1. Using Oracle Machine Learning on Autonomous Database
  2. Administer Oracle Machine Learning

8 Administer Oracle Machine Learning

Oracle Machine Learning is managed at the system level and at the application level by an administrator.

  • Administrator — Creates, edits, and deletes Oracle Machine Learning user accounts. The Administrator reassigns user workspace.

    Note:

    The Administrator is not authorized to run notebooks. The Administrator can only read notebooks.

    Figure 8-1 Admin Home page

    Admin_Home page
  • Developer — This is the default user role that allows you to create and run notebooks, run SQL Statements, create SQL scripts, run Python scripts, create jobs to schedule and run notebooks, create and run AutoML experiments, and deploy models.

    Figure 8-2 Developer Home page

    Developer Home page
  • Typical Workflow for Managing Oracle Machine Learning
    To manage Oracle Machine Learning and other administrative tasks, refer to the tasks listed in the table as a guide.
  • Manage OML Users
    An administrator manages new user account and user credentials creation for Oracle Machine Learning in the User Management interface.
  • About User Data
    In the User Data page in Oracle Machine Learning, you can view existing user data, reassign, and delete it.
  • About Compute Resource
    The term Compute Resource refers to services such as a database, or any other backend service to which an interpreter connects.

Typical Workflow for Managing Oracle Machine Learning

To manage Oracle Machine Learning and other administrative tasks, refer to the tasks listed in the table as a guide.

Tasks Oracle Machine Learning Interface More Information
User account and password creation Oracle Machine Learning User Management interface Create Users for Oracle Machine Learning
Connection Groups — View and Reset Oracle Machine Learning Work with Connection Groups
Compute Resource — View Oracle Machine Learning About Compute Resource
User Data administration — Delete all users, all user related objects such as workspace, projects, and notebooks, and workspace reassignment Oracle Machine Learning About User Data

Note:

The tasks listed here can be performed by an administrator only.

Parent topic: Administer Oracle Machine Learning

Manage OML Users

An administrator manages new user account and user credentials creation for Oracle Machine Learning in the User Management interface.

Parent topic: Administer Oracle Machine Learning

Create User

An administrator creates a new user account and user credentials for Oracle Machine Learning in the User Management interface.

Note:

You must have the administrator role to access the Oracle Machine Learning User Management interface.

To create a user account:

  1. Select an Autonomous Data Warehouse instance and on the details page click Service Console.
  2. On the Service Console click Administration.
  3. Click Manage OML Users to open the Oracle Machine Learning User Administration page.
  4. Click Create on the Oracle Machine Learning User Administration page.
  5. In the Username field, enter a username for the account. Using the username, the user will log in to an Oracle Machine Learning instance.
  6. Enter a name in the First Name field.
  7. Enter a name in the Last Name field.
  8. In the Email Address field, enter the email ID of the user.
  9. Select the option Generate password and email account details to user. User will be required to reset the password on first sign in. to auto generate a temporary password and send an email with the account credentials to the user.
    If you select this option, you need not enter values in the Password and Confirm Password fields; the fields are grayed out.
  10. In the Password field, enter a password for the user, if you choose to create a password for the user.
    This option is disabled if you select the Generate password... option to auto generate a temporary password for the user.
  11. In the Confirm Password field, enter a password to confirm the value that you entered in the Password field.
    By doing so, you create the password for the user. The user can change the password when first logging in.
  12. Click Create.

This creates a new database user and grants the required privileges to use Oracle Machine Learning.

Note:

With a new database user, an administrator needs to issue grant commands on the database to grant table access to the new user for the tables associated with the user's Oracle Machine Learning notebooks.

Parent topic: Manage OML Users

Add Existing Database User Account to Oracle Machine Learning

An administrator adds an existing database user account for Oracle Machine Learning in the User Management interface.

Note:

You must have the administrator role to access the Oracle Machine Learning User Management interface.

To add an existing database user account:

  1. Select an Autonomous Database instance, and on the details page click Service Console.
  2. On the Service Console, click Administration.
  3. Click Manage OML Users to add Oracle Machine Learning users.
  4. Click Show All Users to display the existing database users.

    Description of dwcs_oml_show_all_users.png follows
    Description of the illustration dwcs_oml_show_all_users.png

    Note:

    Initially, the Role field shows the role None for existing database users. After adding a user the role Developer is assigned to the user.
  5. Select a user. To select a user select a name in the User Name column. For example, select ANALYST1.
    Selecting the user shows the Oracle Machine Learning Edit User page.
  6. Enter a name in the First Name field. (Optional)
  7. Enter the last name of the user in the Last Name field. (Optional)
  8. In the Email Address field, enter the email ID of the user.
    Making any change on this page adds the existing database user with the required privileges as a Oracle Machine Learning user.
  9. Click Save.

