Book Image

Improving Your Splunk Skills

By : James D. Miller, Paul R. Johnson, Josh Diakun, Derek Mock
Book Image

Improving Your Splunk Skills

By: James D. Miller, Paul R. Johnson, Josh Diakun, Derek Mock

Overview of this book

Splunk makes it easy for you to take control of your data and drive your business with the cutting edge of operational intelligence and business analytics. Through this Learning Path, you'll implement new services and utilize them to quickly and efficiently process machine-generated big data. You'll begin with an introduction to the new features, improvements, and offerings of Splunk 7. You'll learn to efficiently use wildcards and modify your search to make it faster. You'll learn how to enhance your applications by using XML dashboards and configuring and extending Splunk. You'll also find step-by-step demonstrations that'll walk you through building an operational intelligence application. As you progress, you'll explore data models and pivots to extend your intelligence capabilities. By the end of this Learning Path, you'll have the skills and confidence to implement various Splunk services in your projects. This Learning Path includes content from the following Packt products: Implementing Splunk 7 - Third Edition by James Miller Splunk Operational Intelligence Cookbook - Third Edition by Paul R Johnson, Josh Diakun, et al
Table of Contents (21 chapters)
Title Page

Backfilling the number of purchases by city

In the previous recipe, you generated an hourly summary and then, after waiting for 24 hours, you were able to report on the summary data over a 24-hour period. However, what if you wanted to report over the past 30 days or even 3 months? You would have to wait a long time for your summary data to build up over time. A better way is to backfill the summary data over an earlier time period, assuming you have raw data for this time period in Splunk.

In this recipe, you will create a search that identifies the number of purchases by city on a given day, and write this search to a summary index. You will leverage the IP location database built into Splunk to obtain the city based on the IP address in the results. You will then execute a script that comes bundled with Splunk in order to backfill the summary for the previous 30 days. Following...