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Added implementation of locality-sensitive hashing for near-duplicate…
… detection
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src/main/java/focusedCrawler/minhash/DuplicatePageIndexer.java
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package focusedCrawler.minhash; | ||
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import java.nio.file.Files; | ||
import java.nio.file.Paths; | ||
import java.util.Set; | ||
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import org.slf4j.Logger; | ||
import org.slf4j.LoggerFactory; | ||
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import focusedCrawler.util.Tokenizers; | ||
import focusedCrawler.util.Tokenizers.ShingleTokenizer; | ||
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public class DuplicatePageIndexer { | ||
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public static Logger logger = LoggerFactory.getLogger(DuplicatePageIndexer.class); | ||
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private int numHashes = 256; | ||
private double jaccardThreshold = 0.9d; | ||
private int numberOfShingles = 9; | ||
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private ShingleTokenizer shinglesTokenizer = Tokenizers.shingles(numberOfShingles); | ||
private MinHasher hasher = new MinHasher(numHashes); | ||
private LSH lsh; | ||
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public DuplicatePageIndexer() { | ||
this.lsh = new LSH(numHashes, jaccardThreshold); | ||
} | ||
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public DuplicatePageIndexer(String dataPath) { | ||
this.lsh = new LSH(numHashes, jaccardThreshold, dataPath); | ||
} | ||
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public void insert(String id, String text) throws Exception { | ||
int[] signatures = computeMinHashSignatures(text); | ||
lsh.insert(id, signatures); | ||
} | ||
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public boolean isNearDuplicate(String text) { | ||
Set<String> dupes = findNearDuplicates(text); | ||
return !dupes.isEmpty(); | ||
} | ||
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public Set<String> findNearDuplicates(String text) { | ||
int[] signatures = computeMinHashSignatures(text); | ||
Set<String> dupCandidates = lsh.query(signatures); | ||
return dupCandidates; | ||
} | ||
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private int[] computeMinHashSignatures(String cleanText) { | ||
try { | ||
Set<Integer> hashedShingles = shinglesTokenizer.hashedTokenSet(cleanText); | ||
return hasher.minHashSignature(hashedShingles); | ||
} catch (Exception e) { | ||
logger.warn("Failed to parse clean text into shingles.", e); | ||
return new int[0]; | ||
} | ||
} | ||
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public static void main(String[] args) throws Exception { | ||
DuplicatePageIndexer dpi = new DuplicatePageIndexer(); | ||
String content = new String(Files.readAllBytes(Paths.get("/tmp/ache.html"))); | ||
String content2 = new String(Files.readAllBytes(Paths.get("/tmp/ache-dup.html"))); | ||
dpi.insert("1", content); | ||
System.out.println(dpi.isNearDuplicate(content)); | ||
System.out.println(dpi.isNearDuplicate(content2)); | ||
} | ||
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} |
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package focusedCrawler.minhash; | ||
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import java.util.Collection; | ||
import java.util.HashSet; | ||
import java.util.Set; | ||
import java.util.TreeSet; | ||
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import com.google.common.collect.ArrayListMultimap; | ||
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import focusedCrawler.util.persistence.rocksdb.RocksDBHashtable; | ||
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public class LSH { | ||
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private final int nBands; | ||
private final int nRows; | ||
private final LSHStorage bandsStorage; | ||
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public LSH(int nHashes, double jaccardThreshold) { | ||
this(nHashes, computeNumberOfBandsForThreshold(nHashes, jaccardThreshold)); | ||
} | ||
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public LSH(int nHashes, int nBands) { | ||
this(nHashes, nBands, new InMemoryStorage(nBands)); | ||
} | ||
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public LSH(int nHashes, double jaccardThreshold, String dataPath) { | ||
this(nHashes, computeNumberOfBandsForThreshold(nHashes, jaccardThreshold), new DBStorage(dataPath)); | ||
} | ||
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public LSH(int nHashes, int nBands, String dataPath) { | ||
this(nHashes, nBands, new DBStorage(dataPath)); | ||
} | ||
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public LSH(int nHashes, int nBands, LSHStorage bandsStorage) { | ||
if ((nHashes % nBands) != 0) { | ||
throw new IllegalArgumentException("Bands must divide nHashes (" + nHashes + ") evenly"); | ||
} | ||
this.nBands = nBands; | ||
this.nRows = nHashes / nBands; | ||
this.bandsStorage = bandsStorage; | ||
} | ||
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public double targetThreshold(int nHashes, int nBands) { | ||
return Math.pow(1.0 / nHashes, (1.0 / (nHashes / nBands))); | ||
} | ||
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private static int computeNumberOfBandsForThreshold(int nHashes, double jaccardThreshold) { | ||
int bands = nHashes; | ||
while (bands > 1) { | ||
if ((nHashes % bands) == 0) { | ||
double threshold = Math.pow((double) 1.0 / bands, (double) bands / nHashes); | ||
if (threshold > jaccardThreshold) { | ||
break; | ||
} | ||
} | ||
bands--; | ||
} | ||
return bands; | ||
} | ||
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public void insert(String key, int[] hashes) { | ||
for (int b = 0; b < nBands; b++) { | ||
StringBuffer sb = new StringBuffer(); | ||
