![]() ![]() However, I have not thoroughly tested this, especially for side effects when the database is using a non-default collation. ![]() One way to modify this function to always be case sensitive would be to add a specific collation to the two places where strings are compared. By default, SQL Server's collation is one that will result in case insensitive comparisons. RETURN CASE WHEN <= THEN ELSE NULL ENDĪs mentioned in the comments of this function, the case sensitivity of the character comparisons will follow the collation that's in effect. SELECT = CASE WHEN > + 1 THEN + 1 ELSE + 1 END edit distance is just the delete of additional characters present in longer string if all of shorter string matches prefix and/or suffix of longer string, then IF = 0) RETURN prefix common to both strings can be ignored ![]() suffix common to both strings can be > 0 AND 1) = 1)) faster speed by spending more time spinning just the inner loop during the main processing. if strings of different lengths, ensure shorter string is in s. , int - difference in length between the two strings , int = / 1) + '.', 1)) - length of larger string , int = / 1) + '.', 1)) - length of smaller string get input string lengths including any trailing spaces (which SQL Server would otherwise ignore) , int - ending value for j loop (stopping point for processing a column) , int - offset used to calculate starting value for j loop , int - temporary storage of to allow SELECT combining , nchar - character at index i from s string , int - distance in cell to the left if we were using an m by n matrix , int - distance in cell diagonally above and left if we were using an m by n matrix , int, int - loop counters: i for s string and j for t string , int = 1 - index (1 based) of first non-matching character between the two string , nvarchar(4000)- running scratchpad for storing computed distances Based on Sten Hjelmqvist's "Fast, memory efficient" algorithm, described sensitivity configured in SQL Server (case-insensitive by default). string to the other, or NULL if is exceeded. number of insertion, deletion, and sustitution edits required to transform one Computes and returns the Levenshtein edit distance between two strings, i.e. Here is the code (updated to speed it up a bit more): - = when a max distance is given, early return as soon as max distance bound is known not to be achievable.when a max distance is given, time complexity goes from (len1*len2) to (min(len1,len2)) i.e.uses only a single array representing a column in the matrix (implemented as nvarchar).early return if difference in sizes guarantees max distance will be exceeded.early return if larger string starts or ends with entire smaller string.skips processing of shared prefix and/or suffix.It uses a single nvarchar "array" representing a column, and does all computations in-place in that, plus some helper int variables. It's also memory efficient, using space equal to the larger of the two input strings plus some constant space. For example, when the inputs are two very similar 4000 character strings, and a max edit distance of 2 is specified, this is almost three orders of magnitude faster than the edit_distance_within function in the accepted answer, returning the answer in 0.073 seconds (73 milliseconds) vs 55 seconds. In cases where the two strings have characters in common at their start (shared prefix), characters in common at their end (shared suffix), and when the strings are large and a max edit distance is provided, the improvement in speed is significant. I implemented the standard Levenshtein edit distance function in TSQL with several optimizations that improves the speed over the other versions I'm aware of. ![]()
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