Ruby Data Processing
Using Map, Reduce, and Select
| Price | $14.37 - $24.25
|
| Rating |   |
| Author | Jay Godse |
| Publisher | Apress |
| Published | 2018 |
| Pages | 98 |
| Language | English |
| Format | Paper book / ebook (PDF) |
| ISBN-10 | 1484234731 |
| ISBN-13 | 9781484234730 |
Gain the basics of Ruby's map, reduce, and select functions and discover how to use them to solve data-processing problems. This compact hands-on book explains how you can encode certain complex programs in 10 lines of Ruby code, an astonishingly small number. You will walk through problems and solutions which are effective because they use map, reduce, and select. As you read Ruby Data Processing, type in the code, run the code, and ponder the results. Tweak the code to test the code and see how the results change.
After reading this book, you will have a deeper understanding of how to break data-processing problems into processing stages, each of which is understandable, debuggable, and composable, and how to combine the stages to solve your data-processing problem. As a result, your Ruby coding will become more efficient and your programs will be more elegant and robust.
Discover Ruby data processing and how to do it using the map, reduce, and select functions; Develop complex solutions including debugging, randomizing, sorting, grouping, and more; Reverse engineer complex data-processing solutions.
- Jay Godse
4 5 7
Similar Books
Apache Spark 2: Data Processing and Real-Time Analytics
by Romeo Kienzler, Md. Rezaul Karim, Sridhar Alla, Siamak Amirghodsi, Meenakshi Rajendran, Broderick Hall, Shuen Mei
Apache Spark is an in-memory, cluster-based data processing system that provides a wide range of functionalities such as big data processing, analytics, machine learning, and more. With this Learning Path, you can take your knowledge of Apache Spark to the next level by learning how to expand Spark's functionality and building your o...
Price: $49.99 | Publisher: Packt Publishing | Release: 2018
Big Data Processing with Apache Spark
by Manuel Ignacio Franco Galeano
Processing big data in real time is challenging due to scalability, information consistency, and fault-tolerance. This book teaches you how to use Spark to make your overall analytical workflow faster and more efficient. You'll explore all core concepts and tools within the Spark ecosystem, such as Spark Streaming, the Spark Streamin...
Price: $29.99 | Publisher: Packt Publishing | Release: 2018
by Tyler Akidau, Slava Chernyak, Reuven Lax
Streaming data is a big deal in big data these days. As more and more businesses seek to tame the massive unbounded data sets that pervade our world, streaming systems have finally reached a level of maturity sufficient for mainstream adoption. With this practical guide, data engineers, data scientists, and developers will learn how to wo...
Price: $52.52 | Publisher: O'Reilly Media | Release: 2018
Fast Data Processing with Spark
by Holden Karau
Spark is a framework 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 inbuilt tools for interactive query analysis (Shark), large-scale graph processing and analysis (Bagel), and ...
Price: $22.99 | Publisher: Packt Publishing | Release: 2013
Storm Blueprints: Patterns for Distributed Real-time Computation
by P. Taylor Goetz, Brian O'Neill
Storm is the most popular framework for real-time stream processing. Storm provides the fundamental primitives and guarantees required for fault-tolerant distributed computing in high-volume, mission critical applications. It is both an integration technology as well as a data flow and control mechanism, making it the core of many big dat...
Price: $24.99 | Publisher: Packt Publishing | Release: 2014
by Sandeep Karanth
Hadoop is synonymous with Big Data processing. Its simple programming model, "code once and deploy at any scale" paradigm, and an ever-growing ecosystem makes Hadoop an all-encompassing platform for programmers with different levels of expertise.This book explores the industry guidelines to optimize MapReduce jobs and hi...
Price: $49.99 | Publisher: Packt Publishing | Release: 2014
Fast Data Processing with Spark, 2nd Edition
by Krishna Sankar, Holden Karau
Spark 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 (G...
Price: $29.99 | Publisher: Packt Publishing | Release: 2015
Apache Hadoop 3 Quick Start Guide
by Hrishikesh Karambelkar
Apache Hadoop is a widely used distributed data platform. It enables large datasets to be efficiently processed instead of using one large computer to store and process the data. This book will get you started with the Hadoop ecosystem, and introduce you to the main technical topics, including MapReduce, YARN, and HDFS.The book begins wit...
Price: $29.99 | Publisher: Packt Publishing | Release: 2018