SAS Viya

Yue Qi, Kevin D. Smith, Xiangxiang Meng

Description

Learn how to access analytics from SAS Cloud Analytic Services (CAS) using R and the SAS Viya platform.

SAS Viya : The R Perspective is a general-purpose introduction to using R with the SAS Viya platform. SAS Viya is a high-performance, fault-tolerant analytics architecture that can be deployed on both public and private cloud infrastructures. This book introduces an entirely new way of using SAS statistics from R, taking users step-by-step from installation and fundamentals to data exploration and modeling.

SAS Viya is made up of multiple components. The central piece of this ecosystem is SAS Cloud Analytic Services (CAS). CAS is the cloud-based server that all clients communicate with to run analytical methods. While SAS Viya can be used by various SAS applications, it also enables you to access analytic methods from SAS, R, Python, Lua, and Java, as well as through a REST interface using HTTP or HTTPS. The R client is used to drive the CAS component directly using commands and actions that are familiar to R programmers.

Key features of this book include:

• Connecting to CAS from R
  
• Loading, managing, and exploring CAS Data from R
  
• Executing CAS actions and processing the results
  
• Handling CAS action errors
  
• Modeling continuous and categorical data

This book is intended for R users who want to access SAS analytics as well as SAS users who are interested in trying R. Familiarity with R would be helpful before using this book although knowledge of CAS is not required. However, you will need to have a CAS server set up and running to execute the examples in this book.

Sujets

• Cloud computing
• Analytics
• Machine learning

Informations

• Publié par: SAS Institute
• Date de parution: 20 juillet 2018
• Nombre de lectures: 5
• EAN13: 9781635267013
• Langue: English
• Poids de l'ouvrage: 18 Mo

Extrait

The correct bibliographic citation for this manual is as follows: Qi, Yue, Kevin D. Smith, and Xiangxiang Meng. 2018. SAS Viya : The R Perspective . Cary, NC: SAS Institute Inc.
SAS Viya : The R Perspective
Copyright 2018, SAS Institute Inc., Cary, NC, USA
ISBN 978-1-63526-704-4 (Hard copy)
ISBN 978-1-63526-701-3 (EPUB)
ISBN 978-1-63526-702-0 (MOBI)
ISBN 978-1-63526-703-7 (PDF)
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Contents

About This Book
About These Authors

Chapter 1: Installing R, SAS SWAT, and CAS
Introduction
Installing R
Installing SAS SWAT
Installing CAS
Making Your First Connection
Conclusion
Chapter 2: The Ten-Minute Guide to Using CAS from R
Loading SWAT and Getting Connected
Running CAS Actions
Loading Data
Executing Actions on CAS Tables
Data Visualization
Closing the Connection
Conclusion
Chapter 3: The Fundamentals of Using R with CAS
Connecting to CAS
Running CAS Actions
Specifying Action Parameters
CAS Action Results
Working with CAS Action Sets
Details
Getting Help
CAS Session Options
Conclusion
Chapter 4: Managing Your Data in CAS
Overview
Getting Started with Caslibs and CAS Tables
Loading Data into a CAS Table
Displaying Data in a CAS Table
Computing Simple Statistics
Dropping a CAS Table
CAS Data Types
Caslib and CAS Table Visibility
The Active Caslib
Uploading Data Files to CAS Tables
Uploading Data from URLs to CAS Tables
Uploading Data from a data.frame to a CAS Table
Exporting CAS Tables to Other Formats
Managing Caslibs
Creating a Caslib
Setting an Active Caslib
Dropping a Caslib
Conclusion
Chapter 5: First Steps with the CASTable Object
First Steps with the CASTable Object
Creating a CASTable Object
Setting CASTable Parameters
Managing Parameters Using the Attribute Interface
Materializing CASTable Parameters
Conclusion
Chapter 6: Working with CAS Tables
Using CASTable Objects like a Data Frame
CAS Table Introspection
Computing Simple Statistics
Creating Plots from CASTable Data
Sorting, Data Selection, and Iteration
Fetching Data with a Sort Order
Iterating through Columns
Techniques for Indexing and Selecting Data
Data Wrangling on the Fly
Creating Computed Columns
By-Group Processing
Conclusion
Chapter 7: Data Exploration and Summary Statistics
Overview
Summarizing Continuous Variables
Descriptive Statistics
Histograms
Percentiles
Correlations
Summarizing Categorical Variables
Distinct Counts
Frequency
Top K
Cross Tabulations
Variable Transformation and Dimension Reduction
Variable Binning
Variable Imputation
Conclusion
Chapter 8: Modeling Continuous Variables
Overview
Linear Regression
Extensions of Ordinary Linear Regression
Generalized Linear Models
Regression Trees
Conclusion
References
Chapter 9: Modeling Categorical Variables
Overview
Logistic Regression
Decision Trees
Random Forests, Gradient Boosting, and Neural Networks
Random Forests
Gradient Boosting
Neural Networks
Conclusion
References
Chapter 10: Advanced Topics
Overview
Binary versus REST Interfaces
The Binary Interface
The REST Interface
The Pros and Cons of Each Interface
Result Processing Workflows
Connecting to Existing Sessions
Communicating Securely
Conclusion
Index
About This Book

