Improving instance recovery performance

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You query V$INSTANCE_RECOVERY view and consistently receive an OPTIMAL_LOGFILE_SIZE value that is greater than the size of your smallest online redo log file. The OPTIMAL_LOGFILE_SIZE column of the V$INSTANCE_RECOVERY view can be used to determine the appropriate size for all of the online redo log files in your database. If the value of the OPTIMAL_LOGFILE_SIZE column is greater than the size of your smallest online redo log file, you should change the size of all online redo log files to be at least this value. In addition, the FAST_START_MTTR_TARGET initialization parameter simplifies the configuration of recovery time from instance or system failure. After adjusting the size of your online redo log files, you may be able to adjust the value of this initialization parameter for better performance. This is done by rerunning the MTTR advisor after changing the size of your online redo log file to achieve more optimal results. However, running the MTTR advisor is not the best option in this situation for improving instance recovery performance.

 

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How to create a container database (CDB) resource plan

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You use the DBMS_RESOURCE_MANAGER package to create a CDB resource plan and define the directives for the plan. Then, from the root container of your CDB connects as the SYS user. Then, create a pending area using the CREATE_PENDING_AREA procedure. After the pending area has been completed, you use the CREATE_CDB_PLAN procedure to create the CDB resource plan. Next, create the CDB resource plan directives for the PDBs using the CREATE_CDB_PLAN_DIRECTIVE procedure. Each directive specifies how resources are allocated to a specific PDB. Finally, you validate the pending area and then submit it. This is done using the VALIDATE_PENDING_AREA and SUBMIT_PENDING_AREA procedures, respectively.

 

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Multi-process Multi-thread

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Starting in Oracle Database 12c, the multithreaded Oracle model enables specific Oracle processes to execute as operating system threads in separate address spaces. Setting up an Oracle database instance for using multi-process multi-thread architecture is done by starting up the Oracle database instance with the THREADED_EXECUTION initialization parameter set to TRUE.

The multi-process multi-thread model requires a password file for SYSDBA authentication while starting the database instance. Without using the SYS password

an  ORA-1031: insufficient privileges error will be triggered on startup.

When the THREADED_EXECUTION parameter is set to TRUE, you must set the DEDICATED_THROUGH_BROKER_LISTENER parameter to ON in your listener.ora file.

When that parameter is set, the listener knows that it should not spawn an OS process when a connect request is received; instead, it passes the request to the database so that a database thread is spawned and answers the connection.

 

 

 

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Current State and Updates for Oracle Database 01/2022

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Today, 18th January 2022, The Database patch bundles were released.
All the details on MOS in Doc ID 19202201.9 and Doc ID 21202201.9 are recommended to be installed on production systems.

 

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Oracle 19c Tips & Techniques

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In 19c or higher, it is no longer necessary to enable ‘Shared Servers’ on the catalog database, so Oracle recommends that (if you are using Oracle Native Encryption with sharding) you disable Shared Servers on the catalog database. This can be done by setting the database parameter shared_servers to “0” and restarting Oracle. Note that this is a global parameter set in the Container Database.

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My lectures in 2021

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Oracle Groundbreakers EMEA 2021
Michigan Oracle Users Summit 2021 –
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OML4R

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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

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GIPCD Trace Files Grows Too Fast

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There have been a few issues related to the grid inter-process communication(GIPC) daemon. Since this lets redundant interconnect usage, it would produce many networks interconnect messages. Previously, I carried out a cyclic cleanup of the ‘gipcd’ related trace/logs. You can purge these huge trace files if your Clusterware is well and has no issues. If required, you can keep the recent history and purge the rest. In addition, see Doc ID 25776294.8.

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Oracle Sharding on Oracle Container Engine for Kubernetes

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Oracle Sharding on Oracle Container Engine for Kubernetes (OKE) uses StatefulSet to provide stable, unique network identifiers and stable, persistent storage so you can create and manage your Oracle Sharding replica set natively in OKE with Oracle supported helm and chart templates. In addition, data is stored on persistent volume, so all the data is still there when a pod is recreated.
Related Resources:
Oracle Sharding on Docker GitHub Link: https://lnkd.in/dN2VUSXd
Oracle Sharding on OKE GitHub Link:  https://lnkd.in/du2gfxG6
OCR (Oracle Container Registry) Link: https://lnkd.in/dTebi76i

 

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Automated Generation of Materialized Views

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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

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