Book Image

Implementing Splunk 7, Third Edition - Third Edition

Book Image

Implementing Splunk 7, Third Edition - Third Edition

Overview of this book

Splunk is the leading platform that fosters an efficient methodology and delivers ways to search, monitor, and analyze growing amounts of big data. This book will allow you to implement new services and utilize them to quickly and efficiently process machine-generated big data. We introduce you to all the new features, improvements, and offerings of Splunk 7. We cover the new modules of Splunk: Splunk Cloud and the Machine Learning Toolkit to ease data usage. Furthermore, you will learn to use search terms effectively with Boolean and grouping operators. You will learn not only how to modify your search to make your searches fast but also how to use wildcards efficiently. Later you will learn how to use stats to aggregate values, a chart to turn data, and a time chart to show values over time; you'll also work with fields and chart enhancements and learn how to create a data model with faster data model acceleration. Once this is done, you will learn about XML Dashboards, working with apps, building advanced dashboards, configuring and extending Splunk, advanced deployments, and more. Finally, we teach you how to use the Machine Learning Toolkit and best practices and tips to help you implement Splunk services effectively and efficiently. By the end of this book, you will have learned about the Splunk software as a whole and implemented Splunk services in your tasks at projects
Table of Contents (19 chapters)
Title Page
Packt Upsell
Contributors
Preface
Index

Sparklines


Growing in popularity as a data visualization option, sparklines are inline charts that represent the general shape of a variation (typically over time) in some measurement (such as miles per gallon or home value), in a simple and highly condensed way. Splunk provides you the ability to add sparklines to stats and chart searches, improving their usefulness and overall information density.

Let's look at a simple Splunk search example like the following:

sourcetype=csv "0001" "USD" | chart AVG(Jan) by PERIOD 

It creates the following results table:

As you can see, the preceding example of search generates a table that shows average amounts by the field PERIOD—just two columns.

If you add the keyword sparkline to the search pipeline, you can have Splunk include sparklines with the results:

Note

The sparklines feature is always used in conjunction with chart and stats because it is a function (of those two search commands) and not a command by itself.sourcetype=csv "0001" "USD" | chart sparkline...