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Month: October 2020

Azure Elastic Queries, Jobs, and Transactions

Published 2020-10-22 by Kevin Feasel

Steve Hughes walks us through three Elastic concepts in Azure:

Elastic queries allow developers to interact with data from multiple databases supported on the Azure SQL database platform including Synapse. Elastic queries are often referred to as Polybase which is currently implemented in SQL Server 2019 and Azure Synapse. The key difference is that elastic queries only allow you to interact with other Azure SQL Databases but not Hadoop or other database implementations (e.g. Teradata or Oracle). Part of the confusion comes from the fact that the implementation looks very similar. Both toolsets use external tables in SQL Server to interact with the connected data sources. However, Polybase requires additional components to run whereas elastic queries are ready to go without additional setup.

Read on for more information, including demos.

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Mapping New Column Names with Power Query

Published 2020-10-22 by Kevin Feasel

Soheil Bakhshi reminds me of DB/2:

So, here is my scenario. I received about 10 files, including 15 tables. Some tables are quite small, so I didn’t bother. But some of them are really wide like having between 150 to 208 columns. Nice!

Looking at the column names, they cannot be more difficult to read than they are, and I have multiple tables like that. So I have to rename those columns to something more readable, more on this side of the story later.

Fortunately, there’s a way to fix this; click through for that way.

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Tips for Using Azure Table Storage

Published 2020-10-22 by Kevin Feasel

Adrian Hills takes us through using Azure Table Storage:

Azure Table Storage is a NoSQL key-value PaaS data store that can be a great option for highly scalable, highly available systems. It supports storing petabytes of data and a flexible data schema, meaning different entities in the same table can have different schemas. References to NoSQL databases having “flexible schema” or being “schema-less” can give the impression that database schema design is a thing of the past and that you can bypass it and focus more on the application code. The reality is, even in this NoSQL world, schema design is very important and if you don’t give it due care and attention, then it can come back to bite you.

If you have a RDBMS background and are new to Azure Table Storage, it’s common to find yourself “thinking in SQL” and trying to solve database modeling requirements with a SQL approach before then trying to translate that to a key-value mindset. In this blog post, I’ll cover some of the fundamentals of Azure Table Storage and dive into some common questions you might find yourself asking about Azure Table Storage. Where code samples or references are applicable in this blog post, we’ll be focusing on .NET and using the Azure SDK (specifically relating to the Microsoft.Azure.Cosmos.Table nuget package).

Read on for the full story.

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Importing Perfmon Data Into SQL Server

Published 2020-10-22 by Kevin Feasel

David Klee continues a video series:

If you followed the last video, I showed you how to set up windows perfmon for ongoing performance metric collection on all of your critical SQL Server machines. However, having this raw data in a portable format doesn’t mean you have an easy means to access that data. In this training video, I show you a PowerShell script that we released that helps you export this data into a SQL Server database table so that you have access to the raw data to perform ongoing performance analysis with whatever favorite tool you prefer.

David walks through the process in a video, so check it out.

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Self-Service with Azure Synapse Analytics

Published 2020-10-21 by Kevin Feasel

Paul Andrew lays out an interesting idea:

I’ve been playing around with Azure Synapse Analytics for a while now exploring the preview features and trying to find a meaningful use case for the ‘single pane of glass’ capabilities. In this post I’m exploring one possible option/idea for creating a very simple self service approach to dataset ingestion and consumption. Full disclosure, the below is far from technical perfection for lots of reasons, I mainly wanted to put something out there as an idea and use it to maybe start a conversation.

Click through to see Paul’s take on the matter.

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Choosing the Right Index and Partition in Dedicated SQL Pools

Published 2020-10-21 by Kevin Feasel

Tsuyoshi Matsuzaki gives us some advice on indexing and partitioning data in Azure Synapse Analytics dedicated SQL pools:

Designing index for a table is so primitive and important for better performance.
There’s no “one answer for any case”. You should choose right index for a table depending on the size, usage, query patterns, and cardinality.

In order to help you understand pros/cons in each indexes, I’ll show you each pictures illustrating intuitive structures of indexes available in Synapse Analytics.

Because dedicated SQL pools aren’t the same as the SQL Server box product, it’s important to go in with the understanding that indexing won’t be exactly the same as on-premises or in Azure SQL Database.

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The Raw Facts on Azure SQL DB Serverless

Published 2020-10-21 by Kevin Feasel

Taiob Ali gives us a briefing summary on Azure SQL Database Serverless:

Occasionally, load balancing automatically occurs if the machine cannot satisfy resource demand within a few minutes. For example, if the resource demand is 4 vCores, but only 2 vCores are available, it may take up to a few minutes to load balance before 4 vCores are provided. The database remains online during load balancing except for a brief period at the end of the operation when connections are dropped.

Click through for more points along these lines.

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