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ATP vs ADW – the Autonomous Database lockdown profiles

The Oracle database has always distinguished two types of workloads: transactional (OLTP) and datawarehouse (VLDB, DWH, DSS, BI, analytics). There is the same idea in the managed Oracle Cloud with two autonomous database services.

To show how this is old, here is how they were defined in the Oracle7 Tuning Book:

CaptureOLTPvsDSS

The definition has not changed a lot. But the technology behind DSS/DWH has improved. Now, with In-Memory Column Store, Smart Scan, Result Cache we can even see that indexes, materialized views, star transformation, hints,.. are disabled in the Autonomous Datawarehouse cloud service.

Google Cloud Spanner – inserting data

By Franck Pachot

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In a previous post I’ve created a Google Cloud Spanner database and inserted a few rows from the GUI. This is definitely not a solution fo many rows and here is a post about using the command line.

If I start the Google Shell from the icon on the Spanner page for my project, everything is set. But if I run it from elsewhere, using the https://console.cloud.google.com/cloudshell as I did in A free persistent Google Cloud service with Oracle XE I have to set the project:

franck_pachot@cloudshell:~$ gcloud config set project superb-avatar-210409
Updated property [core/project].

Google Cloud Spanner – no decimal numeric data types

By Franck Pachot

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Google Cloud Spanner is a distributed relational database focused on scalability without compromising consistency and integrity. It is available only as a managed service in Google Cloud. Basically, the idea is to keep the scalability advantages of NoSQL database (like Bigtable) but adding transactions, relational tables, SQL, structured data,… as in the relational databases we love for decades.
The commercial pitch includes all the NoSQL buzzwords, with the addition of the legacy properties of SQL databases:
Cloud Spanner is a fully managed, mission-critical, relational database service that offers transactional consistency at global scale, schemas, SQL (ANSI 2011 with extensions), and automatic, synchronous replication for high availability.
Here I’m testing something that is not mentioned, but is taken for granted with all SQL databases: the ability to add numbers without erroneous arithmetic results.

ADWC new OCI interface

A few things have changed about the Autonomous Data Warehouse Cloud service recently. And I’ve found the communication not so clear, so here is a short post about what I had to do to start the service again. The service has always been on the OCI data centers but was managed with the classic management interface. It has been recently migrated to the new interface:
CaptureADWCnew
Note that ADWC here is the name I’ve given for my service. It seems that the Autonomous Data Warehouse Cloud Service is now referred by the ADW acronym.

demystifying and wrapping the oracle cloud APIs with Python

As an oracle DBA you might have to deal with REST API, especially when working with the cloud. The purpose of this post is to demystify the REST API usage from a DBA point of view. Let’s take an example and write a Python wrapper to automate the Instance creation in the Oracle Database Cloud Service.

The instance creation can be done manually using the Web Interface that way:

Which Bitnami service to choose in the Oracle Cloud Infrastructure?

In the Oracle Cloud PaaS you have a marketplace where you can choose your service. Some are packaged from Bitnami and available on multiple OS. My first idea is that in PaaS you do not care about the OS. But Oracle Cloud has this very nice feature where you still have full access to the OS, as root, even in PaaS. Then, you choose the Linux distribution of your preference. Except if performance is different. They run on different Linux kernels. Is Oracle Linux Unbreakable Kernel more efficient?

We need to compare with relevant and reliable measures. And for that I’ve created a Postgres service and used Kevin Closson SLOB method, as I’m a lucky beta tester for pgio. I’ll post later about the creation of the Postgres service in the Oracle Cloud.

ADWC – connect from your premises

In the previous post about the Autonomous Data Warehouse Service, I’ve run queries though the Machine Learning Notebooks. But you obviously want to connect to it from your premises, with SQL*Net.

CaptureADWCconnect001Of course the connection, going through the public internet, must be secured. If you already use a managed service like the Oracle Exadata Express Cloud Service, you already know how to do: download a .zip containing the connection string and the wallet and certificate for SQL*Net encryption.

SQL Developer Web on the Oracle Cloud

You like SQL Developer because it is easy to install (just unzip a jar) and has a lot of features? Me too. It can be even easier if it is provided as a web application: no installation, and no java to take all my laptop RAM…
When I say no installation, you will see that you have some little things to setup here in DBaaS. That will probably be done for you in the managed services (PDBaaS) such as ‘Express’ and ‘Autonomous’ ones.

CaptureSDW010

ADWC – the hidden gem: Zepplin Notebook

IMG_5339
In the previous blog posts I explained how to create, and stop/start the Autonomous Data Warehouse Cloud service. And I didn’t show yet how to connect to it. It is easy, from sqlplus or SQL Developer, or SQLcl.

But there’s something more exciting to run some SQL queries: the Oracle Machine Learning Notebooks based on Apache Zepplin. At first, I didn’t realize why the administration menu entry to create users in the ADWC service was named ‘Manage Oracle ML Users’, and didn’t realize that the ‘Autonomous Data Warehouse Cloud’ header was replaced by ‘Machine Learning’.

ADWC – a Docker container to start/stop Oracle Cloud services

In the previous post, I’ve explained how to start and stop the Autonomous Data Warehouse Cloud service from PSM (PaaS Service Manager). There’s a setup phase, and a run phase starting with service-start and ending with service-stop. And the setup is specific to an Oracle Cloud account, storing information in the local user home. You may want to run different setups, and even provide an easy way to start/stop an Oracle Cloud service without knowing the user, password and tenant name.

A Docker container is perfect to isolate this.