| /*------------------------------------------------------------------------- |
| * |
| * levenshtein.c |
| * Levenshtein distance implementation. |
| * |
| * Original author: Joe Conway <mail@joeconway.com> |
| * |
| * This file is included by varlena.c twice, to provide matching code for (1) |
| * Levenshtein distance with custom costings, and (2) Levenshtein distance with |
| * custom costings and a "max" value above which exact distances are not |
| * interesting. Before the inclusion, we rely on the presence of the inline |
| * function rest_of_char_same(). |
| * |
| * Written based on a description of the algorithm by Michael Gilleland found |
| * at http://www.merriampark.com/ld.htm. Also looked at levenshtein.c in the |
| * PHP 4.0.6 distribution for inspiration. Configurable penalty costs |
| * extension is introduced by Volkan YAZICI <volkan.yazici@gmail.com. |
| * |
| * Copyright (c) 2001-2023, PostgreSQL Global Development Group |
| * |
| * IDENTIFICATION |
| * src/backend/utils/adt/levenshtein.c |
| * |
| *------------------------------------------------------------------------- |
| */ |
| #define MAX_LEVENSHTEIN_STRLEN 255 |
| |
| /* |
| * Calculates Levenshtein distance metric between supplied strings, which are |
| * not necessarily null-terminated. |
| * |
| * source: source string, of length slen bytes. |
| * target: target string, of length tlen bytes. |
| * ins_c, del_c, sub_c: costs to charge for character insertion, deletion, |
| * and substitution respectively; (1, 1, 1) costs suffice for common |
| * cases, but your mileage may vary. |
| * max_d: if provided and >= 0, maximum distance we care about; see below. |
| * trusted: caller is trusted and need not obey MAX_LEVENSHTEIN_STRLEN. |
| * |
| * One way to compute Levenshtein distance is to incrementally construct |
| * an (m+1)x(n+1) matrix where cell (i, j) represents the minimum number |
| * of operations required to transform the first i characters of s into |
| * the first j characters of t. The last column of the final row is the |
| * answer. |
| * |
| * We use that algorithm here with some modification. In lieu of holding |
| * the entire array in memory at once, we'll just use two arrays of size |
| * m+1 for storing accumulated values. At each step one array represents |
| * the "previous" row and one is the "current" row of the notional large |
| * array. |
| * |
| * If max_d >= 0, we only need to provide an accurate answer when that answer |
| * is less than or equal to max_d. From any cell in the matrix, there is |
| * theoretical "minimum residual distance" from that cell to the last column |
| * of the final row. This minimum residual distance is zero when the |
| * untransformed portions of the strings are of equal length (because we might |
| * get lucky and find all the remaining characters matching) and is otherwise |
| * based on the minimum number of insertions or deletions needed to make them |
| * equal length. The residual distance grows as we move toward the upper |
| * right or lower left corners of the matrix. When the max_d bound is |
| * usefully tight, we can use this property to avoid computing the entirety |
| * of each row; instead, we maintain a start_column and stop_column that |
| * identify the portion of the matrix close to the diagonal which can still |
| * affect the final answer. |
| */ |
| int |
| #ifdef LEVENSHTEIN_LESS_EQUAL |
| varstr_levenshtein_less_equal(const char *source, int slen, |
| const char *target, int tlen, |
| int ins_c, int del_c, int sub_c, |
| int max_d, bool trusted) |
| #else |
| varstr_levenshtein(const char *source, int slen, |
| const char *target, int tlen, |
| int ins_c, int del_c, int sub_c, |
| bool trusted) |
| #endif |
| { |
| int m, |
| n; |
| int *prev; |
| int *curr; |
| int *s_char_len = NULL; |
| int j; |
| const char *y; |
| |
| /* |
| * For varstr_levenshtein_less_equal, we have real variables called |
| * start_column and stop_column; otherwise it's just short-hand for 0 and |
| * m. |
| */ |
| #ifdef LEVENSHTEIN_LESS_EQUAL |
| int start_column, |
| stop_column; |
| |
| #undef START_COLUMN |
| #undef STOP_COLUMN |
| #define START_COLUMN start_column |
| #define STOP_COLUMN stop_column |
| #else |
| #undef START_COLUMN |
| #undef STOP_COLUMN |
| #define START_COLUMN 0 |
| #define STOP_COLUMN m |
| #endif |
| |
| /* Convert string lengths (in bytes) to lengths in characters */ |
| m = pg_mbstrlen_with_len(source, slen); |
