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Category: Misc Languages

Adding Aggregates to Table.Profile

Published 2019-08-05 by Kevin Feasel

Chris Webb shows us how to add additional aggregates to Table.Profile in M:

A few years ago I blogged about the Table.Profile M function and how you could use it to create a table of descriptive statistics for your data:

https://blog.crossjoin.co.uk/2016/01/12/descriptive-statistics-in-power-bim-with-table-profile/

Since that post was written a new, optional second parameter has been added to the function called additionalAggregates which allows you to add your own custom columns containing aggregate values to the output of Table.Profile, so I thought I’d write a follow-up on how to use it.

Click through for that follow-up.

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Keeping Bash Scripts Reusable

Published 2019-08-01 by Kevin Feasel

Kellyn Pot’vin-Gorman explains some of the concepts behind scripting for longevity:

I’m going to admit, that the reason I didn’t embrace Powershell at first, was most of the examples I found were of full of hardcoded values.  I found it incredibly obtuse, but I started to realize that it came from many sources who might not have the scripting history that those of other shells, (this was just my theory, not a lot of evidence to prove on this one, so keep that in mind…)  As Powershell scripts have matured, I’ve noticed how many are starting to build them with more dynamic values and advance scripting options, and with this, I’ve become more comfortable with Powershell.

I think the best way to learn is to see real examples, so let’s demonstrate.

Read on for those examples.

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Hooking SQL Server to Kafka

Published 2019-07-17 by Kevin Feasel

Niels Berglund has an interesting scenario for us:

We see how the procedure in Code Snippet 2 takes relevant gameplay details and inserts them into the dbo.tb_GamePlay table.

In our scenario, we want to stream the individual gameplay events, but we cannot alter the services which generate the gameplay. We instead decide to generate the event from the database using, as we mentioned above, the SQL Server Extensibility Framework.

Click through for the scenario in depth and how to use Java to tie together SQL Server and Kafka.

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How .NET Code Talks to Spark

Published 2019-07-15 by Kevin Feasel

Ed Elliott has a great diagram showing how user-written .NET code communicates with Spark over the Java VM:

4. Spark-dotnet Java driver listens on tcp port
The spark-dotnet Java driver listens on a TCP socket. This socket is used to communicate between the Java VM and the dotnet code, the dotnet code doesn’t run in the Java VM but is in a separate process communitcating with the Java VM via that TCP postrt. The year is 2019, we serialize and deserialize data all the time and don’t even know it, hell notepad probably even does it.

It’s serialization & deserialization as well as TCP sockets all the way down.

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Spark and dotnet in a Single Container

Published 2019-07-11 by Kevin Feasel

Ed Elliott shows how you can combine Spark and .NET Core in a single Docker container:

This is quite new syntax in docker and you need at least docker 17.05 (client and daemon), after the images “FROM blah” you can specify a name “core” in this case, then later you can copy from the first image to the second using “–from=” on the “COPY” command.

In this dockerfile I have added Spark 2.4.3 and the default environment variables we need to get spark running, if you grab this dockerfile and run “docker build -t dotnet-spark .” you should get an images you can then run which includes the dependencies for dotnet as well as spark.

Ed includes all of the scripts needed to test this out, too.

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Scala 2.13 Changes

Published 2019-07-02 by Kevin Feasel

Anmol Sarna takes us through what’s new in Scala 2.13:

Last, but not the least, the team has invested heavily in compiler speedups during the 2.13 cycle which resulted in some major changes with respect to the compiler.

Compiler performance in 2.13 is 5-10% better compared to 2.12, thanks mainly to the new collections.

There are a lot of changes in this version. I wonder how long before Spark supports it fully.

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CQL: Category Theory-Based Querying Language

Published 2019-06-28 by Kevin Feasel

John Cook looks at a querying language based on category theory:

My interest in category theory waxes and wanes, and just as it was was at its thinnest crescent phase I ran across CQL, categorical query language. I haven’t had time to look very far into it, but it seems promising. The site’s modest prose relative to the revolutionary rhetoric of some category enthusiasts makes me have more confidence that the authors may be on to something useful.

I’m going through some lectures on category theory now and am in a big functional programming phase, so this is interesting but I won’t be giving up SQL anytime soon for it.

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Unicode Escaping Across Various Languages

Published 2019-06-28 by Kevin Feasel

Solomon Rutzky shows how to perform Unicode character escaping in a dozen places:

The purpose of this post is to correct the overall lack of examples. Everything shown below are actual working examples of creating both a Unicode-only BMP character (meaning a non-Supplementary Character that would require Unicode) and a Supplementary Character. Most examples include a link to an online demo, either on db<>fiddle (for database demos) or IDE One (for non-database demos), both very cool and handy sites.

This includes T-SQL and MySQL as well as .NET languages, PHP, JavaScript, and even Excel. It’s a handy reference page.

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Case-Insensitive Searches in Snowflake

Published 2019-06-24 by Kevin Feasel

Koen Verbeeck shows how you can perform case-insensitive searches in Snowflake DB:

I’m doing a little series on some of the nice features/capabilities in Snowflake (the cloud data warehouse). In each part, I’ll highlight something that I think it’s interesting enough to share. It might be some SQL function that I’d really like to be in SQL Server, it might be something else.

Today I have a small blog post about a neat little function I discovered last week – with thanks to my German colleague, who wants to remain anonymous. The function is called ILIKE and it is syntactic sugar for the combination of UPPER and LIKE.

I’m personally not a fan of case-sensitive collations for data; it’s hard for me to understand the meaningful differences between “dog,” “Dog,” and “DOG.”

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