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From "Arun Thomas" <arun.tho...@paybytouch.com>
Subject RE: [lang] [PATCH] StringUtils.getLevenshteinDistance() fix for OutOfMemoryError when used with LONG strings
Date Thu, 23 Oct 2003 16:30:40 GMT
Might be worth including as a separate subclass of testcase then - anyone looking for quick
runs can take it out of the test suite temporarily.  

-AMT

-----Original Message-----
From: Chas Emerick [mailto:cemerick@snowtide.com] 
Sent: Wednesday, October 22, 2003 3:52 PM
To: Jakarta Commons Developers List
Subject: Re: [lang] [PATCH] StringUtils.getLevenshteinDistance() fix for OutOfMemoryError
when used with LONG strings


Sure...although there's not much I can add with regard to the simpler  
test cases, I could use RandomStringUtils to generate some long strings  
to test behaviour that the patch addresses.  The downside is that the  
algorithm is fundamentally quadratic, so doing such a test would  
significantly extend the time required to complete the java-lang tests  
(i.e. ~7 minutes to calculate the character-level edit distance of two  
strings of 50K each).  If you think that's OK, I'll submit a patch to  
the test class.

Chas Emerick   |   cemerick@snowtide.com

http://www.snowtide.com
Snowtide Informatics Systems, Inc.


On Wednesday, October 22, 2003, at 04:53 PM, Henri Yandell wrote:

