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Home > Data > Operational Intelligence > Implementing Splunk (Update)
Implementing Splunk (Update)
Implementing Splunk (Update)

Implementing Splunk (Update): A comprehensive guide to help you transform Big Data into valuable business insights with Splunk 6.2

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Implementing Splunk (Update)

Chapter 2. Understanding Search

To successfully use Splunk, it is vital that you write effective searches. Using the index efficiently will make your initial discoveries faster, and the reports you create will run faster for you and for others. In this chapter, we will cover the following topics:

  • How to write effective searches
  • How to search using fields
  • Understanding time
  • Saving and sharing searches

Using search terms effectively

The key to creating an effective search is to take advantage of the index. The Splunk index is effectively a huge word index, sliced by time. The single most important factor for the performance of your searches is how many events are pulled from the disk. The following few key points should be committed to memory:

  • Search terms are case insensitive: Searches for error, Error, ERROR, and ErRoR are all the same thing.
  • Search terms are additive: Given the search item, mary error, only events that contain both words will be found. There are Boolean and grouping operators to change this behavior; we will discuss in this chapter under Boolean and grouping operators.
  • Only the time frame specified is queried: This may seem obvious, but it's very different from a database, which would always have a single index across all events in a table. Since each index is sliced into new buckets over time, only the buckets that contain events for the time frame in question...

Boolean and grouping operators

There are a few operators that you can use to refine your searches (note that these operators must be in uppercase to not be considered search terms):

  • AND is implied between terms. For instance, error mary (two words separated by a space) is the same as error AND mary.
  • OR allows you to specify multiple values. For instance, error OR mary means find any event that contains either word.
  • NOT applies to the next term or group. For example, error NOT mary would find events that contain error but do not contain mary.
  • The quote marks ("") identify a phrase. For example, "Out of this world" will find this exact sequence of words. Out of this world would find any event that contains all of these words, but not necessarily in that order.
  • Parentheses ( ( ) ) is used for grouping terms. Parentheses can help avoid confusion in logic. For instance, these two statements are equivalent:
    • bob error OR warn NOT debug
    • bob AND (error OR warn)) AND NOT debug
  • The equal...

Clicking to modify your search

Though you can probably figure it out by just clicking around, it is worth discussing the behavior of the GUI when moving your mouse around and clicking.

  • Clicking on any word or field value will give you the option to Add to search or Exclude from search (the existing search) or (create a) New search:
    Clicking to modify your search
  • Clicking on a word or a field value that is already in the query will give you the option to remove it (from the existing query) or, as above, (create a) new (search):
    Clicking to modify your search

Event segmentation

In previous versions of Splunk, event segmentation was configurable through a setting in the Options dialog. In version 6.2, the options dialog is not present – although segmentation (discussed later in this chapter under field widgets section) is still an important concept, it is not accessible through the web interface/options dialog in this version.

Field widgets

Clicking on values in the Select Fields dialog (the field picker), or in the field value widgets underneath an...

Using fields to search

When we explored the GUI in Chapter 1, The Splunk Interface, you probably noticed fields everywhere. Fields appear in the field picker on the left and under every event. Where fields actually come from is transparent to the user, who simply searches for key=value. We will discuss adding new fields in Chapter 3, Tables, Charts, and Fields, and in Chapter 11, Configuring Splunk.

Using the field picker

The field picker gives us easy access to the fields (currently defined) for the results of our query. Splunk will extract some fields from event data without your help, such as host, source, and sourcetype values, timestamps, and others. Additional fields to be extracted can be defined by you. Clicking on any field presents us with the details about that field in our current search results:

Using the field picker

As we go through the following items in this widget, we see a wealth of information right away:

  • N Value, X% of events is a good indication of whether we are getting the results we think...

Using wildcards efficiently

Though the index is based on words, it is possible to use wildcards when needed, albeit a little carefully. Take a look at some interesting facts about wildcards:

  • Only trailing wildcards are efficient: Stated simply, bob* will find events containing Bobby efficiently, but *by or *ob* will not. The latter cases will scan all events in the time frame specified.
  • Wildcards are tested last: Wildcards are tested after all other terms. Given the search: authclass *ob* hello world, all other terms besides *ob* will be searched first. The more you can limit the results using full words and fields, the better your search will perform.

Supplementing wildcards in fields

Given the following events, a search for world would return both events:

2012-02-07T01:04:31.102-0600 INFO AuthClass Hello world. [user=Bobby, ip=1.2.3.3]
2012-02-07T01:23:34.204-0600 INFO BarClass Goodbye. [user=Bobby, ip=1.2.3.3, message="Out of this world"]

What if you only wanted the second event...

