Various different mechanisms of calculating similarity scores as well as edit distances between Strings.

The list of edit distances that we currently support follow:

• Cosine Distance,
• Hamming Distance,
• Jaccard Distance,
• Jaro Winkler Distance,
• Levenshtein Distance,
• Longest Common Subsequence Distance,

and the list of similarity scores that we support follows:

• Cosine Similarity,
• Fuzzy Score Similarity,
• Jaccard Similarity,
• Jaro-Winkler Similarity, and
• Longest Common Subsequence Similarity

Before creating the UDFs in Snowflake you need to upload the sfsimilarity-1.0.jar, commons-lang3-3.12.0.jar and commons-text-1.9.jar, download the binaries from the Latest Release.

1. First create a stage (or use an existing one) in Snowflake:

CREATE STAGE SFSimilarity 
 COMMENT = 'Similarity and Distance functions for Snowflake';

2. Load the Jars to the Snowflake stage (for example @SFSimilarity) using Snowsql:

put file:///Users/me/Downloads/sfsimilarity-1.0.jar @SFSimilarity/ AUTO_COMPRESS = FALSE OVERWRITE = TRUE;
put file:///Users/me/Downloads/commons-lang3-3.12.0.jar @SFSimilarity/ AUTO_COMPRESS = FALSE OVERWRITE = TRUE;
put file:///Users/me/Downloads/commons-text-1.9.jar @SFSimilarity/ AUTO_COMPRESS = FALSE OVERWRITE = TRUE;

3. Create the UDFs using the SQL from the source code here: https://github.com/Snowflake-Labs/SFSimilarity/blob/main/src/main/sql/SFSimilarity.sql

Run the following examples to see how the functions work: https://github.com/Snowflake-Labs/SFSimilarity/blob/main/src/main/sql/SFSimilarity_Examples.sql

To compile from source, first clone this repository, then

Build the jar for the UDF functions using Maven:

mvn package

Underlying package java docs: https://commons.apache.org/proper/commons-text/userguide.html

A good walkthrough of the algorithms with examples: https://apothem.blog/apache-commons-text.html#string-similarity