What Does This Book Cover?
This book is an introduction to using the R client on the SAS Viya platform. SAS Viya is a high-performance, fault-tolerant analytics architecture that can be deployed on both public and private cloud infrastructures. Although SAS Viya can be used by various SAS applications, it also enables you to access analytic methods from SAS, R, Python, Lua, and Java, as well as through a REST interface using HTTP or HTTPS. Of course, in this book we focus on the perspective of SAS Viya from R.
SAS Viya consists of multiple components. The central piece of this ecosystem is SAS Cloud Analytic Services (CAS). CAS is the cloud-based server that all clients communicate with to run analytical methods. The R client is used to drive the CAS component directly using objects and constructs that are familiar to R programmers.
We assume that you have some knowledge about R before you approach the topics in this book. We do not assume any knowledge of CAS itself. However, you must have a CAS server that is set up and is running in order to execute the examples in this book.
The chapters in the first part of the book cover topics from the installation of R to the basics of connecting, loading data, and getting simple analyses from CAS. Depending on your familiarity with R, after reading the Ten-Minute Guide to Using CAS from R, you might feel comfortable enough to jump to the chapters later in the book that are dedicated to statistical methods. However, the chapters in the middle of the book cover more detailed information about working with CAS, such as constructing action calls to CAS and processing the results, error handling, managing your data in CAS, and using object interfaces to CAS actions and CAS data tables. Finally, the last chapter about advanced topics covers features and workflows that you might want to take advantage of when you are more experienced with the R client.
This book covers topics that are useful to complete beginners, as well as to experienced CAS users. Its examples extend from creating connections to CAS to simple statistics and machine learning. The book is also useful as a desktop reference.

Is This Book for You?
If you are using the SAS Viya platform in your work and you want to access analytics from SAS Cloud Analytic Services (CAS) using R, then this book is a great starting point. You ll learn about general CAS workflows, as well as the R client that is used to communicate with CAS.

What Are the Prerequisites for This Book?
Some R experience is definitely helpful while reading this book. If you do not know R, there is a multitude of resources on the internet for learning R. The later chapters in the book cover data analysis and modeling topics. Although the examples provide step-by-step code walk-throughs, some training about these topics beforehand is helpful.

What Should You Know about the Examples?
This book includes tutorials for you to follow to gain hands-on experience with SAS.

Software Used to Develop the Book's Content
This book was written using Version 1.3.0 of the SAS Scripting Wrapper for Analytics Transfer (SWAT) package for R. SAS Viya 3.3 was used. Various R resources and packages were used as well. SWAT works with many versions of these packages. The URLs of SWAT and other resources are shown as follows:
SAS Viya www.sas.com/en_us/software/viya.html
SAS Scripting Wrapper for Analytics Transfer (SWAT) - R client to CAS
github.com/sassoftware/R-swat (GitHub repository)

R
https://www.r-project.org/