greenplumn levenshtein 源码
greenplumn levenshtein 代码
文件路径：/src/backend/utils/adt/levenshtein.c
/*-------------------------------------------------------------------------
*
* 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) 2001-2019, 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 i,
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 (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;
#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];
}
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