All Apps and Add-ons

How to predict from time series values for Multiple fields? (Machine Learning Toolkit)

x213217
Explorer
index=deg host=host sourcetype=source source=logpath Name=* Pages=* Schema=* 
| eval SizeInMB = ((Pages * 4 * 1024)/1048576)
| eval Maximum = max(SizeInMB)
| sort -Maximum
| where Maximum > 25000
| timechart span=1hr max(Maximum) by Name
| rename Maximum as "MBSize"
| Predict Name 1

This is my search query that produces a time series of data points (every hour) for Megabyte Size of around 10 tables names.

Name 1 Name 2 Name 3 Name 4 ...
01:00 MBsize MBsize MBsize MBsize
02:00 MBsize MBsize MBsize MBsize
03:00 MBsize MBsize MBsize MBsize
04:00 MBsize MBsize MBsize MBsize
...

My Question is...How do I predict the MBsize for lets say 2 months in the future for each table name based on the gathered previous data points for each table?

I understand how this can be done forecasted for 1 Table Name by specifying | Predict Name 1 Name 2 Name 3 etc.. but I don't know how to pass in all the table names in as a list to handle predicting Multiple tables names based on their past data points.
I cannot hardcode the Name 1 Name 2 Name 3...etc because they may be different based on the table names i retrieve through the search.

0 Karma
Get Updates on the Splunk Community!

Strengthen Your Future: A Look Back at Splunk 10 Innovations and .conf25 Highlights!

The Big One: Splunk 10 is Here!  The moment many of you have been waiting for has arrived! We are thrilled to ...

Now Offering the AI Assistant Usage Dashboard in Cloud Monitoring Console

Today, we’re excited to announce the release of a brand new AI assistant usage dashboard in Cloud Monitoring ...

Stay Connected: Your Guide to October Tech Talks, Office Hours, and Webinars!

What are Community Office Hours? Community Office Hours is an interactive 60-minute Zoom series where ...