Question

我使用PostgreSQL中的pg_trgm模块来计算使用trigrams的两个字符串之间的相似性。特别是我使用：

similarity(text, text)

返回的数字返回一个数字，表示两个参数的相似程度（介于0和1之间）。

如何在Google BigQuery上执行相似度功能（或等效功能）？

Answer 1

请尝试以下操作。至少作为增强蓝图

SELECT text1, text2, similarity FROM 
JS(
// input table
(
  SELECT * FROM 
  (SELECT 'mikhail' AS text1, 'mikhail' AS text2),
  (SELECT 'mikhail' AS text1, 'mike' AS text2),
  (SELECT 'mikhail' AS text1, 'michael' AS text2),
  (SELECT 'mikhail' AS text1, 'javier' AS text2),
  (SELECT 'mikhail' AS text1, 'thomas' AS text2)
) ,
// input columns
text1, text2,
// output schema
"[{name: 'text1', type:'string'},
  {name: 'text2', type:'string'},
  {name: 'similarity', type:'float'}]
",
// function
"function(r, emit) {

  var _extend = function(dst) {
    var sources = Array.prototype.slice.call(arguments, 1);
    for (var i=0; i<sources.length; ++i) {
      var src = sources[i];
      for (var p in src) {
        if (src.hasOwnProperty(p)) dst[p] = src[p];
      }
    }
    return dst;
  };

  var Levenshtein = {
    /**
     * Calculate levenshtein distance of the two strings.
     *
     * @param str1 String the first string.
     * @param str2 String the second string.
     * @return Integer the levenshtein distance (0 and above).
     */
    get: function(str1, str2) {
      // base cases
      if (str1 === str2) return 0;
      if (str1.length === 0) return str2.length;
      if (str2.length === 0) return str1.length;

      // two rows
      var prevRow  = new Array(str2.length + 1),
          curCol, nextCol, i, j, tmp;

      // initialise previous row
      for (i=0; i<prevRow.length; ++i) {
        prevRow[i] = i;
      }

      // calculate current row distance from previous row
      for (i=0; i<str1.length; ++i) {
        nextCol = i + 1;

        for (j=0; j<str2.length; ++j) {
          curCol = nextCol;

          // substution
          nextCol = prevRow[j] + ( (str1.charAt(i) === str2.charAt(j)) ? 0 : 1 );
          // insertion
          tmp = curCol + 1;
          if (nextCol > tmp) {
            nextCol = tmp;
          }
          // deletion
          tmp = prevRow[j + 1] + 1;
          if (nextCol > tmp) {
            nextCol = tmp;
          }

          // copy current col value into previous (in preparation for next iteration)
          prevRow[j] = curCol;
        }

        // copy last col value into previous (in preparation for next iteration)
        prevRow[j] = nextCol;
      }

      return nextCol;
    }

  };

  var the_text1;

  try {
    the_text1 = decodeURI(r.text1).toLowerCase();
  } catch (ex) {
    the_text1 = r.text1.toLowerCase();
  }

  try {
    the_text2 = decodeURI(r.text2).toLowerCase();
  } catch (ex) {
    the_text2 = r.text2.toLowerCase();
  }

  emit({text1: the_text1, text2: the_text2,
        similarity: 1 - Levenshtein.get(the_text1, the_text2) / the_text1.length});

  }"
)
ORDER BY similarity DESC

这是@thomaspark

基于https://storage.googleapis.com/thomaspark-sandbox/udf-examples/pataky.js的轻微修改

Answer 2

我did it是这样的：

CREATE TEMP FUNCTION trigram_similarity(a STRING, b STRING) AS (
  (
    WITH a_trigrams AS (
      SELECT
        DISTINCT tri_a
      FROM
        unnest(ML.NGRAMS(SPLIT(LOWER(a), ''), [3,3])) AS tri_a
    ),
    b_trigrams AS (
      SELECT
        DISTINCT tri_b
      FROM
        unnest(ML.NGRAMS(SPLIT(LOWER(b), ''), [3,3])) AS tri_b
    )
    SELECT
      COUNTIF(tri_b IS NOT NULL) / COUNT(*)
    FROM
      a_trigrams
      LEFT JOIN b_trigrams ON tri_a = tri_b
  )
);

这里是Postgres's pg_trgm的比较：

select trigram_similarity('saemus', 'seamus');
-- 0.25 vs. pg_trgm 0.272727

select trigram_similarity('shamus', 'seamus');
-- 0.5 vs. pg_trgm 0.4

如何在Google BigQuery中执行trigram操作？

2 个答案: