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Improving Your Splunk Skills

You're reading from   Improving Your Splunk Skills Leverage the operational intelligence capabilities of Splunk to unlock new hidden business insights

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Product type Course
Published in Aug 2019
Publisher Packt
ISBN-13 9781838981747
Length 680 pages
Edition 1st Edition
Languages
Tools
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Authors (4):
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James D. Miller James D. Miller
Author Profile Icon James D. Miller
James D. Miller
Josh Diakun Josh Diakun
Author Profile Icon Josh Diakun
Josh Diakun
Paul R. Johnson Paul R. Johnson
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Paul R. Johnson
Derek Mock Derek Mock
Author Profile Icon Derek Mock
Derek Mock
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Toc

Table of Contents (21) Chapters Close

Title Page
Copyright and Credits About Packt Contributors Preface 1. The Splunk Interface FREE CHAPTER 2. Understanding Search 3. Tables, Charts, and Fields 4. Data Models and Pivots 5. Simple XML Dashboards 6. Extending Search 7. Working with Apps 8. Building Advanced Dashboards 9. Summary Indexes and CSV Files 10. Configuring Splunk 11. Play Time – Getting Data In 12. Building an Operational Intelligence Application 13. Diving Deeper – Advanced Searching, Machine Learning and Predictive Analytics 14. Speeding Up Intelligence – Data Summarization 15. Above and Beyond – Customization, Web Framework, HTTP Event Collector, REST API, and SDKs 1. Other Books You May Enjoy

When to use a summary index

When the question you want to answer requires looking at all or most events for a given source type, the number of events can become huge very quickly. This is what is generally referred to as a dense search.

For example, if you want to know how many page views happened on your website, the query to answer this question must inspect every event. Since each query uses a processor, we are essentially timing how fast our disk can retrieve the raw data and how fast a single processor can decompress that data. Doing a little math, we get the following:

1,000,000 hits per day /

10,000 events processed per second =

100 seconds

If we use multiple indexers, or possibly buy much faster disks, we can cut this time, but only linearly. For instance, if the data is evenly split across four indexers, without changing disks, this query will take roughly 25 seconds.

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