[GitHub] [commons-text] kinow commented on a change in pull request #233: [TEXT-212] A More Efficient Implementation for Calculating Size of Longest Common Subsequence
kinow commented on a change in pull request #233:
URL: https://github.com/apache/commons-text/pull/233#discussion_r683855155
##
File path:
src/main/java/org/apache/commons/text/similarity/LongestCommonSubsequence.java
##
@@ -29,36 +29,109 @@
*
*
*
- * This implementation is based on the Longest Commons Substring algorithm
- * from https://en.wikipedia.org/wiki/Longest_common_subsequence_problem;>
- * https://en.wikipedia.org/wiki/Longest_common_subsequence_problem.
+ * As of version 1.10, a more space-efficient of the algorithm is implemented.
The new algorithm has linear space
+ * complexity instead of quadratic. However, time complexity is still
quadratic in the size of input strings.
*
*
- * For further reading see:
+ *
+ * The implementation is based on Hirschberg's Longest Commons Substring
algorithm (cited below).
+ *
*
- * Lothaire, M. Applied combinatorics on words. New York: Cambridge
U Press, 2005. 12-13
+ * For further reading see:
+ *
+ *
+ * Lothaire, M. Applied combinatorics on words. New York: Cambridge U
Press, 2005. 12-13
+ *
+ *
+ * D. S. Hirschberg, "A linear space algorithm for computing maximal common
subsequences," CACM, 1975, pp. 341--343.
+ *
+ *
*
* @since 1.0
*/
public class LongestCommonSubsequence implements SimilarityScore {
-
/**
- * Calculates longest common subsequence similarity score of two {@code
CharSequence}'s passed as
+ * Calculates the longest common subsequence similarity score of two
{@code CharSequence}'s passed as
* input.
*
- * @param left first character sequence
- * @param right second character sequence
- * @return longestCommonSubsequenceLength
- * @throws IllegalArgumentException
- * if either String input {@code null}
+ *
+ * This method implements a more efficient version of LCS algorithm which
has quadratic time and
+ * linear space complexity.
+ *
+ *
+ *
+ * This method is based on newly implemented {@link
#algorithmB(CharSequence, CharSequence)}.
+ * An evaluation using JMH revealed that this method is almost two times
faster than its previous version.
+ *
+ *
+ * @param left First character sequence
+ * @param right Second character sequence
+ * @return Length of the longest common subsequence of left
and right
+ * @throws IllegalArgumentException if either String input {@code null}
*/
@Override
public Integer apply(final CharSequence left, final CharSequence right) {
// Quick return for invalid inputs
if (left == null || right == null) {
throw new IllegalArgumentException("Inputs must not be null");
}
-return longestCommonSubsequence(left, right).length();
+// Find lengths of two strings
+final int leftSz = left.length();
+final int rightSz = right.length();
+
+// Check if we can avoid calling algorithmB which involves heap space
allocation
+if (leftSz == 0 || rightSz == 0) {
+return 0;
+}
+
+// Check if we can save even more space
+if (leftSz < rightSz) {
+return algorithmB(right, left)[leftSz];
+}
+return algorithmB(left, right)[rightSz];
+}
+
+/**
+ * An implementation of "ALG B" from Hirschberg's CACM '71 paper.
+ * Assuming the first input sequence is of size m and the
second input sequence is of size
+ * n, this method returns the last row of the dynamic
programming (DP) table when calculating
+ * the LCS of the two sequences in O(m*n) time and O(n)
space.
Review comment:
Although `algorithmC` does similar trick, but in the javadocs we say
`O(m+n) space`
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[GitHub] [commons-text] kinow commented on a change in pull request #233: [TEXT-212] A More Efficient Implementation for Calculating Size of Longest Common Subsequence
kinow commented on a change in pull request #233:
URL: https://github.com/apache/commons-text/pull/233#discussion_r683853652
##
File path:
src/main/java/org/apache/commons/text/similarity/LongestCommonSubsequence.java
##
@@ -29,36 +29,109 @@
*
*
*
- * This implementation is based on the Longest Commons Substring algorithm
- * from https://en.wikipedia.org/wiki/Longest_common_subsequence_problem;>
- * https://en.wikipedia.org/wiki/Longest_common_subsequence_problem.
+ * As of version 1.10, a more space-efficient of the algorithm is implemented.
The new algorithm has linear space
+ * complexity instead of quadratic. However, time complexity is still
quadratic in the size of input strings.
