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Implementing Splunk: Big Data Reporting and Development for Operational Intelligence

You're reading from  Implementing Splunk: Big Data Reporting and Development for Operational Intelligence

Product type Book
Published in Jan 2013
Publisher Packt
ISBN-13 9781849693288
Pages 448 pages
Edition 1st Edition
Languages
Concepts
Author (1):
VINCENT BUMGARNER VINCENT BUMGARNER
Profile icon VINCENT BUMGARNER

Table of Contents (19) Chapters

Implementing Splunk: Big Data Reporting and Development for Operational Intelligence
Credits
About the Author
About the Reviewers
www.PacktPub.com
Preface
1. The Splunk Interface 2. Understanding Search 3. Tables, Charts, and Fields 4. Simple XML Dashboards 5. Advanced Search Examples 6. Extending Search 7. Working with Apps 8. Building Advanced Dashboards 9. Summary Indexes and CSV Files 10. Configuring Splunk 11. Advanced Deployments 12. Extending Splunk Index

Calculating events per slice of time


There are a number of ways to calculate events per some period of time. All of these techniques rely on rounding _time down to some period of time, and then grouping the results by the rounded "buckets" of _time.

Using timechart

The simplest approach to count events over time is simply to use timechart, like this:

sourcetype=impl_splunk_gen
  | timechart span=1m count

In table view, we see:

Looking at a 24-hour period, we are presented with 1,440 rows, one per minute.

Note

Charts in Splunk do not attempt to show more points than the pixels present on the screen. The user is instead expected to change the number of points to graph, using the bins or span attributes. Calculating average events per minute, per hour shows another way of dealing with this behavior.

If we only wanted to know about minutes that actually had events, instead of every minute of the day, we could use bucket and stats, like this:

sourcetype=impl_splunk_gen
  | bucket span=1m _time
  | stats...
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