| n = pg_mbstrlen_with_len(target, tlen); |
| |
| /* |
| * We can transform an empty s into t with n insertions, or a non-empty t |
| * into an empty s with m deletions. |
| */ |
| if (!m) |
| return n * ins_c; |
| if (!n) |
| return m * del_c; |
| |
| /* |
| * For security concerns, restrict excessive CPU+RAM usage. (This |
| * implementation uses O(m) memory and has O(mn) complexity.) If |
| * "trusted" is true, caller is responsible for not making excessive |
| * requests, typically by using a small max_d along with strings that are |
| * bounded, though not necessarily to MAX_LEVENSHTEIN_STRLEN exactly. |
| */ |
| if (!trusted && |
| (m > MAX_LEVENSHTEIN_STRLEN || |
| n > MAX_LEVENSHTEIN_STRLEN)) |
| ereport(ERROR, |
| (errcode(ERRCODE_INVALID_PARAMETER_VALUE), |
| errmsg("levenshtein argument exceeds maximum length of %d characters", |
| MAX_LEVENSHTEIN_STRLEN))); |
| |
| #ifdef LEVENSHTEIN_LESS_EQUAL |
| /* Initialize start and stop columns. */ |
| start_column = 0; |
| stop_column = m + 1; |
| |
| /* |
| * If max_d >= 0, determine whether the bound is impossibly tight. If so, |
| * return max_d + 1 immediately. Otherwise, determine whether it's tight |
| * enough to limit the computation we must perform. If so, figure out |
| * initial stop column. |
| */ |
| if (max_d >= 0) |
| { |
| int min_theo_d; /* Theoretical minimum distance. */ |
| int max_theo_d; /* Theoretical maximum distance. */ |
| int net_inserts = n - m; |
| |
| min_theo_d = net_inserts < 0 ? |
| -net_inserts * del_c : net_inserts * ins_c; |
| if (min_theo_d > max_d) |
| return max_d + 1; |
| if (ins_c + del_c < sub_c) |
| sub_c = ins_c + del_c; |
| max_theo_d = min_theo_d + sub_c * Min(m, n); |
| if (max_d >= max_theo_d) |
| max_d = -1; |
| else if (ins_c + del_c > 0) |
| { |
| /* |
| * Figure out how much of the first row of the notional matrix we |
| * need to fill in. If the string is growing, the theoretical |
| * minimum distance already incorporates the cost of deleting the |
| * number of characters necessary to make the two strings equal in |
| * length. Each additional deletion forces another insertion, so |
| * the best-case total cost increases by ins_c + del_c. If the |
| * string is shrinking, the minimum theoretical cost assumes no |
| * excess deletions; that is, we're starting no further right than |
| * column n - m. If we do start further right, the best-case |
| * total cost increases by ins_c + del_c for each move right. |
| */ |
| int slack_d = max_d - min_theo_d; |
| int best_column = net_inserts < 0 ? -net_inserts : 0; |
| |
| stop_column = best_column + (slack_d / (ins_c + del_c)) + 1; |
| if (stop_column > m) |
| stop_column = m + 1; |
| } |
| } |
| #endif |
| |
| /* |
| * In order to avoid calling pg_mblen() repeatedly on each character in s, |
| * we cache all the lengths before starting the main loop -- but if all |
| * the characters in both strings are single byte, then we skip this and |
| * use a fast-path in the main loop. If only one string contains |
| * multi-byte characters, we still build the array, so that the fast-path |
| * needn't deal with the case where the array hasn't been initialized. |
| */ |
| if (m != slen || n != tlen) |
| { |
| int i; |
| const char *cp = source; |
| |
| s_char_len = (int *) palloc((m + 1) * sizeof(int)); |
| for (i = 0; i < m; ++i) |
| { |
| s_char_len[i] = pg_mblen(cp); |
| cp += s_char_len[i]; |
| } |
| s_char_len[i] = 0; |
| } |
| |
| /* One more cell for initialization column and row. */ |
| ++m; |
| ++n; |
| |
| /* Previous and current rows of notional array. */ |
| prev = (int *) palloc(2 * m * sizeof(int)); |
| curr = prev + m; |
| |
| /* |
| * To transform the first i characters of s into the first 0 characters of |
| * t, we must perform i deletions. |
| */ |
| for (int i = START_COLUMN; i < STOP_COLUMN; i++) |
| prev[i] = i * del_c; |
| |
| /* Loop through rows of the notional array */ |
| for (y = target, j = 1; j < n; j++) |
| { |
| int *temp; |
| const char *x = source; |
| int y_char_len = n != tlen + 1 ? pg_mblen(y) : 1; |
| int i; |
| |
| #ifdef LEVENSHTEIN_LESS_EQUAL |
| |
| /* |
| * In the best case, values percolate down the diagonal unchanged, so |
| * we must increment stop_column unless it's already on the right end |
| * of the array. The inner loop will read prev[stop_column], so we |
| * have to initialize it even though it shouldn't affect the result. |
| */ |
| if (stop_column < m) |