*
*
- * For further reading see:
+ *
+ * The implementation is based on Hirschberg's Longest Commons Substring
algorithm (cited below).
+ *
*
- * Lothaire, M. Applied combinatorics on words. New York: Cambridge
U Press, 2005. 12-13
+ * For further reading see:
+ *
+ *
+ * Lothaire, M. Applied combinatorics on words. New York: Cambridge U
Press, 2005. 12-13
+ *
+ *
+ * D. S. Hirschberg, "A linear space algorithm for computing maximal common
subsequences," CACM, 1975, pp. 341--343.
+ *
+ *
*
* @since 1.0
*/
public class LongestCommonSubsequence implements SimilarityScore {
-
/**
- * Calculates longest common subsequence similarity score of two {@code
CharSequence}'s passed as
+ * Calculates the longest common subsequence similarity score of two
{@code CharSequence}'s passed as
* input.
*
- * @param left first character sequence
- * @param right second character sequence
- * @return longestCommonSubsequenceLength
- * @throws IllegalArgumentException
- * if either String input {@code null}
+ *
+ * This method implements a more efficient version of LCS algorithm which
has quadratic time and
+ * linear space complexity.
+ *
+ *
+ *
+ * This method is based on newly implemented {@link
#algorithmB(CharSequence, CharSequence)}.
+ * An evaluation using JMH revealed that this method is almost two times
faster than its previous version.
+ *
+ *
+ * @param left First character sequence
+ * @param right Second character sequence
+ * @return Length of the longest common subsequence of left
and right
+ * @throws IllegalArgumentException if either String input {@code null}
*/
@Override
public Integer apply(final CharSequence left, final CharSequence right) {
// Quick return for invalid inputs
if (left == null || right == null) {
throw new IllegalArgumentException("Inputs must not be null");
}
-return longestCommonSubsequence(left, right).length();
+// Find lengths of two strings
+final int leftSz = left.length();
+final int rightSz = right.length();
+
+// Check if we can avoid calling algorithmB which involves heap space
allocation
+if (leftSz == 0 || rightSz == 0) {
+return 0;
+}
+
+// Check if we can save even more space
+if (leftSz < rightSz) {
+return algorithmB(right, left)[leftSz];
+}
+return algorithmB(left, right)[rightSz];
+}
+
+/**
+ * An implementation of "ALG B" from Hirschberg's CACM '71 paper.
+ * Assuming the first input sequence is of size m and the
second input sequence is of size
+ * n, this method returns the last row of the dynamic
programming (DP) table when calculating
+ * the LCS of the two sequences in O(m*n) time and O(n)
space.
Review comment:
Oh, I think because you are always passing the smallest as the second
sequence, then it'll be `O(n)`?
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[GitHub] [commons-text] kinow commented on a change in pull request #233: [TEXT-212] A More Efficient Implementation for Calculating Size of Longest Common Subsequence
kinow commented on a change in pull request #233:
URL: https://github.com/apache/commons-text/pull/233#discussion_r683851199
##
File path:
src/main/java/org/apache/commons/text/similarity/LongestCommonSubsequence.java
##
@@ -29,36 +29,109 @@
*
*
*
- * This implementation is based on the Longest Commons Substring algorithm
- * from https://en.wikipedia.org/wiki/Longest_common_subsequence_problem;>
- * https://en.wikipedia.org/wiki/Longest_common_subsequence_problem.
+ * As of version 1.10, a more space-efficient of the algorithm is implemented.
The new algorithm has linear space
+ * complexity instead of quadratic. However, time complexity is still
quadratic in the size of input strings.
*
*
- * For further reading see:
+ *
+ * The implementation is based on Hirschberg's Longest Commons Substring
algorithm (cited below).
+ *
*
- * Lothaire, M. Applied combinatorics on words. New York: Cambridge
U Press, 2005. 12-13
+ * For further reading see:
+ *
+ *
+ * Lothaire, M. Applied combinatorics on words. New York: Cambridge U
Press, 2005. 12-13
+ *
+ *
+ * D. S. Hirschberg, "A linear space algorithm for computing maximal common
subsequences," CACM, 1975, pp. 341--343.
+ *
+ *
*
* @since 1.0
*/
public class LongestCommonSubsequence implements SimilarityScore {
-
/**
- * Calculates longest common subsequence similarity score of two {@code
CharSequence}'s passed as
+ * Calculates the longest common subsequence similarity score of two
{@code CharSequence}'s passed as
* input.
