BigQuery string fuzzy matching damerau-levenshtein distance

damerau-levenshtein.sql

CREATE OR REPLACE FUNCTION `functions.fuzzy_match_damerau_levenshtein_distance`(s1 STRING, s2 STRING) RETURNS INT64 LANGUAGE js AS """
/*
 * Based off https://github.com/fabvalaaah/damerau-levenshtein-js
 * input: Two strings to compare the edit distance of. You probably want to lowercase/trim these before passing to this function
 * returns: Integer of the edit distance.
 */
  const initMatrix = (s1, s2) => {
    if (undefined == s1 || undefined == s2) {
      return null;
    }

    let d = [];
    for (let i = 0; i <= s1.length; i++) {
      d[i] = [];
      d[i][0] = i;
    }
    for (let j = 0; j <= s2.length; j++) {
      d[0][j] = j;
    }

    return d;
  };

  const damerau = (i, j, s1, s2, d, cost) => {
    if (i > 1 && j > 1 && s1[i - 1] === s2[j - 2] && s1[i - 2] === s2[j - 1]) {
      d[i][j] = Math.min.apply(null, [d[i][j], d[i - 2][j - 2] + cost]);
    }
  };

  if (
    undefined == s1 ||
    undefined == s2 ||
    "string" !== typeof s1 ||
    "string" !== typeof s2
  ) {
    return -1;
  }

  let d = initMatrix(s1, s2);
  if (null === d) {
    return -1;
  }
  for (var i = 1; i <= s1.length; i++) {
    let cost;
    for (let j = 1; j <= s2.length; j++) {
      if (s1.charAt(i - 1) === s2.charAt(j - 1)) {
        cost = 0;
      } else {
        cost = 1;
      }

      d[i][j] = Math.min.apply(null, [
        d[i - 1][j] + 1,
        d[i][j - 1] + 1,
        d[i - 1][j - 1] + cost
      ]);

      damerau(i, j, s1, s2, d, cost);
    }
  }

  return d[s1.length][s2.length];
""";