38.1 Install and Configure a Database for Oracle Machine Learning for SQL
You can install and configure a database for Oracle Machine Learning for SQL by following the listed steps.
38.1.1 About Installation
Oracle Machine Learning for SQL is a component of the Oracle Database Enterprise Edition.
To install Oracle Database, follow the installation instructions for your platform. Choose a Data Warehousing configuration during the installation.
Oracle Data Miner, the graphical user interface to Oracle Machine Learning for SQL, is an extension to Oracle SQL Developer. Instructions for downloading SQL Developer and installing the Data Miner repository are available on the Oracle Technology Network.
To perform machine learning activities, you must be able to log on to the Oracle database, and your user ID must have the database privileges described in Grant Privileges for Oracle Machine Learning for SQL.
Related Topics
See Also:
Install and Upgrade page of the Oracle Database online documentation library for your platform-specific installation instructions: Oracle Database 21c Release
38.1.2 Database Tuning Considerations for Oracle Machine Learning for SQL
Standard administrative practices can be followed to manage workload on the system when machine learning activities are running.
DBAs managing production databases that support Oracle Machine Learning for SQL must follow standard administrative practices as described in Oracle Database Administrator’s Guide.
Building machine learning models and batch scoring of machine learning models tend to put a DSS-like workload on the system. Single-row scoring tends to put an OLTP-like workload on the system.
Database memory management can have a major impact on machine learning. The correct sizing of Program Global Area (PGA) memory is very important for model building, complex queries, and batch scoring. From a machine learning perspective, the System Global Area (SGA) is generally less of a concern. However, the SGA must be sized to accommodate real-time scoring, which loads models into the shared cursor in the SGA. In most cases, you can configure the database to manage memory automatically. To do so, specify the total maximum memory size in the tuning parameter MEMORY_TARGET. With automatic memory management, Oracle Database dynamically exchanges memory between the SGA and the instance PGA as needed to meet processing demands.
Most machine learning algorithms can take advantage of parallel execution when it is enabled in the database. Parameters in INIT.ORA control the behavior of parallel execution.