A Fine Slice Of SQL Server
As Synapse engineer or Synapse Support Engineer you may need to start and test some Pools, and you want this to be the most cost efficient possible. Leaving some Synapse with a lot of DWU left turned on during the weekend because you forget to pause the DW after you shutdown your computers is not a good approach and we can quickly resolve this by using Powershell + Automation accounts.
This is also a good introduction to Azure Automation if you aren’t familiar with it.
Comments closedWolfgang Strasser has a project for us:
In todays blog post I would like to build an end-to-end solution to combine data coming from different sources and stored in different form factors into a single Power BI data model using Azure Synapse Analytics.
Click through for the full demo.
Comments closedFollowing this lab: Lab: Serverless Synapse – From Spark to SQL On Demand – Microsoft Tech Community
You may experience this message:
Failed to execute the query because content of directory cannot be listed)
This is due to an extra step required to enable the AAD to pass through the firewall on the storage.
Click through for the solution.
Comments closedIn this guide, you will be integrating an already-existing Power BI workspace with Azure Synapse Analytics so that you can quickly access datasets, edit reports directly in the Synapse Studio, and automatically see updates to the report in the Power BI workspace. We will be using a Power BI report developed using the Movie Analytics dataset of the previous guide to show the functionalities of the Power BI integration in Azure Synapse.
Click through for the demo.
Comments closedIgor Stanko takes us through both dedicated and serverless SQL Pools in Azure Synapse Analytics:
Both serverless and dedicated SQL pools can be used within the same Synapse workspace, providing the flexibility to choose one or both options to cost-effectively manage your SQL analytics workloads. With Azure Synapse, you can use T-SQL to directly query data within a data lake for rapid data exploration and take advantage of the full capabilities of a data warehouse for more predictable and mission-critical workloads. With both query options available, you can choose the most cost-effective option for each of your use cases, resulting in cost savings across your business.
This post explores 2 consumption choices when exercising analytics using Synapse SQL (serverless and dedicated SQL pools) and examines the power and flexibility provided by Azure Synapse when both are used to execute T-SQL workloads. In addition, we will explore options to control cost when using both models.
Click through for details, including hints on minimizing costs.
Comments closedEuan Garden shows off some Apache Spark functionality in Azure Synapse Analytics:
Apache Spark has been a long-time favorite tool amongst data engineers and data scientists; it is well known for handling large scale data processing and complex machine learning workloads.
Azure Synapse Analytics offers a fully managed and integrated Apache Spark experience. By leveraging Apache Spark in Azure Synapse, you can benefit from integrated security, fully managed provisioning, and tight-coupling to other Azure services, such as SQL databases (dedicated and serverless), Azure Key Vault , ADLS Gen2, and Azure Blob Storage as well as fast starting, high performance compute instances.
Click through for the demo.
Comments closedServerless Synapse SQL pools in Azure Synapse Analytics have a new set of features that will enable you to analyze your Azure data more efficiently. The new Transact-SQL (T-SQL) language features that you can use in serverless SQL pools are STRING_AGG, OFFSET/FETCH, PIVOT/UNPIVOT, SESSION_CONTEXT, and CONTEXT_INFO.
Old T-SQL hands will likely know what all of this does, but click through if something looks unfamiliar. All of this is available in SQL Server 2017 and later (and everything but STRING_AGG() is available going back to 2008).
Saveen Reddy shows off the Manage Hub in Azure Synapse Analytics:
Azure Synapse Analytics allows you to provision a managed virtual network for your workspace. With the managed VNet, administators do not need to handle the burden of configuring traffic management rules, since that configuration is handled by Synapse. Moreover, using the managed VNet provides support for managed private endpoints. These endpoints are created in the managed VNet and enable access to Azure services. Communication between private endpoints and Azure resources occurs over private links, which transfer data through Microsoft’s network infrastructure.
Read on for a walkthrough.
Comments closedSaveen Reddy takes us through monitoring processes in Azure Synapse Analytics:
In order to test out SQL Script Monitoring in Azure Synapse we need some SQL Scripts. We can get some good ones from Azure Synapse Knowledge Center. Inside the Synapse workspace, choose the Develop option from the left menu to open the Develop Hub. Select “+” Add New Resource command and Browse gallery to navigate to the gallery.
Read on to see it in action.
Comments closedCharles Feddersen shows off one of the Azure Synapse Analytics hubs:
The Develop Hub in Azure Synapse Analytics enables you to write code and define business logic using a combination of notebooks, SQL scripts, and data flows. This gives us a development experience which provides the capability to query, analyze, and model data in multiple languages, along with giving us Intellisense support for these languages. This provides a rich interface for authoring code and in this post, we will see how we can use the Knowledge Center to jump-start our development experience.
Click through to see two demos, one of notebooks and one of SQL scripts.
Comments closed