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Month: March 2020

Managing Jobs in Availability Groups

Published 2020-03-27 by Kevin Feasel

Goncalo Cruz has a plan to run SQL Agent jobs on the primary node in an availability group:

In SQL Availability Groups the SQL jobs have to be created in all replicas and you need to add logic at the beginning of each relevant job to make it execute on the primary database. (this only applies when the local replica is the primary for the database)

If you do not add the logic they will execute with success in the primary replica but they will fail in the secondary replica.

Read on for a process which keeps jobs from running except on the primary.

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Transforming JSON to CSV with Azure Data Factory

Published 2020-03-27 by Kevin Feasel

Rayis Imayev shows how to use the Flatten task with Azure Data Factory wrangling data flows:

Last week I blogged about using Mapping Data Flows to flatten sourcing JSON file into a flat CSV dataset:
Part 1: Transforming JSON to CSV with the help of Flatten task in Azure Data Factory

Today I would like to explore the capabilities of the Wrangling Data Flows in ADF to flatten the very same sourcing JSON dataset.

Click through to see what’s different.

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An Overview of HADR Concepts with SQL Server

Published 2020-03-27 by Kevin Feasel

Kevin Hill walks through different topics around high availability and disaster recovery:

Replication—a very Special Snowflake:

SQL SERVER REPLICATION IS NEITHER HA NOR DR.

Not everything in a SQL Server user database CAN be replicated, such as users, or tables with no Primary Key. New objects are not automatically sent from Publisher to Subscriber. System databases are not replicated.

There’s plenty of good information in here, so check it out.

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Deleting Old Build Definitions in Azure DevOps

Published 2020-03-27 by Kevin Feasel

Mark Broadbent solves a problem for us:

I have been experiencing a problem for quite a while now in my current environment, in that some of our old builds cannot be deleted. When you attempt to do so it results in the following error:

One or more builds associated with the requested pipeline(s) are retained by a release. The pipeline(s) and builds will not be deleted.

Many of our pipelines have undergone a lot of change over time to the degree it is not even obvious anymore why (or indeed where) these builds are being prevented from being dropped. The only thing that is clear is that until they can be, the old build definitions will remain.

Regardless of the reason why, Mark has the answer for how.

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Using Azure Key Vault with Azure Databricks

Published 2020-03-26 by Kevin Feasel

Jason Bonello shows how easy it is to integrate Azure Key Vault into Azure Databricks:

In Azure Key Vault we will be adding secrets that we will be calling through Azure Databricks within the notebooks. First and foremost, this is for security purposes. It will ensure usernames and passwords are not hardcoded within the notebook cells and offer some type of control over access in case it needs to be reverted later on (assuming it is controlled by a different administrator). In addition to this, it will offer a better way of maintaining a solution, since if a password ever needs to be changed, it will only be changed in the Azure Key Vault without the need to go through any notebooks or logic.

If you don’t use Key Vault, Databricks does include its own secrets storage, so there’s really no reason to keep them in plaintext.

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Working with Spark.Net on Azure Synapse Analytics

Published 2020-03-26 by Kevin Feasel

Paul Andrew takes a look at Spark.NET (or Spark.Net or dotnet-spark or however I’m calling it this time):

The main reason I wanted access to Synapse is to play around with Spark.Net via the Synapse workspace Notebooks. Currently if deploying Synapse via the public Azure portal you only get the option to create a SQL compute pool, formally known as an Azure SQLDW. While this is good, it gives us none of the exciting things that we were shown about Synapse back in November last year during the Microsoft Ignite conference.

To get the good stuff in Azure Synapse Analytics you need access to the full developer UI and Synapse Workspace.

Click through to learn more about the experience.

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Powershell 7 and SMO

Published 2020-03-26 by Kevin Feasel

Max Trinidad gives us a primer on SMO with Powershell 7:

There are two ways you could use SMO in PowerShell 7 (cross-platform):

1. Installing the SMO NuGet packages, two packages are requiered:
a. Microsoft.SqlServer.SqlManagementObjects Version 150.18208.0 (as of 03/23/2020)
b. Microsoft.Data.SqlClient Version 1.1.1 (recommended)

2. Installing the PowerShell Module: SqlServer Version 21.1.18221 (as of 03/23/2020)

Keep in mind, once the packages and/or modules are installed, you need to update them manually.

Read the whole thing.

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Using relog to Make PerfMon Better

Published 2020-03-26 by Kevin Feasel

Erin Stellato shows us how to use relog:

Today I had to remember the steps for using relog. If you’ve never heard of relog, stay with me. It’s a tool for merging PerfMon files, and also for extracting smaller data sets from Perfmon. I still love PerfMon friends, I admit it. It’s been a staple for understanding performance on a Windows Server since I’ve started in IT. But I haven’t used relog in forever so I completely forgot the commands I needed.

Click through for usage instructions.

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sqltxls Now Supported Cross-Platform

Published 2020-03-26 by Kevin Feasel

Randolph West has made sql2xls work on Linux and MacOS:

Last year I released sql2xls, a free open-source tool which lets you throw a bunch of scripts into a folder, run them automatically against SQL Server and get the results back in a nicely-formatted Excel file, one tab per script.

A year later, I am happy to announce that the tool now runs cross-platform. You can compile and run it with .NET Core 3.1 LTS to run on Windows, macOS, and Linux. It uses the new Microsoft.Data.SqlClient library from NuGet, as well as the latest beta of ClosedXML.

Read on for a few more tips and go check the project out.

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Getting SQL Server with Current Linux Distributions

Published 2020-03-26 by Kevin Feasel

Tejas Shah announces the availability of SQL Server 2019 on the latest long-term releases of Ubuntu, Red Hat, and SuSE:

SQL Server team has been working diligently in adding support for current Linux distributions. To this end, the team announced support for SQL Server 2019 on RHEL 8.0, Ubuntu 18.04 and SLES 12 SP5 within last quarter.

The team is glad to announce that the Azure marketplace PAYG (Pay As You Go) images for SQL Server 2019 on RHEL 8.0, Ubuntu 18.04 and SLES 12 SP5 have been made generally available. You can deploy these images to get the latest of both SQL Server 2019 functionality and operating system improvements.

With Ubuntu 20.04 coming out soon, it’ll be interesting to see when that officially becomes supported.

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