“Seems so good… Hard to believe an end to it.. Warehouse is bare”
Greetings and Salutations..
My odyssey this week didn’t quite have the twists and turns of last week’s pilgrimage. Perhaps, it’s was a bit of hangover from “Holy Week” or just the sheer lassitude from the an over abundance of learning new skills during this time of quarantine?
Last weekend, I finally got a chance to tinker around with Raspberry PI. I managed to get it setup on my Wifi network.. Thanks to finding an HDMI cable to hook up to my 50′ Samsung TV. I also learned how to set VSCode on the Amanda’s Mac and connect via SSH to my PI with out using a password (creating a token instead) which is convenient little trick. In addition, I got to play around with the Sense HAT Python module and made the Raspberry PI display some trippy flashing lights with the on-top LED board add-on.
So after being on Cloud 9 most of the last week, I decided I should stay a little longer in the stratosphere and bang on the Google Cloud Platform or more endearing known as GCP and their Compute Engine. Again, I would rebuild my SQL Server 2016 Always On environment (previously created several weeks back on AWS and last week on Azure). Once again, the goal would be to compare and contrast now all 3 major cloud providers. In effort to avoid redundancy here, I won’t reiterate the same prerequisites taken to build out my SQL farm. However, I will share my observations with GCP
GCP – Compute Engine Issues – Observations:
- More options than Azure but less then AWS – Interface was bit confusing to navigate through
- 1st instance built (Domain Controller) got corrupt whenI upgraded my account from Free to Paid Instance need to be rebuilt
- Windows Domain failed to be created as Administrator account was set to blank (disabled on AWS EC2 and Azure VMs)
- Disks can only be detached from an instance that is an “Stopped” state
Here are my final rankings based on the the 3 Cloud providers I evaluated
1. Best UI: AWS2.
2. Most Features: AWS
3. Easiest to Navigate UI: Azure
4. Most suited for Microsoft workloads (i.e. SQL Server): Azure
5. Most enticing to use it: GCP (free offer)
6. Most potential: GCP
1. Hardest to Navigate UI: GCP
2. Hardest to configure (security): AWS
3. Least amount of features: Azure
So after burning out my fuse up there alone… it was time to touch down and bring me round again.. And that led me back to SQL Server and Columnstore Indexes. Here is what I did:
- Completed Joe Sack’s Pluralsight course: SQL Server 2012: Nonclustered Columnstore Indexes
- Watched Row-based vs. Column-based Indexes Module in Kimberly L. Tripp awesome course in Pluralsight on SQL Server: Indexing for Performance
- Watched Designing Columnstore Indexes for Analytic Queries Module in Gail Shaw’s Designing and Implementing SQL Server Database Indexes
- Downloaded/Restored modified AdventureWorksDW2012
- Created 60 million rows for the Internet Sales Fact table
- Created Columnstore Index and benchmarked performance vs old Row based Index
- Created Table partition for Internet Sales Fact table and designed Partition Switching scenario (workaround used with SQL 2012 and non-clustered CIs) Old Lava Archive database design.
- Started reading through Niko Neugebauer’s awesome blog posts on Columnstore – http://www.nikoport.com/columnstore/ (1- 11)
Below are some topics I am considering for my voyage next week:
- SQL Server Advanced Features:
- Best practices around SQL Server AlwaysOn (Snapshot Isolation/sizing of Tempdb, etc)
- Data Visualization Tools (i.e. Looker)
- ETL Solutions (Stitch, FiveTran)
- Process and Transforming data/Explore data through ML (i.e. Databricks) .
- Getting Started with Kubernetes with an old buddy (Nigel)
Stay safe and Be well