Using search terms effectively

The key to creating an effective search is to take advantage of the index. The Splunk index is effectively a huge word index, sliced by time. The single most important factor for the performance of your searches is how many events are pulled from the disk. The following few key points should be committed to memory:

  • Search terms are case insensitive: Searches for error, Error, ERROR, and ErRoR are all the same thing.

  • Search terms are additive: Given the search item, mary error, only events that contain both words will be found. There are Boolean and grouping operators to change this behavior; we will discuss in this chapter under Boolean and grouping operators.

  • Only the time frame specified is queried: This may seem obvious, but it's very different from a database, which would always have a single index across all events in a table. Since each index is sliced into new buckets over time, only the buckets that contain events for the time frame in question need to...

Boolean and grouping operators

There are a few operators that you can use to refine your searches (note that these operators must be in uppercase to not be considered search terms):

  • AND is implied between terms. For instance, error mary (two words separated by a space) is the same as error AND mary.

  • OR allows you to specify multiple values. For instance, error OR mary means find any event that contains either word.

  • NOT applies to the next term or group. For example, error NOT mary would find events that contain error but do not contain mary.

  • The quote marks ("") identify a phrase. For example, "Out of this world" will find this exact sequence of words. Out of this world would find any event that contains all of these words, but not necessarily in that order.

  • Parentheses ( ( ) ) is used for grouping terms. Parentheses can help avoid confusion in logic. For instance, these two statements are equivalent:

    • bob error OR warn NOT debug

    • bob AND (error OR warn)) AND NOT debug

  • The equal sign (=) is reserved...

Clicking to modify your search

Though you can probably figure it out by just clicking around, it is worth discussing the behavior of the GUI when moving your mouse around and clicking.

  • Clicking on any word or field value will give you the option to Add to search or Exclude from search (the existing search) or (create a) New search:

  • Clicking on a word or a field value that is already in the query will give you the option to remove it (from the existing query) or, as above, (create a) new (search):

Event segmentation

In previous versions of Splunk, event segmentation was configurable through a setting in the Options dialog. In version 6.2, the options dialog is not present – although segmentation (discussed later in this chapter under field widgets section) is still an important concept, it is not accessible through the web interface/options dialog in this version.

Field widgets

Clicking on values in the Select Fields dialog (the field picker), or in the field value widgets underneath an event,...

Using fields to search

When we explored the GUI in Chapter 1, The Splunk Interface, you probably noticed fields everywhere. Fields appear in the field picker on the left and under every event. Where fields actually come from is transparent to the user, who simply searches for key=value. We will discuss adding new fields in Chapter 3, Tables, Charts, and Fields, and in Chapter 11, Configuring Splunk.

Using the field picker

The field picker gives us easy access to the fields (currently defined) for the results of our query. Splunk will extract some fields from event data without your help, such as host, source, and sourcetype values, timestamps, and others. Additional fields to be extracted can be defined by you. Clicking on any field presents us with the details about that field in our current search results:

As we go through the following items in this widget, we see a wealth of information right away:

  • N Value, X% of events is a good indication of whether we are getting the results we think...

Using wildcards efficiently

Though the index is based on words, it is possible to use wildcards when needed, albeit a little carefully. Take a look at some interesting facts about wildcards:

  • Only trailing wildcards are efficient: Stated simply, bob* will find events containing Bobby efficiently, but *by or *ob* will not. The latter cases will scan all events in the time frame specified.

  • Wildcards are tested last: Wildcards are tested after all other terms. Given the search: authclass *ob* hello world, all other terms besides *ob* will be searched first. The more you can limit the results using full words and fields, the better your search will perform.

Supplementing wildcards in fields

Given the following events, a search for world would return both events:

2012-02-07T01:04:31.102-0600 INFO AuthClass Hello world. [user=Bobby, ip=1.2.3.3]
2012-02-07T01:23:34.204-0600 INFO BarClass Goodbye. [user=Bobby, ip=1.2.3.3, message="Out of this world"]

What if you only wanted the second event, but all you...

All about time

Time is an important and confusing topic in Splunk. If you want to skip this section, absorb one concept—time must be parsed properly on the way into the index as it cannot be changed later without indexing the raw data again.

How Splunk parses time

If given the date 11-03-04, how would you interpret this date? Your answer probably depends on where you live. In the United States, you would probably read this as November 3, 2004. In Europe, you would probably read this as March 11, 2004. It would also be reasonable to read this as March 4, 2011.

