In Using the MOJO Scoring Pipeline section, clarify that MOJO Scoring Pipelines are from Driverless AI license

[exalate-issue-sync]

[Mojo Scoring Docs|http://h2o-release.s3.amazonaws.com/sparkling-water/spark-2.4/3.28.0.1-1-2.4/doc/deployment/scoring_mojo_pipeline.html#preparing-your-environment] shows the need for Driverless AI. But it is not clear that MOJO Scoring Pipelines are only from DAI (since H2O OS can produce MOJOs as well).

h3. +Suggested corrections:+

h3. Using the MOJO Scoring Pipeline ({color:#ff991f}from Driverless AI{color}) with Spark/Sparkling Water

MOJO scoring pipeline{color:#ff991f}, created in Driverless AI,{color} artifacts can be used in Spark to carry out predictions in parallel using the Sparkling Water API. This section shows how to load and run predictions on the MOJO scoring pipeline in Spark using Scala and the Python API.

…

h2. Preparing Your Environment

In order {color:#ff991f}to{color}{color:#ff991f} (<- typo fix needed){color} use the MOJO scoring pipeline, Driverless AI license has to be passed to Spark. This can be achieved via {{--jars}} argument of the Spark launcher scripts.

Note: In Local Spark mode, please use {{--driver-class-path}} to specify path to the license file.

[DinukaH2O]

JIRA Issue Migration Info

Jira Issue: SW-2122
Assignee: Jakub Hava
Reporter: Neema Mashayekhi
State: Resolved
Fix Version: 3.28.1.3-1
Attachments: N/A
Development PRs: Available

Linked PRs from JIRA

#1993

[hasithjp]

JIRA Issue Migration Info Cont'd

Jira Issue Created Date: 2020-03-25T16:44:29.805-0700