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October 2020

Video : Vagrant Oracle Real Application Clusters (RAC) Build

In today’s video we’ll discuss how to build a 2-node RAC setup using Vagrant.

This video is based on the OL8 19c RAC build, but it’s similar to that of the OL7 19c RAC build also. If you don’t have access to the patches from MOS, stick with the OL7 build, as it will work with the 19.3 base release. The GitHub repos are listed here.

If you need some more words to read, you can find descriptions of the builds here, as well as a beginners guide to Vagrant.

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.

Automattic Awarded Coveted Spot on Forbes Cloud 100 List

Automattic — a leader in publishing and e-commerce software and the parent company behind the industry-leading brands WordPress.com, WooCommerce, WordPress VIP, Jetpack, Tumblr, and more — was awarded a coveted spot on the prestigious Forbes Cloud 100 list, the annual ranking of the world’s top private cloud companies. In partnership with Bessemer Venture Partners and Salesforce Ventures, the Forbes Cloud 100 recognizes standouts in tech’s hottest categories from disruptive startups to internet giants.

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:

Oracle 19c Automatic Indexing: Indexing Partitioned Tables Part I (Conversation Piece)

In this little series, I’m going to discuss how Automatic Indexing works in relation to Partitioning. I’ve discussed Indexing and Partitioning many times previously and how Oracle has various options when indexing a partitioned table: Non-Partitioned Index Globally Partitioned Index Locally Partitioned Index So the question(s) are how does Automatic Indexing handle scenarios with partitioned […]

A New Way to Publish Your Blog Posts Simultaneously as Twitter Threads

Publishing WordPress content on Twitter just got a whole lot easier. You can already bring single Tweets or threads, also known as Tweetstorms, over from Twitter to WordPress, and now we’re bringing the process full circle. With just two extra clicks, you can transform your entire blog post into a Twitter thread. By publishing your quality content on Twitter, you can open new lines of engagement and conversation.

The weirdest reason to avoid SELECT *

A quick Google or Bing search and you’ll find no limit to the number of articles on databases that tell you that using “SELECT *” is a terrible terrible thing to do. Your code will be more fragile.  It is bad for your data dictionary.  You’ll end up with conflicts when you join, the list goes on. You can find a more reasoned argument from Markus Winand but ultimately for the majority of the time, the potential drawbacks outweigh any convenience benefits of using SELECT *.

Video : Temporal Validity in Oracle Database 12c Onward

In today’s video we discuss how Temporal Validity can make querying of effective date ranges simpler in Oracle 12c and beyond.

The video is based on this article.

The syntax looks similar to Flashback Query and Flashback Version Query.

Interval Oddity

Interval partitioning is a popular strategy for partitioning date-based data. It’s an enhanced variant of range partitioning that allows you to define a starting partition and an interval that should be used to derive the high values for all subsequent partitions – and Oracle doesn’t even have to create intervening partitions if you insert data that goes far beyond the current partition, it automatically creates exactly the right partition (with the correct high_value and correctly inferred lower boundary) for the incoming data and behaves as if the intervening partitions will become available when they’re needed at some later point in time.