| { |
| prev[stop_column] = max_d + 1; |
| ++stop_column; |
| } |
| |
| /* |
| * The main loop fills in curr, but curr[0] needs a special case: to |
| * transform the first 0 characters of s into the first j characters |
| * of t, we must perform j insertions. However, if start_column > 0, |
| * this special case does not apply. |
| */ |
| if (start_column == 0) |
| { |
| curr[0] = j * ins_c; |
| i = 1; |
| } |
| else |
| i = start_column; |
| #else |
| curr[0] = j * ins_c; |
| i = 1; |
| #endif |
| |
| /* |
| * This inner loop is critical to performance, so we include a |
| * fast-path to handle the (fairly common) case where no multibyte |
| * characters are in the mix. The fast-path is entitled to assume |
| * that if s_char_len is not initialized then BOTH strings contain |
| * only single-byte characters. |
| */ |
| if (s_char_len != NULL) |
| { |
| for (; i < STOP_COLUMN; i++) |
| { |
| int ins; |
| int del; |
| int sub; |
| int x_char_len = s_char_len[i - 1]; |
| |
| /* |
| * Calculate costs for insertion, deletion, and substitution. |
| * |
| * When calculating cost for substitution, we compare the last |
| * character of each possibly-multibyte character first, |
| * because that's enough to rule out most mis-matches. If we |
| * get past that test, then we compare the lengths and the |
| * remaining bytes. |
| */ |
| ins = prev[i] + ins_c; |
| del = curr[i - 1] + del_c; |
| if (x[x_char_len - 1] == y[y_char_len - 1] |
| && x_char_len == y_char_len && |
| (x_char_len == 1 || rest_of_char_same(x, y, x_char_len))) |
| sub = prev[i - 1]; |
| else |
| sub = prev[i - 1] + sub_c; |
| |
| /* Take the one with minimum cost. */ |
| curr[i] = Min(ins, del); |
| curr[i] = Min(curr[i], sub); |
| |
| /* Point to next character. */ |
| x += x_char_len; |
| } |
| } |
| else |
| { |
| for (; i < STOP_COLUMN; i++) |
| { |
| int ins; |
| int del; |
| int sub; |
| |
| /* Calculate costs for insertion, deletion, and substitution. */ |
| ins = prev[i] + ins_c; |
| del = curr[i - 1] + del_c; |
| sub = prev[i - 1] + ((*x == *y) ? 0 : sub_c); |
| |
| /* Take the one with minimum cost. */ |
| curr[i] = Min(ins, del); |
| curr[i] = Min(curr[i], sub); |
| |
| /* Point to next character. */ |
| x++; |
| } |
| } |
| |
| /* Swap current row with previous row. */ |
| temp = curr; |
| curr = prev; |
| prev = temp; |
| |
| /* Point to next character. */ |
| y += y_char_len; |
| |
| #ifdef LEVENSHTEIN_LESS_EQUAL |
| |
| /* |
| * This chunk of code represents a significant performance hit if used |
| * in the case where there is no max_d bound. This is probably not |
| * because the max_d >= 0 test itself is expensive, but rather because |
| * the possibility of needing to execute this code prevents tight |
| * optimization of the loop as a whole. |
| */ |
| if (max_d >= 0) |
| { |
| /* |
| * The "zero point" is the column of the current row where the |
| * remaining portions of the strings are of equal length. There |
| * are (n - 1) characters in the target string, of which j have |
| * been transformed. There are (m - 1) characters in the source |
| * string, so we want to find the value for zp where (n - 1) - j = |
| * (m - 1) - zp. |
| */ |
| int zp = j - (n - m); |
| |
| /* Check whether the stop column can slide left. */ |
| while (stop_column > 0) |
| { |
| int ii = stop_column - 1; |
| int net_inserts = ii - zp; |
| |
| if (prev[ii] + (net_inserts > 0 ? net_inserts * ins_c : |
| -net_inserts * del_c) <= max_d) |
| break; |
| stop_column--; |
| } |
| |
| /* Check whether the start column can slide right. */ |
| while (start_column < stop_column) |
| { |
| int net_inserts = start_column - zp; |
| |
| if (prev[start_column] + |
| (net_inserts > 0 ? net_inserts * ins_c : |
| -net_inserts * del_c) <= max_d) |
| break; |
| |
| /* |
| * We'll never again update these values, so we must make sure |
| * there's nothing here that could confuse any future |
| * iteration of the outer loop. |
| */ |
| prev[start_column] = max_d + 1; |
| curr[start_column] = max_d + 1; |
| if (start_column != 0) |
| source += (s_char_len != NULL) ? s_char_len[start_column - 1] : 1; |
| start_column++; |
| } |
| |
| /* If they cross, we're going to exceed the bound. */ |
| if (start_column >= stop_column) |
| return max_d + 1; |
| } |
| #endif |
| } |
| |
| /* |
| * Because the final value was swapped from the previous row to the |
| * current row, that's where we'll find it. |
| */ |
| return prev[m - 1]; |
| } |