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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

Using CSV files to store transient data


Sometimes it is useful to store small amounts of data outside of a Splunk index. Using the inputcsv and outputcsv commands, we can store tabular data in CSV files on the filesystem.

Pre-populating a dropdown

If a dashboard contains a dynamic dropdown, you must use a search to populate the dropdown. As the amount of data increases, the query to populate the dropdown will run more and more slowly, even from a summary index. We can use a CSV file to store just the information needed, simply adding new values when they occur.

First, we build a query to generate the CSV file. This query should be run over as much data as possible:

source="impl_splunk_gen"
  | stats count by user
  | outputcsv user_list.csv

Next, we need a query to run periodically that will append any new entries to the file. Schedule this query to run periodically as a saved search:

source="impl_splunk_gen"
  | stats count by user
  | append [inputcsv user_list.csv]
  | stats sum(count) as count...
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