Copyright © 2014 Splunk Inc.

DATA MODELS

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Search is hard

Analytics Big PictureBuild complex reports without the search language

Provides more meaningful representation of underlying raw machine data

Acceleration technology delivers up to 1000x faster analytics over Splunk 5

4

Pivot

Data Model

Analytics Store

Operational Intelligence Across the Enterprise

IT professionalCreate and share data modelsAccelerate data models and custom searches with the analytics storeCreate reports with pivot

Developer AnalystLeverage data models to abstract dataLeverage pivot in custom apps

Create reports using pivot based on data models created by IT

PivotData Model

Raw Data

AnalyticsStore

[10/11/12 18:57:04 UTC] 000000b0 PolicyService E

Pivot is a query builder.

Demo

Data Models 101

Data set

Source

Source

Source

Sourcetype

Success

Failure

Warning

Data set

Business divisionSource

Source

Business divisionSource

Source

Common model

Technology 1

Technology 2

Technology 3

Context

sourcetype=access_combined source = "/home/ssorkin/banner_access.log.2013.6.gz"

| eval unique=(uid + useragent) | stats dc(unique) by os_name

| rename dc(unique) as "Unique Visitors" os_name as "Operating System"

search and filter | munge | report | clean-up

Splunk Search Language

Hurdles

Simple searches easy… Multi-stage munging/reporting is hard!

Need to understand data’s structure to construct search

Non-technical users may not have data source domain knowledge

Splunk admins do not have end-user search context

index=main source=*/banner_access* uri_path=/js/*/*/login/* guid=* useragent!=*KTXN* useragent!=*GomezAgent* clientip!=206.80.3.67 clientip!=198.144.207.62 clientip!=97.65.63.66 clientip!=175.45.37.78 clientip!=209.119.210.194 clientip!=212.36.37.138 clientip!=204.156.84.0/24 clientip!=216.221.226.0/24 clientip!=207.87.200.162 | rex field=uri_path "/js/(?<t>[^/]*)/(?<v>[^/]*)/login/(?<l>[^/]*)” | eval license = case(l LIKE "prod%" AND t="pro", "enterprise", l LIKE "trial%" AND t="pro", "trial", t="free", "free”) | rex field=v "^(?<vers>\d\.\d)” | bin span=1d _time as day | stats values(vers) as vers min(day) as min_day min(eval(if(vers=="5.0", _time, null()))) as min_day_50 dc(day) as days values(license) as license by guid | eval type = if(match(vers,"4.*"), "upgrade", "not upgrade") + "/" + if(days > 1, "repeat", "not repeat")| search license=enterprise | eval _time = min_day_50| timechart count by type| streamstats sum(*) as *

Data Model GoalsMake it easy to share/reuse domain knowledge

Admins/power users build data models

Non-technical users interact with data via pivot UI

Data Models 101

What is a Data Model?A data model is a search-time mapping of data onto a hierarchical structure

Encapsulate the knowledge needed to build a searchPivot reports are build on top of data modelsData-independent

Screenshot here

A Data Model is a Collection of Objects

Screenshot here

Objects Have Constraints and Attributes

Screenshot here

Child Objects Inherit Constraints and Attributes

Screenshot here

Child Objects Inherit Constraints and Attributes

Building Data Models

Three Root Object TypesEvent

– Maps to Splunk events – Requires constraints

and attributes

Three Root Object TypesEvent

– Maps to Splunk events – Requires constraints

and attributesSearch

– Maps to arbitrary Splunk search (may include generating, transforming and reporting search commands)

– Requires search string attributes• Transaction

– Maps to groups of Splunk events or groups of Splunk search results

– Requires objects to group, fields/ conditions to group by, and attributes

Three Root Object TypesEvent

– Maps to Splunk events – Requires constraints

and attributesSearch

– Maps to arbitrary Splunk search (may include generating, transforming and reporting search commands)

Requires search string attributesTransaction

– Maps to groups of Splunk events or groups of Splunk search results

– Requires objects to group, fields/ conditions to group by, and attributes

Object AttributesAuto-extracted – default and pre-defined fieldsEval expression – a new field based on an expression that you defineLookup – leverage an existing lookup tableRegular expression – extract a new field based on regexGeo IP – add geolocation fields such as latitude, longitude, country, etc.

Object AttributesSet field types

Configure various flagsNote: Child object configuration can differ from parent

Demo

Data Model Builder UI

Best PracticesUse event objects as often as possible

– Benefit from data model acceleration

Resist the urge to use search objects instead of event objects!!– Event based searches can be optimized better

Minimize object hierarchy depth when possible– Constraint based filtering is less efficient deeper down the tree

Event object with deepest tree (and most matching results) first– Model-wide acceleration only for first event object and its descendants

Warnings!Object constraints and attributes cannot contain pipes or subsearches

A transaction object requires at least one event or search object in the data model

Lookups used in attributes must be globally visible (or at least visible to the app using the data model)

No versioning on data models (and objects)!

