An adventure on SQL Server performance and features

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SQL Notebooks: On the right track to enhance Data Analysis on SQL Server

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Since about a couple of versions ago, Azure Data Studio introduced Jupyter Notebooks support for SQL Server (and with SQL Server 2019 “Big Data Clusters” on the horizon, it was about time) What are Notebooks? “Notebooks” are a tool that our data science/machine learning colleagues know, love and are at their disposal since some time (Python, Spark, etc…); A notebook...

Cast any string directly to XML with auto-escaping characters in SQL Server

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Recently I had to look up the definition for a bunch of SQL objects and didn’t want to manually retrieve them manually in SSMS (with Create Scripts) or Visual Studio (by searching the object name in my TFS repository). Since lazyness and automation are the basis of a well done engineering work, I wanted to create a list, where I could basically click on the object that I needed and see the...

A quick function to remove (or keep only) string patterns from SQL Server Strings

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Working with strings in SQL Server isn’t as easy or powerful as using any programming language, but, I’m sure that more than once you had to to some data manipulation directly in the database, this may help you out, and it doesn’t use Loops, CLR or XML The idea is to exploit set logic, as opposed to the classic program logic of when you’re usually playing with strings in...

Tracking Dynamic SQL performance automatically with a wrapper on sp_executesql (Dynamic SQL Inception)

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in some projects I have a lot of Dynamic SQL going on, some queries are fast, some queries are slow, it depends on how the dynamic statement is actually put together ¯\_(ツ)_/¯ Tracking the performance of such statements is usually difficult because you don’t really know “why it’s slow” and you have to interpolate data from the app and the plan cache (if the plan is still...

Test: confronting various methods of bulk loading data from a table to another, what’s the fastest?

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 Most of the support request I get involved with can be summarized with the following keywords: “slow” + “datawarehouse” + “ETL” + “Save us” What about thinking about ETL performance before it goes bad? Before the system is in production for some time , the data size reaches a decent size which wasn’t tested in DEV and you find out that the...

An adventure on SQL Server performance and features

Emanuele Meazzo

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