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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
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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
Author Profile Icon Paul R. Johnson
Paul R. Johnson
Derek Mock Derek Mock
Author Profile Icon Derek Mock
Derek Mock
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Table of Contents (21) Chapters Close

Title Page
Copyright and Credits About Packt Contributors Preface 1. The Splunk Interface 2. Understanding Search FREE CHAPTER 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

Summary Indexes and CSV Files

As the number of events retrieved by a query increases, the performance decreases linearly. Summary indexing allows you to calculate the statistics in advance and then run reports against these roll ups, dramatically increasing performance.

In this chapter, we will cover the following topics:

  • Understanding summary indexes
  • When to use a summary index
  • When not to use a summary index
  • Populating summary indexes with saved searches
  • Using summary index events in a query
  • Using sistats, sitop, and sitimechart
  • How latency affects summary queries
  • How and when to backfill summary data
  • Reducing summary index size
  • Calculating top for a large time frame
  • Using CSV files to store transient data
  • Speeding up queries and backfilling
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