The purpose of an Elastic Job is to execute a T-SQL script that is scheduled or executed ad-hoc against a group of Azure SQL databases. Targets can be in different SQL Database servers, subscriptions, and/or regions. This blog post is quite long and heavy (code wise) so grab a coffee and follow through.
The architecture you could follow is shown below.
I had a good question from JP via a comment on my blog about whether you can use the MAXDOP query hint in Azure SQL Database. The answer? Yes.
Let’s use the Azure portal to build a globally distributed Cosmos DB. Before doing this, why would you ? what are the benefits?
Technically you do not have to create a cosmos DB and incur costs to test cosmos DB based applications, you could use the local emulator. This means that you do not need an Azure subscription, an actual hosted database or even an internet connection, everything is local to your machine and once ready you can deploy the solution to the cloud.
Cosmos DB falls into the “NoSQL” technology group, call it a buzz word if you like but it is very different to classic Relational Databases such as SQL Server. I never really understood why it was labeled NoSQL, if you build a document based data model via the SQL API you actually use SQL like language to query the JSON (from the collection). Moving on, it is an evolution from what used to exist called Document DB. (Cosmos DB sounds way more aggressive and punchy, right?) Recently I have been using it to store JSON documents (Document based data model) in Azure, as a fully managed service, i.e. PaaS and maybe you will use it one day.
Quite simply the objective as follows: Move data from Azure SQL Database to Azure SQL DW via Azure Data Factory v2 (ADF).
Quite a significant change has taken place within the Azure SQL Database space, more specifically the development of Azure SQL Database Serverless. Currently in preview mode this “compute” tier changes how you are billed (/second) and addresses some behaviors that many have wanted in the past. There are things to be aware of though.
Before writing about pausing (and resuming) Azure SQL Data Warehouse (DW) it makes sense to discuss the architecture of this product. At a high level it involves a control node, a MPP (Massively Parallel Processing) engine compromising of compute nodes and storage. Perfectly summarised by this image.
A quick 2 minute upload (with sound, my voice) showing you how easy it is to create an Azure SQL Database using the Azure portal and then using SSMS (SQL Server Management Studio) to connect to it.
There are a few ways to scale a SQL elastic pool. For this blog post I show you how to scale up. It can be done via the Azure portal and Azure PowerShell but not T-SQL.
I would say the PowerShell route is the easiest. Connect to your account and issue the below code. Here I am going from a 100 edtu pool to a massive 2000 edtu pool whilst tweaking the min/max setting.
