Go. As with learning new things, probably the best way to do this is to discover it for yourself by creating your own programs. Therefor includes each chapter a number of exercises (and answers) to acquaint you with the language. ...
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