*
- * @param left first character sequence
- * @param right second character sequence
- * @return longestCommonSubsequenceLength
- * @throws IllegalArgumentException
- * if either String input {@code null}
+ *
+ * This method implements a more efficient version of LCS algorithm which
has quadratic time and
+ * linear space complexity.
+ *
+ *
+ *
+ * This method is based on newly implemented {@link
#algorithmB(CharSequence, CharSequence)}.
+ * An evaluation using JMH revealed that this method is almost two times
faster than its previous version.
+ *
+ *
+ * @param left First character sequence
+ * @param right Second character sequence
+ * @return Length of the longest common subsequence of left
and right
+ * @throws IllegalArgumentException if either String input {@code null}
*/
@Override
public Integer apply(final CharSequence left, final CharSequence right) {
// Quick return for invalid inputs
if (left == null || right == null) {
throw new IllegalArgumentException("Inputs must not be null");
}
-return longestCommonSubsequence(left, right).length();
+// Find lengths of two strings
+final int leftSz = left.length();
+final int rightSz = right.length();
+
+// Check if we can avoid calling algorithmB which involves heap space
allocation
+if (leftSz == 0 || rightSz == 0) {
+return 0;
+}
+
+// Check if we can save even more space
+if (leftSz < rightSz) {
+return algorithmB(right, left)[leftSz];
+}
+return algorithmB(left, right)[rightSz];
+}
+
+/**
+ * An implementation of "ALG B" from Hirschberg's CACM '71 paper.
+ * Assuming the first input sequence is of size m and the
second input sequence is of size
+ * n, this method returns the last row of the dynamic
programming (DP) table when calculating
+ * the LCS of the two sequences in O(m*n) time and O(n)
space.
Review comment:
@ali-ghanbari
>and O(n) space
Isn't that `O(m+n)`?
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[GitHub] [commons-text] kinow commented on a change in pull request #233: [TEXT-212] A More Efficient Implementation for Calculating Size of Longest Common Subsequence
kinow commented on a change in pull request #233:
URL: https://github.com/apache/commons-text/pull/233#discussion_r683849914
##
File path:
src/test/java/org/apache/commons/text/jmh/LongestCommonSubsequencePerformance.java
##
@@ -0,0 +1,166 @@
+/*
+ * Licensed to the Apache Software Foundation (ASF) under one or more
+ * contributor license agreements. See the NOTICE file distributed with
+ * this work for additional information regarding copyright ownership.
+ * The ASF licenses this file to You under the Apache License, Version 2.0
+ * (the "License"); you may not use this file except in compliance with
+ * the License. You may obtain a copy of the License at
+ *
+ * http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+package org.apache.commons.text.jmh;
+
+import org.apache.commons.lang3.tuple.ImmutablePair;
+import org.apache.commons.lang3.tuple.Pair;
+import org.apache.commons.text.similarity.LongestCommonSubsequence;
+import org.apache.commons.text.similarity.SimilarityScore;
+import org.openjdk.jmh.annotations.Benchmark;
+import org.openjdk.jmh.annotations.BenchmarkMode;
+import org.openjdk.jmh.annotations.Fork;
+import org.openjdk.jmh.annotations.Level;
+import org.openjdk.jmh.annotations.Measurement;
+import org.openjdk.jmh.annotations.Mode;
+import org.openjdk.jmh.annotations.OutputTimeUnit;
+import org.openjdk.jmh.annotations.Scope;
+import org.openjdk.jmh.annotations.Setup;
+import org.openjdk.jmh.annotations.State;
+import org.openjdk.jmh.annotations.Warmup;
+
+import java.io.BufferedReader;
+import java.io.IOException;
+import java.io.InputStream;
+import java.io.InputStreamReader;
+import java.util.ArrayList;
+import java.util.List;
+import java.util.Objects;
+import java.util.concurrent.TimeUnit;
+
+/**
+ * Performance analysis for LongestCommonSubsequence
+ */
+@BenchmarkMode(Mode.AverageTime)
+@OutputTimeUnit(TimeUnit.MILLISECONDS)
+@Warmup(iterations = 5, time = 1)
+@Measurement(iterations = 5, time = 1)
+@Fork(value = 1, jvmArgs = {"-server", "-Xms512M", "-Xmx512M"})
+public class LongestCommonSubsequencePerformance {
+@State(Scope.Benchmark)
+public static class InputData {
+final List> inputs = new
ArrayList<>();
+
+@Setup(Level.Trial)
+public void setup() {
+final ClassLoader classloader =
Thread.currentThread().getContextClassLoader();
+try (InputStream is =
classloader.getResourceAsStream("lcs-perf-analysis-inputs.csv");
+ InputStreamReader isr = new
InputStreamReader(Objects.requireNonNull(is));
+ BufferedReader br = new BufferedReader(isr)) {
+String line;
+while ((line = br.readLine()) != null &&
!line.trim().isEmpty()) {
+line = line.trim();
Review comment:
Checkstyle was complaining about re-assigning `line` in the `while`