This grants the required privileges to use the Oracle Machine Learning application. In Oracle Machine Learning this user can then access any tables the user has privileges to access in the database.

Parent topic: Manage OML Users

About User Data

In the User Data page in Oracle Machine Learning, you can view existing user data, reassign, and delete it.

The User Data page lists details of the Oracle Machine Learning user such as the name, role, comments, last updated date. You can perform the following tasks:

  • Delete User Data: To delete a user, select the user to delete and click Delete User Data.

  • Reassign: To reassign workspace and templates from one user to another.

  • Reassign
    The Reassign option allows you to reassign workspaces, along with templates, from one user to another.

Parent topic: Administer Oracle Machine Learning

Reassign

The Reassign option allows you to reassign workspaces, along with templates, from one user to another.

To reassign workspaces:
  1. On the User Data page, select the user from whom you want to reassign workspace and click Reassign.
    The Reassign page opens.
  2. In the Target User field, select the user to whom you want to reassign workspace.
  3. Select All Templates if you want to reassign all the templates associated with the user selected in the User Data page.
  4. Select:
    • Reassign all workspaces: To reassign all the workspaces associated with the selected user.
    • Select workspaces to reassign: To reassign particular workspaces associated with the selected user.
  5. Click Reassign.
After the templates and workspaces are reassigned successfully, a notification message is displayed on the User Data page with the number of templates and workspaces reassigned.

Parent topic: About User Data

About Compute Resource

The term Compute Resource refers to services such as a database, or any other backend service to which an interpreter connects.

Note:

You must have the Administrator role to access the Compute Resources page.

The Compute Resources page displays the list of compute resources along with the name of each resource, its type, comments, and last updated details. To view details of each Compute Resource, click the Compute Resource name. The connection details are displayed in the Oracle Resources page.

  • Oracle Resource
    The Oracle Resource page displays the details of the selected compute resource on the Compute Resources page. You can configure the memory settings (in Gigabytes) for the Python interpreter for the selected compute resource.

Parent topic: Administer Oracle Machine Learning

Oracle Resource

The Oracle Resource page displays the details of the selected compute resource on the Compute Resources page. You can configure the memory settings (in Gigabytes) for the Python interpreter for the selected compute resource.

Note:

You must have Administrator privilege to configure the memory settings.

Figure 8-3 Oracle Resource

Description of Figure 8-3 follows
Description of "Figure 8-3 Oracle Resource"
To manage memory settings for the Python interpreter:
  1. Name: Displays the name of the selected resource.
  2. Comment: Displays comment, if any.
  3. Memory: You can configure memory settings (in Gigabytes) for Python interpreters in this field.
    • For the resource databasename_high, the memory settings (in Gigabytes) must be between 8 and 16
    • For the resource databasename_medium, the memory settings (in Gigabytes) must be between 4 and 8
    • For the resource databasename_low, the memory settings (in Gigabytes) must be between 2 and 4

    Note:

    The Memory setting is applicable only for the Python interpreter.
  4. Connection Type: Displays the database connection of the resource.
  5. Network Alias: Displays the alias of the network connection.

Parent topic: About Compute Resource

Resource Services and Notebooks

This topic lists the number of notebooks that you can run concurrently per PDB for each Resource service.

The Resource Services and Number of Notebooks table lists the Compute Resources assigned for running of Python scripts at different Resource Service levels - High, Medium and Low. The High level is assigned the maximum number of Compute Resources to run the Python script, which could result in faster running of the scripts. The Low level is assigned the least number of Resource Services, which results in slower running of the scripts.

Table 8-1 Resource Services and Number of Notebooks

Resource Service OCPUs (Oracle CPUs) Memory Number of Concurrent Notebooks
High Up to 8 OCPUs 8 GB (up to 16 GB) Up to 3
Medium Up to 4 (OCPUs) 4 GB (up to 8 GB) Up to max (1.25 × number of OCPUs)

Note:

The number of current notebook run is calculated by the formula 1.25 x (number of OCPUs) provisioned for the corresponding PDB. OCPU stands for Oracle CPU.

For example, if a PDB is provisioned with 4 OCPUs, then the maximum number of notebooks run would be 5 (1.25 x 4) in Medium level.
Low 1 2 GB (up to 4 GB) Up to 100

Parent topic: Oracle Resource