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

Description

Mojo Scoring Docs 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).

Suggested corrections:

Using the MOJO Scoring Pipeline (from Driverless AI) with Spark/Sparkling Water

MOJO scoring pipeline, created in Driverless AI, 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.

Preparing Your Environment

In order to (<- typo fix needed) 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.

Assignee

Jakub Hava

Reporter

neema.mashayekhi

Labels

None

CustomerVisible

No

testcase 1

None

testcase 2

None

testcase 3

None

h2ostream link

None

Affected Spark version

None

AffectedContact

None

AffectedCustomers

None

AffectedPilots

None

AffectedOpenSource

None

Support Assessment

None

Customer Request Type

None

Support ticket URL

None

End date

None

Baseline start date

None

Baseline end date

None

Task progress

None

Task mode

None

Fix versions

Priority

Major
Configure