From Data Models to Reports

Using the UISubhead

Count of http_success events, split by useragent

events

fields

Under the Hood: Object Search String Generation

Syntax:<constraints search> | <my attribute definitions>

Example:sourcetype=access_* OR sourcetype=iis* uri=* uri_path=* status=* clientip=* referer=* useragent=*

Under the Hood: Object Search String Generation

Syntax:<base search> | <my attribute definitions>

Example:_time=* host=* source=* sourcetype=* uri=* status<600 clientip=* referer=* useragent=* (sourcetype=access_* OR source=*.log) | eval userid=clientip | stats first(_time) as earliest, last(_time) as latest, list(uri_path) as uri_list by userid| earliest=* latest=* uri_list=*

Under the Hood: Object Search String Generation

Syntax:<objects to group search> | transaction <group by fields> <group by params> | <my attribute definitions>

Example:sourcetype=access_* uri=* uri_path=* status=* clientip=* referer=* useragent=* | transaction clientip useragent | eval landingpage=mvindex(uri_path,1) | eval exitpage=mvindex(uri_path,-1)

Under the Hood: Object Search String Generation

Syntax:<parent object search> | search <my constraints> | <my attribute definitions>

Example:sourcetype=access_* uri=* uri_path=* status=* clientip=* referer=* useragent=* status=2* | <my attribute definitions>

Using the Splunk Search Language| datamodel <modelname> <objectID> search

Example:| datamodel WebIntelligence HTTP_Request search

Behind the scenes:sourcetype=access_* OR sourcetype=iis* uri=* uri_path=* status=* clientip=* referer=* useragent=*

Under the hood: Pivot Search String GenerationExample:(sourcetype=access_* OR sourcetype=iis*) status=2* uri=* uri_path=* status=* clientip=* referer=* useragent=* | stats count AS "Count of HTTP_Sucess" by ”useragent" | sort limit=0 "useragent" | fields - _span | fields "useragent" "Count of HTTP_Success"| fillnull "Count of HTTP_Success" | fields "useragent" *

Using the Splunk Search Language| pivot <modelname> <objectID> [statsfns, rowsplit, colsplit, filters, …]

Example:| pivot WebIntelligence HTTP_Request count(HTTP_Request) AS "Count of HTTP_Request" SPLITROW status AS "status" SORT 0 status

Behind the scenes:sourcetype=access_* OR sourcetype=iis* uri=* uri_path=* status=* clientip=* referer=* useragent=* | stats count AS "Count of HTTP_Request" by "status" | sort limit=0 "status" | fields - _span | fields "status", "Count of HTTP_Request" | fillnull "Count of HTTP_Request" | fields "status" *

Warnings| datamodel and | pivot are generating commands – They must be at the beginning of the search string

Use objectIDs NOT user-visible object names

DemoBuilding a report from a data

model

Managing Data Models

Data Model on DiskEach data model is a separate JSON file Lives in <myapp>/local/data/models(or <myapp>/default/data/models for pre-installed models)Has associated conf stanzas and metadata

Editing Data Model JSONAt your own risk!

Models edited via the UI are validatedManually edited data models: NOT SUPPORTEDException: installing a new model by adding the file to <myapp>/<local OR default>/data/models is probably okay

Deleting a Data Model

Use the UI for appropriate cleanupPotential for bad state if manually deleting model on disk

Interacting With a Data Model

Use data model builder and pivot UI – safest option!Use REST API – for developers (see docs for details)

Use | datamodel and | pivot Splunk search commands

PermissionsData models have permissions just like other Splunk objectsEdit permissions through the UI

Data Model Acceleration

Run a pivot report

Poll: are there new accelerated

models?

Turn on acceleration via

UISetting written to conf file

Kick off collection

Acceleration

Kick off ad-hoc acceleration and run search

Run search using on-disk acceleration

Admin or power user

Backend magic

Non-technical userNo acceleration

Model-Wide Acceleration

Pivot search: | tstats count AS "Count of HTTP_Success" from datamodel="WebIntelligence" where (nodename="HTTP_Request") (nodename="HTTP_Request.HTTP_Success") prestats=true | stats count AS "Count of HTTP_Success”

Only accelerates first event-based object and descendants

Does not accelerate search and transaction-based objects

Ad-Hoc Object Acceleration

Kick off acceleration on pivot page (re) load for non-accelerated models and search/transaction objects

Amortize cost of ad-hoc acceleration over repeated pivoting on same object

Pivot search:| tstats count AS "Count of HTTP_Success" from sid=1379116434.663 prestats=true | stats count AS "Count of HTTP_Success”

Acceleration DisclaimersWorks with search-head pooling – we collect on indexersCannot edit accelerated models

Thank You