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Advanced Splunk

You're reading from  Advanced Splunk

Product type Book
Published in Jun 2016
Publisher
ISBN-13 9781785884351
Pages 348 pages
Edition 1st Edition
Languages
Author (1):
Ashish Kumar Tulsiram Yadav Ashish Kumar Tulsiram Yadav
Profile icon Ashish Kumar Tulsiram Yadav

Table of Contents (20) Chapters

Advanced Splunk
Credits
About the Author
Acknowledgements
About the Reviewer
www.PacktPub.com
Preface
1. What's New in Splunk 6.3? 2. Developing an Application on Splunk 3. On-boarding Data in Splunk 4. Data Analytics 5. Advanced Data Analytics 6. Visualization 7. Advanced Visualization 8. Dashboard Customization 9. Advanced Dashboard Customization 10. Tweaking Splunk 11. Enterprise Integration with Splunk 12. What Next? Splunk 6.4 Index

Splunk with R for analytics


We now have enough knowledge of Splunk's features and analytical capabilities; let's look at R and its capabilities. R is a statistically and graphically supported programming language for data analysis and data mining. R has extensive library support for statistical computing (linear/nonlinear modeling, clustering, classification, time series analysis, graphical plotting, predicting, forecasting, data mining, and so on).

Splunk, being a big data tool, can be integrated with R to leverage its advanced analytical capabilities for real-time insights. The Splunk app store had an app called R Project, but it is no longer available on the app store. The R Project app for Splunk can now be downloaded from GitHub (https://github.com/rfsp/r/).

The app can be installed on a Splunk instance like any other app downloaded from the Splunk app store. This app on Splunk exposes a new search command—r, which allows us to pass data from Splunk to the R-Engine for calculation and...

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