The Hidden Performance Costs Of Collation Mismatch

Nate Johnson explains why you want collation consistency when joining tables together on varchar/nvarchar columns:

There’s a subtle difference here, vs. those many community blog posts, which I’ll repeat.  The columns are of the same type.  Just different collations.

And when the collation on the join predicates is different, bad things happen. Let’s take CustomerNumber for example. On the ERP side, it’s a nvarchar(20) collate Latin1_General_100_CI_AS. On the internal & web apps side, it’s a varchar(20) collateSQL_Latin1_General_CP1_CI_AS. As you might imagine, this is a prime field for joining because it’s the main customer identified throughout all the systems.

Let’s be clear here. This is a numeric value only. Did it need to support Unicode? Absolutely not. Should it have been an int or bigint? Probably. But did The ERP designers choose to make it Unicode string anyway? Yep.

Read on to see how Nate tries to dig himself out of this hole.

More Collation Comparison Fun

Solomon Rutzky wraps up his collation comparison series:

Just in case you were wondering: No, the test directly above test does not prove the documentation (as quoted at the top of Part A) correct. Yes, the documentation did state that characters would be converted to the Code Page specified by the Collation of the Database or Column, which does appear to be what is going on here. But, the differences are:

  1. The documentation states that the transformation happens if you reference a Unicode datatype, but what we just saw in the most recent test is the exact opposite:

    • only the NVARCHAR columns of the “Subscript 2” row match because they are still the “Subscript 2” character, while the NVARCHAR columns of the other two rows do not match due to being either “2” or “?”.
    • transformation did occur in the Latin1 and Hebrew VARCHAR columns, which is how it matched both rows with “2” in the Latin1 column and both rows with “?” in the Hebrew column.
  2. In the scenario involving another column where it would help to prefix the string literal with a capital-“N” (i.e. a VARCHAR column using a Collation that specifies a different Code Page than the Database’s Code Page), the Collation of the Database is not used for the transformation; it is only the referenced column’s Collation. The assumption here is that the string literal without the capital-“N” is being used in a Database where the Collation specifies a Code Page that has all of the characters.

  3. In the scenarios where the Database’s Collation, via its specified Code Page, did transform a string literal that was not prefixed with a capital-“N” (the two tests in the previous post), there would have already been unintended behavior no matter how the string literal was used.

I still think it’s a duck.

Collations Used In NVarchar To Varchar Conversions

Solomon Rutzky digs into collations:

So, the actual question is a bit more specific than would reasonably fit into a title, and it is:

In a WHERE condition (in Microsoft SQL Server, if that’s not obvious), when a string constant containing Unicode characters but not prefixed with a capital-N is compared to a column, which Collation (and hence Code Page) is used to do the implicit conversion of the Unicode characters into VARCHAR? Is it the Database’s default Collation, or the column’s Collation?

The answer has a lot more nuance than you might first think.  And for the record, it’s a duck.

Supplementary Characters In SQL Server 2017

Solomon Rutzky tests SQL Server 2017 collations to determine whether they support supplementary characters:

As you scroll through the list, does anything appear to be missing? Go ahead, take another look. I’ll wait :wink:. Figure it out? Yep, that’s right: none of those Collations end in “_SC“. Collations ending in “_SC” were added in SQL Server 2012 and support the full UTF-16 character set. Without the “_SC” ending built-in functions and comparisons / sorting only fully support the base UCS-2 character set (i.e. the first 65,536 Unicode Code Points). You can, of course, store and view all Unicode Code Points, even Supplementary Characters, in non-“_SC” Collations, but they will be interpreted as being two separate “unknown” characters instead of as a single character.

To illustrate this point, the following query shows: the two surrogate Code Points (not actual characters by themselves, but when used in pairs of any of the assigned combinations, produce a single character), the resulting Supplementary Character, and how the LEN function interprets that sequence in both non-“_SC” and “_SC” Collations.

Read on for Solomon’s testing, which includes a cat face emoji.  I know that I, for one, thought there was insufficient cat face emoji representation in SQL Server prior to 2017.

Binary Collation Case-Sensitivity

Solomon Rutzky explains that binary collations are not really case-sensitive:

Quite often people will use, or will recommend using, a binary Collation (one ending in “_BIN” or “_BIN2“) when wanting to do a case-sensitive operation. While in many cases it appears to behave as expected, it is best to not use a binary Collation for this purpose. The problem with using binary Collations to achieve case-sensitivity is that they have no concept of linguistic rules and cannot equate different versions of characters that should be considered equal. And the reason why using a binary Collation often appears to work correctly is simply the result of working with a set of characters that has no accents or other versions. One such character set (a common one, hence the confusion), is US English (i.e. “A” – “Z” and “a” – “z”; values 65 – 90 and 97 – 122, respectively). However, there are a few areas where binary collations don’t behave as many (most, perhaps?) people expect them to.

Solomon gives examples of false negatives (such as the same character represented by different code point combinations) and also explains how sort order can change.

Making Text Search Faster

Rob Farley looks at binary collations and specifically hash functions on aggregation:

If there’s an index on the column you’re grouping, then changing the collation is going to hurt a bit. Grouping could take advantage of a Stream Aggregate under our indexed collation, but changing the column is like throwing it away the index order (ORDER BY doesn’t get handled well by changing the collation) means a Hash is required. But comparing two query plans that both use Hash Match (Aggregate), one on a case-insensitive collation and one on a binary collation, then I found the latter was slightly faster. Not as drastic a change as searching, but still 10-30% better. One would run in about 12 seconds, and one in about 10.

Be sure to check out his comments for more details.

Anglicize Values

Dave Mattingly shows an easy way to anglicize values:

If your customer’s name is “José” but you search for “Jose”, you won’t (by default) find him.

Here’s a simple way to take care of that in your SQL database, without changing the data that you have.

If a particularly system only needs to support one language (e.g., English), this can be helpful, at least until somebody throws in Chinese or Hebrew characters.  That said, supporting Unicode is the best move when available.

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