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November 2020

Oracle 19c: Adventures with Automatic Indexing

The video of this recent presentation, given as a part of the Oracle Groundbreakers EMEA Tour 2020, is now available.

Automatic Indexing is one of the much-heralded features of Oracle 19c, but it is only available on Engineered Systems, therefore in Autonomous Database that is built on Exadata and on other Exadata platforms. This presentation shares some initial experiences with the feature based on testing it in conjunction with Swingbench and discusses how well it performed.

Handling kernel upgrades with Ansible prior to an Oracle installation

As part of the process of setting up VMs in the cloud for use with the Oracle database it is frequently necessary to update the systems to the latest and greatest, and hopefully more secure packages before the Oracle installation can begin. In a similar way I regularly upgrade the (cloud-vendor provided) base image when building a custom image using Packer. This demands for an automated process in my opinion, and Ansible is the right tool for me.

I may have mentioned once or twice that a Spacewalk powered (or equivalent) local repository is best for consistency. You may want to consider using it to ensure all systems are upgraded to the same packages. Applying the same package updates in production as you did in test (after successful regression testing of course) makes testing in lower-tier environments so much more meaningful ;)

Application Express – the PSE update

I published a post a couple of days ago about how due to the architecture of PL/SQL and hence Application Express, we can rapidly deliver and deploy updates to the core APEX product to deliver timely fixes to the APEX community.

Because a single patch may now evolve over time to contain additional fixes, long time friend of the APEX community Peter Raganitsch then made the following observation on Twitter:


Oracle 19c: Real-Time Statistics & High-Frequency Statistics Collection

The video of this recent presentation, given as a part of the Oracle Groundbreakers EMEA Tour 2020, is now available.

Keeping object statistics up to date is critical to Oracle database performance and stability. Both of these features aim to address the challenge of using data that has been significantly updated before the statistics maintenance window has run again. The features are only available on engineered systems, and so certainly are targetted at the autonomous database.

About the oracle database and compiling and linking.

This blogpost is about how the oracle database executable created or changed during installation and patching. I take linux for the examples, because that is the version that I am almost uniquely working with. I think the linux operating is where the vast majority of linux installations are installed on, and therefore an explanation with linux is helpful to most of the people.

The first thing to understand is the oracle executable is a dynamically linked executable. This is easy to see when you execute the ‘ldd’ utility against the oracle executable:

Vagrant & Docker Builds : ORDS and SQLcl 20.3

In a previous post I discussed the recent release of APEX 20.2 and the subsequent builds it triggered. Last night I pulled down ORDS 20.3 and SQLcl 20.3, so I updated my Vagrant and Docker builds again.

Updating my APEX 20.2 installation

One of (or should I say “another of”!) the very cool features of Application Express (APEX) is that by being a database-centric software installation, patching of the product can be done very efficiently and easily by simply loading fresh versions of the underlying PL/SQL source.

The reason loading PL/SQL source is such a good thing is that when you load PL/SQL source that is unchanged the database can simply treat that as a “no-op” which

  • makes loading the unchanged PL/SQL faster,
  • avoids invalidation and recompilation impacts

We can see that with this simple demo.

What’s new with Oracle database versus

This blogpost takes a look at the technical differences between Oracle database PSU 200714 (july 2020) and PSU 201020 (october 2020). This gives technical specialists an idea of the differences, and gives them the ability to assess if the PSU impacts anything.


NoSQL and SQL: key-value access always scale

By Franck Pachot

I have written about some NoSQL myths in previous posts ( and here) and I got some feedback from people mentioning that the test case was on relatively small data. This is true. In order to understand how it works, we need to explain and trace the execution, and that is easier on a small test case. Once the algorithm is understood it is easy to infer how it scales. Then, if readers want to test it on huge data, they can. This may require lot of cloud credits, and I usually don’t feel the need to do this test for a blog post, especially when I include all the code to reproduce it on a larger scale.

FBI or Virtual

This note has has been sitting with the other 800 drafts since some time in May 2019, and started with a comment about following on from “a recent talk on how to engineer indexes properly”. Unfortunately I don’t remember when I wrote it, or why it came about.I mention this only because the note shows you how you can run into irritating limitations when you’re trying to do things properly.

First, a little script to generate some highly skewed data: