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Oracle DB on Azure with Multitenant Option

By Franck Pachot

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If you want to run an Oracle Database in the Microsoft Azure cloud, you will install it yourself on a VM. And then, you can expect the same as when you install it in your premises, in a virtual environment. Except that Oracle makes it two times more expensive by accepting to license the processor metric on vCPUs at the condition that the Intel core factor is not applied. And in addition to that there is a weird limitation on multitenant. I create a VM with the 19c image provided by Azure. I’m not sure there’s a big advantage to have this image. You have an Oracle Linux OS, with all prerequisites (which is like having installed the preinstall rpm), and a 19.3 Oracle Home (which is like downloading it, unzip and runInstaller). But you will still have to apply the latest Release Update and create a database.

Migrating Oracle Exadata Workloads to Azure- Storage Indexes

I’m about simplifying anything for customers as we bring over complex environments into Azure and Oracle databases running on Exadata is a big part of these challenges.  Decoupling the database from the engineered features is a crucial part of my work and with Oracle 19c, having customers running on the terminal release isn’t the only reason to upgrade if the database is on an earlier release.

As I’ve discussed in other posts, blogs and articles, I have numerous ways to address latency when losing cell node offloading, hybrid columnar compression (HCC), thin cloning with sparse clone, flash cache, flash logging, etc., but storage indexes are unique to Exadata that simply have no comparable work around.

CockroachDB troubleshooting series… define the process

After working with customers for about 18 months now, I am starting a blog series to write up the common issues seen while running CockroachDB. Diagnosis and treatment of issues when running on distributed database architectures like CockroachDB, closely mirror the process used in the medical community.

There are observed symptoms which leads to a diagnosis and finally a treatment to resolve the condition. Good troubleshooting methodology can help frame the problem which leads to better overall outcomes. This process is outlined below:

Scaling CockroachDB key generation… uuid, serial, and sequences

Overview

Primary keys are critical in any RDBMS in order to ensure the validity of data. Unlike other distributed SQL databases, CockroachDB is not sharded by primary key to distribute the data. Data is divided to ranges and distributed automatically among nodes in the cluster. CockroachDB ranges are sorted by the primary key values. So, while the value doesn’t define the distribution, the sorting of the values can have implications if you use sequences that increment values in a counter-like fashion. This will put stress on a single RANGE of data which scaling of a distributed application.

Azure IO Performance for the RDBMS DBA- Part I

With my upcoming session on “Migrating Oracle Workloads to Azure IaaS” this week at PASS Virtual Summit 2020, I wanted to take some time to dig deeper onto the performance side. The last thing you want to have happen is to migrate your database to the cloud and have it just screech to a halt.

Why a One-Week Report for AWR Sizing in Azure

It’s not uncommon for different recommended practices to arise in technical sizing and optimization practices.  For many, it’s a compromise between most optimal data and ease of access vs. impact on production environments, which is no different from what we face when sizing Oracle on Azure.

Join Performance for UUID, STRING, and INTEGER with CockroachDB

overview

To continue on the UUID performance thread, I was recently asked by a customer how joins perform with various data types. I had not run a specific test, but suspected perform would be driven mostly by the size of the data types.

I wanted to verify my assumptions with real test data that shows the core performance of joins with CockroachDB.

the schema, data, and queries

For this test, two tables were created. The first table had one million rows and the second table had 200k matching primary keys for UUID, STRING, and INTEGER data types.

schema:

create table u1 (id uuid primary key);
create table u2 (id uuid primary key);

create table s1 (id string primary key);
create table s2 (id string primary key);

create table i1 (id integer primary key);
create table i2 (id integer primary key);

data load:

2020 PASS Summit and the Azure SQL Championship

I barely have enough time to breathe let along blog these days, but lucky for me, I am taking some downtime today, so I can come out here and write!

Anyway, since I’m so busy, I volunteered to help judge the Azure SQL Championship that you can be part of!

Ingest format performance with UUID using CockroachDB

Recently, I have been working with customers that have been concerned about the performance of various UUID formats. Other products have various performance characteristics for inserting, generating and presenting UUID data.

For this blog, I ran a quick series of tests using jmeter insert data along with some simple SQL tests to generate UUID values. Hopefully, this will be helpful to better your understanding of UUID with CockroachDB.

UUID formats

Cockroach DB has four different ways data can be formatted for use with the UUID data type.

String format
'63616665-6630-3064-6465-616462656564'

Curly Brace format
'{63616665-6630-3064-6465-616462656564}'

Prepping an Oracle Database for a Cloud Migration

There’s so much I need to get written down these days, but there’s only so many hours in a day and days in a week and I’ve totally failed in this area.  Well, I have a little time right now, so going to try to get something down.  It only took me four times to get this published! </p />
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