When patching an Oracle home, you might run into problems. OPatch might not behave as expected. It is helpful to know where to look for error messages or find additional information to pass on to Oracle Support if you want to log an SR for your problem. So OPatch maintains logs for apply, rollback, and lsinventory operations. The OPatch log files are located in the $ORACLE_HOME/cfgtoollogs/opatch. Each time you run OPatch, a new log file is created, and each log file is tagged with the operation’s timestamp. OPatch maintains an index of processed commands and log files in the opatch_history.txt file – and that is also in the above-mentioned $ORACLE_HOME/cfgtoollogs/opatch directory. So if you change the directory to $ORACLE_HOME/cfgtoollogs/opatch, you’ll see that every time you run OPatch, a log file is created with a date stamp. And then, at the bottom, you’ll see an opatch_history.txt file. look at the file, you’ll see a record of each time you ran the opatch apply, opatch rollback, or lsinventory command. The DBMS_QOPATCH package provides a PL/SQL or a SQL interface to view the installed database patches.

The package returns the patch and patch metadata information available as part of the “opatch lsinventory -xml” command in real-time. So it’s basically a way to see which patches are applied to your database home but from a PL/SQL or a SQL interface. So you basically get an XML-formatted return of your patch information. The DBMS_QOPATCH package allows users to query what patches are installed from SQL*Plus, write wrapper programs to create reports and do validation checks across multiple environments, and also to check patches installed on cluster nodes from a single location. If you log into SQL*Plus as the sys user and then perform select DBMS_QOPATCH.GET_OPATCH_LSINVENTORY from dual. And you’ll see just lots of XML information – which you can use an XML parser to make sense of it.

Oracle Groundbreakers EMEA 2021 
Michigan Oracle Users Summit 2021 

Oracle Machine Learning for R (OML4R) is an R API that makes the open-source R statistical programming language and environment ready for enterprise and big data. Designed for significant data problems, OML4R integrates R with Oracle Database.
R users can run R commands and scripts for statistical and graphical analyses on data stored in the Oracle Database. In addition, they can develop, refine and deploy R scripts that leverage the parallelism and scalability of the database to automate data analysis.

For more information, see: https://docs.oracle.com/en/database/oracle/machine-learning/oml4r/1.5.1/tasks.html

The paper below describes an automated system that generates, selects, verifies, and maintains materialized views in the Oracle RDBMS; it presents a novel technique, called the extended covering subexpression algorithm, for the automated generation of materialized views. An extensive set of experiments is described that demonstrates the feasibility and efficiency of this approach. This system has been fully implemented and will be deployed on the Oracle Autonomous Database on the Cloud.

For more information see https://dl.acm.org/doi/abs/10.14778/3415478.3415533

The following figure illustrates the phases, and the iterative nature, of a machine learning project. The process flow shows that a machine learning project does not stop when a particular solution is deployed. Instead, the results trigger new business questions, which can be used to develop more focused models.

After applying DB RU 19.12.0.0.210720 or DB RUR 19.11.1.0.210720, you may notice that the Block Change Tracking (BCT) file is getting created of a size that is not in line with the database size.
Oracle recommends that you apply interim one-off Patch 33185773 to correct this problem(s) in the RU/RURs indicated above.
Note the fix for this issue has been included in the Oct2021 quarterly RU/RURs.

MV2OCI is a new tool is permitting the load data and migration from “on-premises” to Oracle Cloud Database leveraging on Oracle Data Pump and within one command. Data Pump Import lets you import data from Data Pump files residing on the Oracle Cloud Database node.
For more information see Doc ID 2514026.1.

For all offerings using Oracle Database 19c or later, if you are not licensed for Oracle Multitenant, then you may have up to 3 user-created PDBs in a given container database at any time. For all offerings using Oracle Database 12.1 through 18c, if you are not licensed for Oracle Multitenant, then the container database architecture is available in single-tenant mode, that is, with one user-created PDB, one user-created application root, and one user-created proxy PDB.

EE: Extra cost option; if you are licensed for Oracle Multitenant, then you can create up to 252 PDBs.

ODA and Exa: Extra cost option; if you are licensed for Oracle Multitenant, then you can create up to 4096 PDBs.

ExaCS/CC, DBCS EE-HP, and DBCS EE-EP: Included option; you can create up to 4096 PDBs.