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Category: Synapse Analytics

Working with Serverless and Dedicated SQL Pools in Azure Synapse Analytics

Igor 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.

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Apache Spark Basics in Azure Synapse Analytics

Euan 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.

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T-SQL Additions to Serverless SQL Pools

Jovan Popvic lays out some of the T-SQL syntax added to serverless SQL pools in Azure Synapse Analytics:

Serverless 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_AGGOFFSET/FETCHPIVOT/UNPIVOTSESSION_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).

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The Azure Synapse Analytics Manage Hub

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.

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Using the Synapse Studio Monitor Hub

Saveen 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.

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Using the Develop Hub in Azure Synapse Analytics

Charles 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.

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Issues Deploying Azure Synapse Analytics via ARM Template

Paul Andrew hits on some growing pains:

Just last week we heard the announcement from Microsoft that Azure Synapse Analytics is now generally available (GA)… A full year on, plus a few weeks, since first seeing Synapse at the big USA conferences in November 2019.

Today I’ve been attempting to use the resource with a view to implementing it for several customer projects. Although GA, it would seem that many part of the technology are far from ready.

In this brief blog I’m exposing some of the pain I’ve faced so far in simply trying to deploy a second instance of Azure Synapse Analytics using ARM templates.

Click through for three that Paul found. I’d expect that most of these will be tidied up in the next few months.

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Azure Synapse Analytics Goes GA

Sacha Tomey recaps some announcements:

After much anticipation, today, Microsoft have announced the general availability of Azure Synapse Analytics! Azure Synapse Analytics is a limitless analytics service that brings together data integration, enterprise data warehousing and Big Data analytics all into a single service, accelerating time to insights, enabling organisations to become data-driven. Azure Synapse combines capabilities spanning the needs of data engineering, machine learning, and BI without creating silos in processes and tools.

Read on for more info on this as well as info on Azure Purview.

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Folders in Azure Synapse Analytics


Wolfgang Strasser checks out a small but helpful addition to Azure Synapse Analytics
:

Good morning, day, afternoon or night – wherever and whenever you read this blog post! My day started with a nice surprise when I connected to one of our Azure Synapse workspaces …

Sometimes, it’s those little things that make (development) life easier – you can now add folders to structure the list of development artefacts in Synapse:

Read on to see how, including how you can bring order to the chaos of existing Synapse Analytics workspaces.

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Querying Data Lake Files in Power BI through Synapse Analytics

Wolfgang Strasser shows us how to integrate Azure Synapse Analytics and Power BI:

Sometimes however, would not it be nice to access the data lake in Direct Query mode – to get the most up to date information for every report view? I would say: yes … but how can you achieve this? The options natively provided by ADLS Gen2 and Power BI are not sufficient to solve this requirement. But: there are options to achieve this and, in this post, I would like to show you the possibilities using Azure Synapse Analytics to build a query layer on top of a ADLS Gen2 storage account.

Click through for a step-by-step walkthrough.

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