How to use Ansible with Oracle Autonomous Database on Dedicated Exadata Infrastructure?

Quick Into: How to use Ansible with Oracle Autonomous Database on Dedicated Exadata Infrastructure?

There is a very good blog post by Jeffrey Cowen Senior Principal Product Manager on How to use Ansible with Oracle Autonomous Database on Dedicated Exadata Infrastructure.

Here is a quick recap.

• Two Ansible files are needed:
• sample.yaml is the main script which will 
• 1. Create a new Autonomous Container Database (ACD).
• 2. Create a new Autonomous Database (ADB) on top of the newly created ACD.
• 3. List ADBs in a compartment filtered by display name.
• 4. Get facts of the ADB that was created earlier.
• 5. Stop/Start the ADB.
• 6. Kick off the cleanup script.
• teardown.yaml is the cleanup script which can be run by itself.

Enjoy this blog post on How to use Ansible with Oracle Autonomous Database on Dedicated Exadata Infrastructure?

Cheers. 

Oracle Database 21c New Feature: Hybrid Scans with In-Memory

Oracle Database 21c New Feature: Hybrid Scans with In-Memory.

This blog post by Andy Rivenes Product Manager at Oracle highlights this exciting new feature in 21c to the already expansive array of features boasted by Oracle Database In-Memory.

Here is a brief summary.

• Columns are excluded from being populated to save space. If one or more columns of a table are never accessed by analytic queries then, there is no point in using the space in the IM column store to populate them.
• In previous versions, the problem with excluding columns was that, you had to make sure that none of the excluded columns were accessed by your analytic queries or else performance for those queries suffered because the object had to be accessed from the row store.
• Now that In-Memory Hybrid Scans are available in 21c, even if the columns of a table have been excluded and are then part of some analytic queries there usually won't be a huge drop off in performance.
• The cost of running the query in the IM column store and then retrieving a large number of column values from the row store may not be any better than just accessing the data in the row store.
• The query will run slower than if all the columns were populated, but in many instances, it will still run much faster than, if the entire table has to be accessed from the row store. 
• If you are only returning a relatively small number of values then the query can run almost as fast as if all the columns were populated. 
• There is a tradeoff but the space savings can be quite dramatic.

Enjoy this blog post announcing this exciting new capability now available for Oracle Database In-Memory.

Cheers.

Step-by-Step: How to migrate from AWS RDS to Oracle Autonomous Database via Data Pump

Step-by-Step: How to migrate from AWS RDS to Oracle Autonomous Database via Data Pump.

There is a very good blog post by SATYABRATA MISHRA Senior Product Manager at Oracle on How to migrate from AWS RDS to Oracle Autonomous Database via Data Pump.

Here is a quick recap of the steps involved.

• Step 1 - Identify the Source Oracle database on AWS RDS.
• Step 2 - Prepare target Autonomous Database on Oracle DB Cloud.
• Step 3 - Validate compatibility using CPAT (Cloud Premigration Advisory Tool).
• Step 4 - Start the export of the source schema.
• Step 5 - Create an Amazon S3 bucket to upload the data pump dump file. 
• Step 6 - Import the data pump dump file from the  Amazon S3 bucket to Oracle Autonomous Database.

Enjoy this blog post on How to migrate from AWS RDS to Oracle Autonomous Database via Data Pump.

Cheers.