A Fine Slice Of SQL Server
Josh Darnell explains why you might get threadpool waits even when you think you shouldn’t:
I occasionally see (usually brief)
THREADPOOLwaits on systems that are really not all that heavily loaded. This is my investigation into why. Some might say I have too much time on my hands.Before getting into these unusual
THREADPOOLcases, let’s cover the normal ones.
Read the whole thing. It’s example #9068 of how a particular wait is not always a bad thing.
Comments closedNathan Thompson walks us through a mutation testing experiment:
Since our hypothesis was that the implementation differences between Jasmine and Jest could affect the Mutation Score of our legacy and new test suites, we began by cataloging every bit of Jasmine-specific syntax in our legacy suite. We then compiled a list of roughly forty test files that we would target for Mutation Testing in order to cover the full syntax catalog. For each file we generated a Mutation Score for its legacy state, converted it to run in our new Jest setup, and generated a Mutation Score again. Our hope was that the new Jest framework would have a Mutation Score as good as or better than our legacy framework.
By limiting the scope of our test to just a few dozen files, we were able to run all mutations Stryker had to offer within a reasonable timeframe. However, the sheer size of our codebase and the sprawling dependency trees in any given feature presented other challenges to this work. As I mentioned before, Stryker copies the source code to be mutated into separate sandbox directories. By default, it copies the entire project into each sandbox, but that was too much for Node.js to handle in our repository:
In my undergrad days, I loved mutation testing mostly because of the terminology. I’m happy to see a proper implementation of mutation testing and I’m even happier to see that they have a .NET version.
Comments closedMikey Bronowski continues a series on dbatools:
At some point, you have lots of different objects between replicas like logins, credentials, agent jobs, other agent objects. In some scenarios, it is good to have them all in sync. I am going to show you the -WhatIf output just to get an idea.
This is one of the (many) areas where dbatools makes life quite a bit easier.
Comments closedFred Kaffenberger poses a question:
If you can ask, how do we know that we are improving, you should also be able to ask how do we know that the security roles are implemented correctly. Data culture is not just for the business, but for the reporting team as well. I haven’t seen much discussion of auditing security roles in Power BI circles, so I’m genuinely curious about how others tackle this issue. Does everyone simply work hard and hope for the best? Or do you restrict everything at the database level and use different apps for different groups instead? There may even be regulatory reasons which require you to restrict it at the database level. But even if you do restrict everything at the database level, you still need to validate that security as well.
Read on for a verification technique.
Comments closedSoheil Bakhshi shows how we can take an input from Power Query and pass it to a stored porcedure:
This is the fourth one in the form of Quick Tips. Here is the scenario. One of my customers had a requirement to get data from a Stored Procedure from SQL Server. She required to pass the values from a Query Parameter back to SQL Server and get the results in Power BI.
The solution is somewhat easy.
If you’re familiar with SQL Server Reporting Services, the solution instantly makes sense.
Comments closedSQL Server provides two different forms of authenticating the users that connect to the database server: Windows Authentication, which is the default and preferred method, and SQL Server Authentication, which needs to be explicitly enabled.
There are reasons you might need to enable SQL Server authentication and, although advertised as less secure than Windows Authentication, there are still a few things we can do to minimise the risks.
Read on for those tips.
Comments closedRobert Metzger updates us on the state of Apache Flink on Docker:
With over 50 million downloads from Docker Hub, the Flink docker images are a very popular deployment option.
The Flink community recently put some effort into improving the Docker experience for our users with the goal to reduce confusion and improve usability.
Read on to learn more about those recent improvements and how to get started with Flink.
Comments closedKundan Kumarr walks us through a simple data pipeline:
Spark Structured Streaming is a component of Apache Spark framework that enables scalable, high throughput, fault tolerant processing of data streams.
Apache Kafka is a scalable, high performance, low latency platform that allows reading and writing streams of data like a messaging system.
Apache Cassandra is a distributed and wide-column NoSQL data store.
As I’m reading through this, I enjoyed just how straightforward the whole process was.
Comments closedMatt Allington wants to solve a problem:
Using a switch measure to toggle results is a mature and common technique used in Power BI and Power Pivot for Excel. For example, a switch measure can be used to toggle what appears on a chart so that the end user can easily switch the data being visualised (see image below).
This technique uses a disconnected table, a slicer to receive the user selection, and a switch measure to change the result of the measure based on user input. When you select an option on the slicer you can have your chart update to show the result you want to see in the chart. I blogged about this in 2014 here.
The switch measure has a drawback, though: you can only have one number format, so Matt has a new solution using calculation groups.
Comments closedThomas Rushton has a function for us:
(This follows on from my previous script about emailing SQL Job ouput.)
There are times when a SQL server scheduled task needs to look at the output from the previous step, and make decisions based on that – particularly when parsing output from noisy/chatty scripts.
I have, therefore, put together a quick and dirty script to check the output from a SQL Server job step, and pull that into a string, so that it can be examined and a script can then make decisions about what to do next.
Read on for the function definition as well as a few notes on its usage.
Comments closed