Luckily, most dates are not this ambiguous, and Splunk makes a good effort to find and extract them, but it is absolutely worth the trouble to give Splunk a little help by configuring the time format. We'll discuss the relevant configurations in Chapter 11, Configuring Splunk.

How Splunk stores time

Once the date is parsed, the date stored in Splunk is always stored as GMT epoch. Epoch time is the number of seconds since January 1, 1970...

Making searches faster

We have talked about using the index to make searches faster. When starting a new investigation, the following few steps will help you get results faster:

  1. Set the time to the minimum time that you believe will be required to locate relevant events. For a chatty log, this may be as little as a minute. If you don't know when the events occurred, you might search a larger time frame and then zoom in by clicking on the timeline while the search is running.

  2. Specify the index if you have multiple indexes. It's good to get into the habit of starting your queries with the index name. For example, index=myapplicationindex error bob.

  3. Specify other fields that are relevant. The most common fields to specify are sourcetype and host. For example, index=myapplicationindex sourcetype="impl_splunk_gen" error bob. If you find yourself specifying the field source on a regular basis, you could probably benefit from defining more source types. Avoid using the sourcetype field to capture...

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Description

If you are a data analyst with basic knowledge of Big Data analysis but no knowledge of Splunk, then this book will help you get started with Splunk. The book assumes that you have access to a copy of Splunk, ideally not in production, and many examples also assume you have administrator rights.

Who is this book for?

If you are a data analyst with basic knowledge of Big Data analysis but no knowledge of Splunk, then this book will help you get started with Splunk. The book assumes that you have access to a copy of Splunk, ideally not in production, and many examples also assume you have administrator rights.

What you will learn

  • Enrich your data with lookups and commands
  • Transform your data into useful and beautiful reports
  • Build professionallooking, informative dashboards
  • Get to know what Splunk data models and pivots are
  • Learn about pivot editor, pivot elements, filters, Sparklines, and more
  • Manage configurations from one to thousands of instances
  • Extend Splunk with scripts and advanced configuration
  • Create fields from your unstructured data
  • Write searches that are fast and lean

Product Details

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Publication date : Jul 28, 2015
Length: 506 pages
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Category :
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Concepts :
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Tools :
Splunk

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Table of Contents

14 Chapters
1. The Splunk Interface Chevron down icon Chevron up icon
1. The Splunk Interface
Logging into Splunk
The home app
The top bar
The search & reporting app
Using the time picker
Using the field picker
The settings section
Summary
2. Understanding Search Chevron down icon Chevron up icon
2. Understanding Search
Using search terms effectively
Boolean and grouping operators
Clicking to modify your search
Using fields to search
Using wildcards efficiently
All about time
Making searches faster
Sharing results with others
Search job settings
Saving searches for reuse
Creating alerts from searches
Summary
3. Tables, Charts, and Fields Chevron down icon Chevron up icon
3. Tables, Charts, and Fields
About the pipe symbol
Using top to show common field values
Using stats to aggregate values
Using chart to turn data
Using timechart to show values over time
Working with fields
Summary
4. Data Models and Pivots Chevron down icon Chevron up icon
4. Data Models and Pivots
What is a data model?
What does a data model search?
Creating a data model
Lookup attributes
What is a pivot?
A quick example
Sparklines
Summary
5. Simple XML Dashboards Chevron down icon Chevron up icon
5. Simple XML Dashboards
The purpose of dashboards
Using wizards to build dashboards
Converting the panel to a report
Back to the dashboard
Editing XML directly
UI examples app
Building forms
Features replaced
Autorun dashboard
Scheduling the generation of dashboards
Summary
6. Advanced Search Examples Chevron down icon Chevron up icon
6. Advanced Search Examples
Using subsearches to find loosely related events
Using transaction
Determining concurrency
Calculating events per slice of time
Rebuilding top
Acceleration
Summary
7. Extending Search Chevron down icon Chevron up icon
7. Extending Search
Using tags to simplify search
Using event types to categorize results
Using lookups to enrich data
Using macros to reuse logic
Creating workflow actions
Using external commands
Summary
8. Working with Apps Chevron down icon Chevron up icon
8. Working with Apps
Defining an app
Included apps
Installing apps
Building your first app
Editing navigation
Customizing the appearance of your app
Object permissions
The app directory structure
Summary
9. Building Advanced Dashboards Chevron down icon Chevron up icon
9. Building Advanced Dashboards
Reasons for working with advanced XML
Reasons for not working with advanced XML
The development process
The advanced XML structure
Converting simple XML to advanced XML
Module logic flow
Understanding layoutPanel
Reusing a query
Using intentions
Creating a custom drilldown
Third-party add-ons
10. Summary Indexes and CSV Files Chevron down icon Chevron up icon
10. Summary Indexes and CSV Files
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
Summary
11. Configuring Splunk Chevron down icon Chevron up icon
11. Configuring Splunk
Locating Splunk configuration files
The structure of a Splunk configuration file
The configuration merging logic
An overview of Splunk .conf files
User interface resources
Summary
12. Advanced Deployments Chevron down icon Chevron up icon
12. Advanced Deployments
Planning your installation
Splunk instance types
Common data sources
Sizing indexers
Planning redundancy
Working with multiple indexes
Deploying the Splunk binary
Using apps to organize configuration
Configuration distribution
Using LDAP for authentication
Using Single Sign On
Load balancers and Splunk
Multiple search heads
Summary
13. Extending Splunk Chevron down icon Chevron up icon
13. Extending Splunk
Writing a scripted input to gather data
Using Splunk from the command line
Querying Splunk via REST
Writing commands
Writing a scripted lookup to enrich data
Writing an event renderer
Writing a scripted alert action to process results
Hunk
Summary
Index Chevron down icon Chevron up icon
Index