>
> Cool. Sounds good and I'll have a go at applying your patch.
>
> Any chance of you submitting your other unit tests for the class?
>
> Hen
>
> On Wed, 22 Oct 2003, Chas Emerick wrote:
>
>> I've never submitted a patch for an open-source project before (never 
>> got around to it lo these many years I guess), so I apologize for any 
>> errors in form or convention that I commit.
>>
>> I was planning on using the
>> StringUtils.getLevenshteinDistance(String,String) method in a 
>> particular circumstance where I needed to get the edit distance
>> between
>> two large strings (anywhere between 10K - 500K characters each).
>> However, I found that calling that method (as of v2.0 of commons-lang)
>> would result in an OutOfMemoryError when strings of such lengths were
>> provided.
>>
>> A quick look at the source revealed that the current implementation 
>> (which uses the sample impl. at http://www.merriampark.com/ld.htm)
>> creates a matrix with dimensions corresponding to the lengths of the 
>> two strings provided.  Clearly, a 100K x 100K int[] is problematic.
>>
>> Therefore, I've (mostly) rewritten the method using a two int arrays
>> of
>> the size of the first string's length, and the method now works
>> properly with larger strings (beastly slow, but that's quadratic
>> algorithms for you) .  I've tested the new implementation against the
>> ten or so testcases mentioned in the javadocs, as well as another
>> half-dozen of my own, and everything looks good.
>>
>> If my mail client botches the patch diff, you can get it at 
>> http://www.snowtide.com/commons-lang-LDpatch.txt
>>
>> Chas Emerick   |   cemerick@snowtide.com
>>
>> http://www.snowtide.com
>> Snowtide Informatics Systems, Inc.
>>
>> =====================================================================
>> =
>> ==
>> ==
>> --- StringUtils.java.old        Wed Oct 22 12:58:04 2003
>> +++ StringUtils.java    Wed Oct 22 13:51:36 2003
>> @@ -4255,8 +4255,8 @@
>>        * another, where each change is a single character 
>> modification (deletion,
>>        * insertion or substitution).</p>
>>        *
>> -     * <p>This implementation of the Levenshtein distance algorithm
>> -     * is from <a
>> href="http://www.merriampark.com/ld.htm">http://www.merriampark.com/
>> ld.
>> htm</a></p>
>> +     * <p>This implementation of the Levenshtein distance algorithm
>> was originally based
>> upon the one
>> +     * presented at <a
>> href="http://www.merriampark.com/ld.htm">http://www.merriampark.co
>> m/ld.htm</a></p>
>>        *
>>        * <pre>
>>        * StringUtils.getLevenshteinDistance(null, *)             =
>> IllegalArgumentException
>> @@ -4281,76 +4281,64 @@
>>           if (s == null || t == null) {
>>               throw new IllegalArgumentException("Strings must not be 
>> null");
>>           }
>> -        int d[][]; // matrix
>> -        int n; // length of s
>> -        int m; // length of t
>> -        int i; // iterates through s
>> -        int j; // iterates through t
>> -        char s_i; // ith character of s
>> -        char t_j; // jth character of t
>> -        int cost; // cost
>> -
>> -        // Step 1
>> -        n = s.length();
>> -        m = t.length();
>> +
>> +               /*
>> +               The difference between this impl. and the previous is
>> that, rather than cr
>> eating and retaining a matrix of size
>> +               s.length()+1 by t.length()+1, we maintain two
>> single-dimensional arrays of
>>   length s.length()+1.  The first, d,
>> +               is the 'current working' distance array that 
>> + maintains
>> the newest distance
>>   cost counts as we iterate through
>> +               the characters of String s.  Each time we increment
>> the
>> index of String t
>> we are comparing, d is copied to p,
>> +               the second int[].  Doing so allows us to retain the
>> previous cost counts a
>> s required by the algorithm
>> +               (taking the minimum of the cost count to the left, up
>> one, and diagonally
>> up and to the left of the current
>> +               cost count being calculated).  (Note that the arrays
>> aren't really copied
>> anymore, just switched...this is clearly much
>> +               better than cloning an array or doing a
>> System.arraycopy() each time throu
>> gh the outer loop.)
>> +
>> +               Effectively, the difference between the two
>> implementations is this one do
>> es not cause an out of memory condition
>> +               when calculating the LD over two very large strings.
>> +               */
>> +
>> +        int n = s.length(); // length of s
>> +        int m = t.length(); // length of t
>> +
>>           if (n == 0) {
>>               return m;
>> -        }
>> -        if (m == 0) {
>> +        } else if (m == 0) {
>>               return n;
>>           }
>> -        d = new int[n + 1][m + 1];
>>
>> -        // Step 2
>> -        for (i = 0; i <= n; i++) {
>> -            d[i][0] = i;
>> -        }
>> +        int p[] = new int[n+1]; //'previous' cost array, horizontally
>> +        int d[] = new int[n+1]; // cost array, horizontally
>> +               int _d[]; //placeholder to assist in swapping p and d
>>
>> -        for (j = 0; j <= m; j++) {
>> -            d[0][j] = j;
>> -        }
>> -
>> -        // Step 3
>> -        for (i = 1; i <= n; i++) {
>> -            s_i = s.charAt(i - 1);
>> -
>> -            // Step 4
>> -            for (j = 1; j <= m; j++) {
>> -                t_j = t.charAt(j - 1);
>> -
>> -                // Step 5
>> -                if (s_i == t_j) {
>> -                    cost = 0;
>> -                } else {
>> -                    cost = 1;
>> -                }
>> +        //indexes into strings s and t
>> +        int i; // iterates through s
>> +        int j; // iterates through t
>>
>> -                // Step 6
>> -                d[i][j] = min(d[i - 1][j] + 1, d[i][j - 1] + 1, d[i -
>> 1][j - 1] + cost);
>> -            }
>> -        }
>> +        char t_j; // jth character of t
>>
>> -        // Step 7
>> -        return d[n][m];
>> -    }
>> +        int cost; // cost
>>
>> -    /**
>> -     * <p>Gets the minimum of three <code>int</code> values.</p>
>> -     *
>> -     * @param a  value 1
>> -     * @param b  value 2
>> -     * @param c  value 3
>> -     * @return  the smallest of the values
>> -     */
>> -    private static int min(int a, int b, int c) {
>> -        // Method copied from NumberUtils to avoid dependency on
>> subpackage
>> -        if (b < a) {
>> -            a = b;
>> -        }
>> -        if (c < a) {
>> -            a = c;
>> +        for (i = 0; i<=n; i++) {
>> +            p[i] = i;
>>           }
>> -        return a;
>> +
>> +        for (j = 1; j<=m; j++) {
>> +            t_j = t.charAt(j-1);
>> +            d[0] = j;
>> +
>> +            for (i=1; i<=n; i++) {
>> +                cost = s.charAt(i-1)==t_j ? 0 : 1;
>> +
>> +                d[i] = Math.min(Math.min(d[i-1]+1, p[i]+1),
>> p[i-1]+cost);  //minimum of c
>> ell to the left+1, to the top+1, diagonally left and up +cost
>> +            }
>> +
>> +            //copy current distance counts to 'previous row' 
>> + distance
>> counts
>> +            _d = p;
>> +            p = d;
>> +            d = _d;
>> +        }
>> +
>> +        //our last action in the above loop was to switch d and p, 
>> + so
>> p now actual
>> ly has the most recent cost counts
>> +        return p[n];
>>       }
>>
>>   }
>>
>>
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