Did you ever try to query DBA_EXTENTS on a very large database with LMT tablespaces? I had to, in the past, in order to find which segment a corrupt block belonged to. The information about extent allocation is stored in the datafiles headers, visible though X$KTFBUE, and queries on it can be very expensive. In addition to that, the optimizer tends to start with the segments and get to this X$KTFBUE for each of them. At this time, I had quickly created a view on the internal dictionary tables, forcing to start by X$KTFBUE with materialized CTE, to replace DBA_EXTENTS.

In the previous post I used a simple oci-curl() function as a Command Line Interface to the Oracle Cloud Infrastructure without installing any client tool or language. It was easy for simple things such as starting and stopping services. But it can also be more powerful because it is simply a wrapper to call the OCI REST API, simplifying the sign-in and authentication, but allowing to run any GET, POST, PUT and DELETE method.

In the previous post I've setup all the environment to be able to easily control the OCI services without bothering with the sign-in headers, and without installing anything. In this post I'll used the oci-curl() function to stop all my Autonomous Database services. In the previous post, I've set the environment variables for the private and public key, and the user, tenant and compartment OCIDs.

As you may have read in the news, CERN is testing some Oracle Cloud services. When a large organisation is using the Cloud Credits, there's a need to control the service resources. This requires automation and then the GUI interface from the Cloud portal is not sufficient. We can control the Oracle Cloud Infrastructure through the REST API, OCI CLI, OCI SDKs, and all those methods require a RSA key for sign-in and some OCI (Oracle Cloud Identifier) to identify the user, the tenant, the compartment, the service,...

How do you manage when you need to gather statistics on some tables in a critical environment? Some queries are too long because of stale statistics. But other queries on the same tables are ok. You cannot leave the inital problem without fixing it. Adding hints or SQL Profiles for the identified queries is not the right solution when you identified that stale statistics are the problem. But you want to reduce the risk of regression on other queries at maximum.

Topic: In this short post you can find examples of how to use IPython/Jupyter notebooks for running SQL on Oracle.

Topic: In this post you will find a short discussion and pointers to the code of a few sample scripts that I have written using Linux BPF/bcc and uprobes for

PerfSheet.js is a tool aimed at DBAs and Oracle performance analysts. It provides a simplified interface to extract and visualize AWR time series data in the browser using javascript.

Topic: This blog post is about kernel stack profiling and visualization with flame graphs.