block, so I left the double `line.trim` call, which shouldn't really interfere
with the performance tests :+1:
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[GitHub] [commons-text] kinow commented on a change in pull request #233: [TEXT-212] A More Efficient Implementation for Calculating Size of Longest Common Subsequence
kinow commented on a change in pull request #233: URL: https://github.com/apache/commons-text/pull/233#discussion_r683839207 ## File path: src/test/resources/lcs-perf-analysis-inputs.csv ## @@ -0,0 +1,5 @@ +"This code is free software; you can redistribute it and/or modify it","under the terms of the GNU General Public License version 2 only, as" +"You should have received a copy of the GNU General Public License version","2 along with this work; if not, write to the Free Software Foundation," +"Here, the field iterations will be populated with appropriate values from the @Param annotation by the JMH when it is passed to the benchmark method. The @Setup annotated method is invoked before each invocation of the benchmark and creates a new Hasher ensuring isolation. When the execution is finished, we'll get a result similar to the one below: When running microbenchmarks, it's very important to be aware of optimizations. Otherwise, they may affect the","benchmark results in a very misleading way. To make matters a bit more concrete, let's consider an example: We expect object allocation costs more than doing nothing at all. However, if we run the benchmarks: Apparently finding a place in the TLAB, creating and initializing an object is almost free! Just by looking at these numbers, we should know that something does not quite add up here." +"Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. This code is free software; you can redistribute it and/or modify it published by the Free Software Foundation. Oracle designates this This code is distributed in the hope that it will be useful, but WITHOUT FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License You should have received a copy of the GNU General Public License version","Sed ut perspiciatis unde omnis iste natus error sit voluptatem accusantium doloremque laudantium, totam rem aperiam, eaque ipsa quae ab illo inventore veritatis et quasi architecto beatae vitae d icta sunt explicabo. Nemo enim ipsam voluptatem quia voluptas sit aspernatur aut odit aut fugit, sed quia consequuntur magni dolores eos qui ratione voluptatem sequi nesciunt. Neque porro quisquam est, qui dolorem ipsum quia dolor sit amet, consectetur, adipisci velit, sed quia non numquam eius modi tempora incidunt ut labore et dolore magnam aliquam quaerat voluptatem. Ut enim ad minima veniam, quis nostrum exercitationem ullam corporis suscipit laboriosam, nisi ut aliquid ex ea commodi consequatur? Quis autem vel eum iure reprehenderit qui in ea voluptate velit esse quam nihil molestiae consequatur, vel illum qui dolorem eum fugiat quo voluptas nulla pariatur? under the terms of the GNU General Public License version 2 only, as particular file as subject to the *Classpath* exception as provided ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or version 2 for more details (a copy is included in the LICENSE file that 2 along with this work; if not, write to the Fr ee Software Foundation," +"But I must explain to you how all this mistaken idea of denouncing pleasure and praising pain was born and I will give you a complete account of the system, and expound the actual teachings of the great explorer of the truth, the master-builder of human happiness. No one rejects, dislikes, or avoids pleasure itself, because it is pleasure, but because those who do not know how to pursue pleasure rationally encounter consequences that are extremely painful. Nor again is there anyone who loves or pursues or desires to obtain pain of itself, because it is pain, but because occasionally circumstances occur in which toil and pain can procure him some great pleasure. To take a trivial example, which of us ever undertakes laborious physical exercise, except to obtain some advantage from it? But who has any right to find fault with a man who chooses to enjoy a pleasure that has no annoying consequences, or one who avoids a pain that produces no resultant pleasure? Here, the field iteration s will be populated with appropriate values from the @Param annotation by the JMH when it is passed to the benchmark method. The @Setup annotated method is invoked before each invocation of the benchmark and creates a new Hasher ensuring isolation. When the execution is finished, we'll get a result similar to the one below: When running microbenchmarks, it's very important to be aware of optimizations. Otherwise, they may affect the","At vero eos et accusamus et iusto odio dignissimos ducimus qui blanditiis praesentium voluptatum
