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

How and when to backfill summary data


If you are building reports against summary data, you need enough time represented in your summary index. If your report represents only a day or two, then you can probably just wait for the summary to have enough information. If you need the report to work sooner rather than later, or if the time frame is longer, then you can backfill your summary index.

Using fill_summary_index.py to backfill

The fill_summary_index.py script allows you to backfill the summary index for any time period that you like. It does this by running the saved searches which you have defined to populate your summary indexes, but only for the time periods you specify.

To use the script, follow the given procedure:

  1. Create your scheduled search, as detailed previously in the Populating summary indexes with saved searches section.
  2. Log in to the shell on your Splunk instance. If you are running a distributed environment, log in to the search head.
  3. Change directories to the Splunk bin directory...