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Customer reviews

Rating distribution
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Ed P Aug 20, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
This massive volume (clocking in at over 450 pages!) is easily one of the better IT books I've read in the past few years. Although its called Implementing Splunk it DOES NOT cover installing the software. Check the documentation for that. What it does cover is getting started with using the software, and working towards more in-depth scenarios and configurations so you can handle a wider variety of data, with better dashboards and visualizations. I think one of the best parts of this book is the number of screenshots with clearly marked emphasis on the areas that the author is referring to in the text. That in itself makes following the text much easier, since you aren't hunting around trying to find the setting, menu or piece of information, but you can immediately see it. Need touch!
Amazon Verified review Amazon
Ishaan Shekhar Aug 10, 2015
Full star icon Full star icon Full star icon Full star icon Full star icon 5
Very nice book! Much better than the first edition. Good for beginners and medium-pros.
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Gary Jun 10, 2017
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Good starter book
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SM Lawson Aug 19, 2015
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First and foremost let me say I enjoyed the first book and was very excited to purchase this book on theexpectations that this would surpass it. I was not disappointed the book delves into the extensive concepts ofBig Data and intelligence gathering concepts used in the real world, that said I have one extensive criticism and thatwould be the instructions given on setting up the tutorial data. The Event generator is not really windows friendly and instructionsare not quite clear on setting it up... the instructions given do not work within windows as given and I suppose were only tested in a Linuxenvironment. It would help immensely if the Writers could address this issue with a solution for windows installs concerning the event generator propagated by Splunk making sure step by step instructions are given to make the data work with Splunk. Much easier to work with examples in book.
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About the authors

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Profile icon VINCENT BUMGARNER
VINCENT BUMGARNER
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Vincent Bumgarner has been designing software for over 20 years, working with many languages on nearly as many platforms. He started using Splunk in 2007 and has enjoyed watching the product evolve over the years. While working for Splunk, he has helped many companies train dozens of users to drive, extend, and administer this extremely flexible product. At least one person in every company he has worked with has asked for a book, and he hopes that this book will help fill their shelves.
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Profile icon James D. Miller
James D. Miller
James D. Miller is an IBM certified expert, Master Consultant, Application/System Architect with +35 years of applications & system design/development experience across multiple platforms, technologies and data formats, including Big Data. His experience includes IBM Planning Analytics, BI, Web architecture & design, systems analysis, GUI design & testing, Data modeling, design, and development of OLAP, Client/Server, Web & Mainframe applications and systems utilizing: Planning Analytics Workspace (PAW), IBM Watson Analytics, Cognos BI & TM1, Framework Manager, dynaSight/ArcPlan, ASP, DHTML, XML, MS Visual Basic, VBA, PERL, R, SPLUNK, MS SQL Server, ORACLE, etc. He has authored numerous books, including Implementing Splunk - Second Edition; Mastering Splunk; Hands-On Machine Learning with IBM Watson; IBM Watson Projects; Statistics for Data Science; Mastering Predictive Analytics with R - Second Edition and others. Project areas include those with Data Analytics, Planning Analytics, and FOPM projects, holding various roles from architect, developer, technical and project leader.
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