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Category: Syntax

Script Parsing with ScriptDOM

Mala Mahadevan continues a series on ScriptDOM:

In the last post I wrote about what ScriptDOM is and why it is useful. From this post, I will explain how it can be put to use. What it does when you pass a script to it is to parse it, check if it is free of syntax errors, and build what is called an ‘Abstract Syntax Tree’, which is a programmatic representation of the script, with nodes and branches for each code element. The rest of the usage/functionality is built around the Abstract Syntax Tree. So in this post let us look into how this is accomplished.

Read on to see what you need to do.

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An Introduction to ScriptDOM

Mala Mahadevan gives us an idea of what ScriptDOM is:

I’ve been meaning to get a series of blog posts started on this topic. A twitter conversation from yesterday finally pushed me to it. Last year, I was tasked with finding a linting tool for the large t-sql code base we have at work. I looked into several tools – tsqllint, Sonarqube and several others. We ran into similar issues on all of them. Someone else defining rules for us didn’t work.
One tool called it wrong to use more than 3 tables in a query – we had several with 6-7, maybe even more. Another started to point out lack of indexes on temp tables as a problem (the rule was designed for table scripts but worked the same on code). Getting new rules that we wanted – such as not having unnaming primary keys on temp tables (Querystore doesn’t like them) or having our naming standards enforced meant extra work on someone else’s code. Our rules were custom to our environment. There were generic best practices for sure, such as finding the SELECT * or NOLOCK hints, but those were a small subset of what we needed. I then started looking for a tool with which I could make a custom linter. That’s when I discovered ScriptDOM, which has been around for a really long time with few people knowing or using it. It took me some time to understand how to put this to use. But after I figured it out it was really easy. Now I have a fairly robust, custom linter in place written in PowerShell and integrated well into our Azure DevOps Build process. It is easy to use and it is owned by us.

Read on to see what ScriptDOM can do and stay tuned to learn more.

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The DIFFERENCE() and SOUNDEX() Functions

Hadi Fadlallah looks at two methods of string distance:

Soundex is a phonetic algorithm developed by Robert C. Russell and Margaret King Odell in the early 1900s. This algorithm is used to index names as they are pronounced in English. The main goal of such an algorithm is to encode homophones to the same representation to be matched even if there are some slight spelling differences. As an example, consider the names “Smith” and “Smyth”, or “Mohamad” and “Mouhammad”. Soundex mainly encodes consonants and only encodes a vowel if it is the first letter of the name.

Being one of the most popular phonetic algorithms, Soundex was implemented in multiple database engines such as OracleSQL ServerMySQLSQLite, and PostgreSQL.

These two methods are not perfect and they do really limit you to one word (or small word grouping), but they are useful.

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CORRESPONDING and ANSI SQL

Lukas Eder looks at a rarely-implemented keyword in SQL:

I recently stumbled upon a standard SQL feature that was implemented, to my surprise, in HSQLDB. The keyword is CORRESPONDING, and it can be used with all set operations, including UNIONINTERSECT, and EXCEPT.

Click through to see what it does. Be sure to check out the comments, where Joe Celko pops in to provide some additional historical context to explain why you won’t find this keyword in many implementations of the standard..

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TRY_CAST and TRY_PARSE

Joe Obbish shows the difference between two functions:

There’s a lot of guidance out there that states that TRY_CAST is a faster, more modern version of TRY_PARSE and that TRY_PARSE should only be used if you need to set the optional culture parameter. However, the two functions can return different results in some cases, even without the culture parameter.

That guidance is blatantly wrong. TRY_CAST() and TRY_PARSE() both came out in SQL Server 2012. TRY_PARSE() uses .NET to perform parsing, which is going to have some edge case differences, especially around cultures and localization. TRY_CAST() is CAST() in an error-safe wrapper. If anything, TRY_CAST() is the “old” version and TRY_PARSE() the “new” version, with scare quotes in place because they both came out at the same time.

Both of them are useful, though I do agree with Joe’s advice of avoiding TRY_PARSE(), at least for larger datasets. If you’re parsing a single date or a small table of dates, TRY_PARSE() does an excellent job because TRY_PARSE('13/01/2019' AS DATE USING 'fr-fr') is not something you can easily do with TRY_CAST() in a US locale.

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Finding Substrings in a String with T-SQL

Kevin Wilkie avoids a regex:

Continuing on with our series from last time – see here if you somehow missed it – let’s have some more fun with the different functions we can use with strings.

This time, let’s focus on looking for different items we can use to find a string within a string.

With T-SQL not natively supporting regular expressions—though you can use a CLR module to do this—click through to see what Kevin uses.

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Implementing GREATEST in SQL Server 2019

Ronen Ariely is on a mission to be the greatest:

The function GREATEST returns the maximum value from a list of one or more expressions. It returns the data type with the highest precedence from the set of types passed to the function.

This function was added to Azure SQL. At this time, it is supported in Azure SQL Database, Azure SQL Managed Instance and Azure Synapse Analytics serverless. 

Unfortunately, it not yet supported on SQL Server on premises and synapse dedicated sql pool.

Click through for a pair of alternative constructs while we wait for GREATEST on-premises.

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Use TOP instead of SET ROWCOUNT

Jared Poche explains why the TOP clause is superior to using SET ROWCOUNT:

I was presenting on how to use the TOP clause to break down large operations into short, fast, bite-sized operations. The mechanics are things I learned from writing processes that do garbage collection, backfill new columns, and anonymizing PII data on existing tables. I’ve just posted the slides and example scripts here if you are interested.

ARE THEY THE SAME?

The question was whether the SET ROWCOUNT command would work just the same, and the answer is sometimes yes but largely no.

Read on to see what Jared means.

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Using GREATEST and LEAST in Azure SQL DB

Aaron Bertrand preps us for SQL Server 2022:

In an earlier tip, “Find MAX value from multiple columns in a SQL Server table,” Sergey Gigoyan showed us how to simulate GREATEST() and LEAST() functions, which are available in multiple database platforms but were – at least at the time – missing from Transact-SQL. These functions are now available in Azure SQL Database and Azure SQL Managed Instance, and will be coming in SQL Server 2022, so I thought it was a good time to revisit Sergey’s methods and compare.

Read on to see how the workaround compares.

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