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Category: Bugs

Bug with UnmatchedIndexes and Filtered Indexes

Taiob Ali points out a bug in SQL Server Management Studio:

SQL Server Management Studio (SSMS) showplan root node properties have two attributes to indicate when a filtered index can not be used during a parameterized query. One is ‘UnmatchedIndexes’, and the other one is under ‘Warnings’ attribute. Due to a bug in SSMS, the attributes are also showing positive results with filtered index and non-parameterized queries.

Let’s look at an example. I am using the AdventureWorks database, which you download from here.

If you want this fixed, vote up this Feedback item.

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Static Analysis of Hadoop Libraries

Maxim Stefanov ran a static analysis of several Hadoop libraries and here are the findings:

After the analysis was completed, I chose the most interesting warnings and noticed that I had the same number of warnings in production code and in tests. Normally, I don’t consider analyzer warnings from tests. But when I divided them, I couldn’t leave ‘tests’ warnings unattended. “Why not take a look at them,” I thought, “because bugs in tests might also have adverse consequences.” They can lead to incorrect or partial testing, or even to mishmash. 

After I selected the most intriguing warnings, I divided them by the following groups: production, test and the four main Hadoop modules. And now I’m glad to offer the review of analyzer warnings.  

Read on for the list. Hopefully Maxim submitted a few pull requests or at least Jira tickets for the projects.

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Recovering From Parsing NaN Values

Slava Murygin shows how you can recover from a nasty TRY_PARSE error:

In my previous post I outlined very dangerous SQL Server problem, caused by usually not very harmful commands “PARSE” and “TRY_PARSE“: Having “NaN” value for REAL and FLOAT producing severe error.

This post will be about a major issue it causes and on how to fight it.

Will start from generating the problem.

Attention: Do not run that in production!!!

Slava’s serious about not running the code in a real environment.

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SQL Server Truncating Numbers to Asterisks

Bert Wagner points out that some numeric types handle overflow in a weird way:

Why does SQL Server sometimes error when converting a number into a string, but other times succeeds and returns an asterisk?

I don’t know.

The best (and logical) answer I could find online is from Robert Sheldon, who attributes it to poor error handling practices, “…before error handling got a more reputable foothold.”

This makes it important to check your results. I imagine that there’s somebody who relies upon this exact functionality, but it’s pretty weird.

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TRY_PARSE and NaN

Slava Murygin finds a nasty bug in SQL Server:

Database in trouble has a table with FLOAT column. It’s Front-End application verifies user’s input and inserts the data into that column using TRY_PARSE function.
The developer’s intention was that any “Not-a-Numeric” or “Out-of-Range” values will be automatically converted to NULL and it will be for user’s discretion to verify and fix these values.

However, one of the application users was very educated and instead of empty space, NULL or any other bad not numeric value the user supplied data with value of “NaN” for empty cells, which simply stands for “Not a Numeric”.
That action caused a database corruption!

Click through for a demo which you should not repeat on a work server.

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When PolyBase Startup Fails in SQL Server 2019

Niels Berglund hits an annoying error after installing PolyBase on SQL Server 2019:

At MS Ignite in Orlando November 4 – 8, 2019, Microsoft announced the general availability of SQL Server 2019. At the same time, the SQL Server 2019 Developers Edition appeared as an MSDN download, and of course, I downloaded it and installed it on my dev box.

After the installation, I noticed that PolyBase did not start up correctly, and I saw dump files all over the place. After some investigation, I figured out what the issue was, and this blog post describes the fix.

This only affects Developer and Express editions, not Standard or Enterprise.

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rBokeh Tips for Missing Arguments

Matthias Nistler walks through troubleshooting rBokeh missing argument errors:

This approach is my go-to solution to change a rBokeh plot for which there is an argument missing in rBokeh that is available in python.
– Create the plot.
– Inspect the structure (str(plot)) of the rBokeh object.
– Search for the python’s argument name.
– Overwrite the value with the desired option as derived from python’s bokeh.

Given how nice the bokeh package looks, I really want rBokeh to work well. Hopefully this experience improves over time.

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Data Retrieval Bug Fixed for Columnstore Indexes

Dmitri Korotkevich takes us through an important bugfix in SQL Server:

The typical columnstore table is usually large and contains hundreds of millions or even billions of rows. Think about large fact tables in the data warehouses or huge transactional tables in OLTP systems. Those tables are usually partitioned. Besides usual reasons (Availability, Maintainability, etc), partitioning helps with the data load – it is easier to perform ETL in the staging table and import data through partition switch.

And here comes the problem. If you run OLTP query against partitioned clustered columnstore table and end up with the execution plan that uses index intersection of nonclustered B-Tree indexes, you may get incorrect results.

Getting the correct results in a query is pretty important (he says, with understatement), so this is an important bugfix; keep those SQL Server instances patched accordingly.

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Problems with Pivoting

Itzik Ben-Gan wraps up an outstanding series:

When people want to pivot data using T-SQL, they either use a standard solution with a grouped query and CASE expressions, or the proprietary PIVOT table operator. The main benefit of the PIVOT operator is that it tends to result in shorter code. However, this operator has a few shortcomings, among them an inherent design trap that can result in bugs in your code. Here I’ll describe the trap, the potential bug, and a best practice that prevents the bug. I’ll also describe a suggestion to enhance the PIVOT operator’s syntax in a way that helps avoid the bug.

If you use the PIVOT operator, you definitely want to read this article.

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Unexpected Results with ANY Aggregate

Paul White points out a couple odd scenarios with the ANY aggregate in SQL Server:

The execution plan erroneously computes separate ANY aggregates for the c2 and c3 columns, ignoring nulls. Each aggregate independently returns the first non-null value it encounters, giving a result where the values for c2 and c3 come from different source rows. This is not what the original SQL query specification requested.

The same wrong result can be produced with or without the clustered index by adding an OPTION (HASH GROUP) hint to produce a plan with an Eager Hash Aggregate instead of a Stream Aggregate.

Click through for the scenarios. Paul has also reported the second scenario as a bug.

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