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Category: Synapse Analytics

Synchronizing Metadata between Spark Tables and Serverless Pool

Charl Roux takes us through one back-end integration mechanism between tables in Azure Synapse Analytics Spark pools and serverless SQL pool:

Synapse provides an exciting feature which allows you to sync Spark database objects to Serverless pools and to query these objects without the Spark pool being active or running.  Synapse workspaces are accessed exclusively through an Azure AD Account and objects are created within this context in the Spark pool. In some scenarios I would like to share the data which I’ve created in my Spark database with other users for reporting or analysis purposes. This is possible with Serverless and in this article I will show you how to complete the required steps from creation of the object to successful execution. 

Click through for the demonstration.

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The Production-Readiness of Azure Synapse Analytics

Paul Andrew casts some harsh light:

While I completely share and actually like Microsoft’s vision of an analytics resource…

“that brings together data integration, enterprise data warehousing and big data analytics”

https://azure.microsoft.com/en-gb/services/synapse-analytics/

… the marketing, hype and technical implementation have resulted in a lot of confusion and disappointment.

So, to answer the title of this blog post directly. My opinion, as I write on 29th January 2021, is: NoAzure Synapse Analytics is not ready. Sorry Microsoft, but you’ve had long enough. I can’t hold back the questions and demands from customers anymore on why Synapse still isn’t included in my architecture diagrams.

Paul raises many good points, and the positive takeaway is that these are fixable issues. But as of today, they are definitely things you want to consider before jumping in.

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Combining Azure Synapse Analytics and Azure Purview

Wolfgang Strasser shows how we can integrate Azure Synapse Analytics with Azure Purview:

In the past months I had the chance to play with and build solutions based on Azure Synapse Analytics and Azure Purview.

Azure Synapse (my Synapse blog entries) as the foundation for a solid platform to store, analyze and build data solutions and Azure Purview (my Purview blog posts) as the data governance and data catalog solution in Azure.

During the writing of my latest blog post (What’s new in Azure Synapse Analytics?), I found a very interesting entry in the update feature list: Azure Purview Integration.

Read on to see how.

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Optimizing a SQL Server 2019 Project for a Dedicated SQL Pool

Kevin Chant shows us how we can modify a database schema intended for SQL Server 2019 to work best with an Azure Synapse Analytics dedicated SQL pool:

In this post I want to cover how you can transform your SQL Server database schema for a dedicated SQL Pool if you are using Azure DevOps. Because I covered it at Data Toboggan over the weekend and it can be very useful.

By the end of this post, you will know one way you can transform the schema of a database project for SQL Server 2019 if you are using Azure DevOps. So that you can make it optimal for dedicated SQL Pools.

Click through for the process and an example. Note that this isn’t a quick “check this box and you’re done” type of solution, but if you already have a proper star schema, this will help you think through some of the things you’ll need to do.

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Using Spark Pools in Azure Synapse Analytics

Rahul Mehta shows how to create and use an Apache Spark pool in Azure Synapse Analytics:

In the last part of the Azure Synapse Analytics article series, we learned how to create a dedicated SQL pool. Azure Synapse support three different types of pools – on-demand SQL pool, dedicated SQL pool and Spark pool. Spark provides an in-memory distributed processing framework for big data analytics, which suits many big data analytics use-cases. Azure Synapse Analytics provides mechanisms to use SQL on-demand pool to query data as a service, SQL dedicated pool for data warehousing using distributed data processing engine, and Spark pool for analytics using in-memory big data processing engine. This article shows how to create a Spark pool in Azure Synapse Analytics and further how to process the data using it.

Click through for a demo on setup and a sample notebook to get started.

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Auto-Pausing Dedicated SQL Pools in Azure Synapse Analytics

Fonseca Sergio automates an important cost-saving measure when working with Azure Synapse Analytics dedicated SQL pools:

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.

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External Table Not Accessible because Content of Directory Cannot be Listed

Liliam Leme troubleshoots an error when working with a serverless SQL pool in Azure Synapse Analytics:

Following 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.

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