for (int r = 0; r < nRows; r++) { | ||
sb.append(Integer.toHexString(hashes[b * nRows + r])); | ||
} | ||
String hh = sb.toString(); | ||
bandsStorage.insertToBand(b, hh, key); | ||
} | ||
} | ||
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public Set<String> query(int[] hashes) { | ||
Set<String> candidates = new HashSet<String>(); | ||
for (int b = 0; b < nBands; b++) { | ||
StringBuffer sb = new StringBuffer(); | ||
for (int r = 0; r < nRows; r++) { | ||
sb.append(Integer.toHexString(hashes[b * nRows + r])); | ||
} | ||
String hh = sb.toString(); | ||
Collection<String> values = bandsStorage.getValues(b, hh); | ||
if (values != null) { | ||
candidates.addAll(values); | ||
} | ||
} | ||
return candidates; | ||
} | ||
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interface LSHStorage { | ||
public void insertToBand(int b, String hh, String key); | ||
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public Collection<String> getValues(int b, String hh); | ||
} | ||
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static class InMemoryStorage implements LSHStorage { | ||
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private final ArrayListMultimap<String, String>[] maps; | ||
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@SuppressWarnings("unchecked") | ||
public InMemoryStorage(int nBands) { | ||
maps = new ArrayListMultimap[nBands]; | ||
for (int i = 0; i < nBands; i++) { | ||
maps[i] = ArrayListMultimap.create(); | ||
} | ||
} | ||
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public void insertToBand(int band, String hexHash, String key) { | ||
maps[band].put(hexHash, key); | ||
} | ||
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public Collection<String> getValues(int band, String hexHash) { | ||
return maps[band].get(hexHash); | ||
} | ||
} | ||
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static class DBStorage implements LSHStorage { | ||
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private final RocksDBHashtable<TreeSet<String>> maps; | ||
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@SuppressWarnings({"unchecked", "rawtypes"}) | ||
public DBStorage(String path) { | ||
maps = new RocksDBHashtable(path, TreeSet.class); | ||
} | ||
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public void insertToBand(int band, String hexHash, String key) { | ||
String hashtableKey = band + hexHash; | ||
TreeSet<String> keysSet = maps.get(hashtableKey); | ||
if (keysSet == null) { | ||
keysSet = new TreeSet<>(); | ||
} | ||
keysSet.add(key); | ||
maps.put(hashtableKey, keysSet); | ||
} | ||
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public Collection<String> getValues(int band, String hexHash) { | ||
String hashtableKey = band + hexHash; | ||
return maps.get(hashtableKey); | ||
} | ||
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} | ||
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} |
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package focusedCrawler.minhash; | ||
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import java.util.HashSet; | ||
import java.util.Random; | ||
import java.util.Set; | ||
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public class MinHasher { | ||
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public final int nextPrime = 2147483587; | ||
public final int maxValue = nextPrime - 1; | ||
public int[] coeffA; | ||
public int[] coeffB; | ||
public int numOfHashes; | ||
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public MinHasher(int numOfHashes) { | ||
this.numOfHashes = numOfHashes; | ||
this.coeffA = pickRandCoefficients(numOfHashes); | ||
this.coeffB = pickRandCoefficients(numOfHashes); | ||
} | ||
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public int[] minHashSignature(Set<Integer> hashedShingles) { | ||
int[] signatures = new int[numOfHashes]; | ||
for (int i = 0; i < numOfHashes; i++) { | ||
int min = nextPrime + 1; | ||
for (int shingle : hashedShingles) { | ||
shingle = shingle % maxValue; | ||
int h = (coeffA[i] * shingle + coeffB[i]) % nextPrime; | ||
if (h < min) { | ||
min = h; | ||
} | ||
} | ||
signatures[i] = min; | ||
} | ||
return signatures; | ||
} | ||
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private int[] pickRandCoefficients(int k) { | ||
int[] rands = new int[k]; | ||
HashSet<Integer> seen = new HashSet<Integer>(k); | ||
Random random = new Random(); | ||
int i = 0; | ||
while (k > 0) { | ||
int randIndex = random.nextInt(maxValue); | ||
while (seen.contains(randIndex)) { | ||
randIndex = random.nextInt(maxValue); | ||
} | ||
rands[i] = randIndex; | ||
seen.add(randIndex); | ||
k = k - 1; | ||
i++; | ||
} | ||
return rands; | ||
} | ||
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} |
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package focusedCrawler.util; | ||
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import java.io.IOException; | ||
import java.util.ArrayList; | ||
import java.util.HashSet; | ||
import java.util.List; | ||
import java.util.Set; | ||
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import org.apache.lucene.analysis.Analyzer; | ||
import org.apache.lucene.analysis.TokenStream; | ||
import org.apache.lucene.analysis.core.SimpleAnalyzer; | ||
import org.apache.lucene.analysis.shingle.ShingleAnalyzerWrapper; | ||
import org.apache.lucene.analysis.tokenattributes.CharTermAttribute; | ||
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import com.google.common.base.Charsets; | ||
import com.google.common.hash.HashFunction; | ||
import com.google.common.hash.Hashing; | ||
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public class Tokenizers { | ||
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private static HashFunction murmur = Hashing.murmur3_32(); | ||
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public static class ShingleTokenizer { | ||
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private Analyzer analyzer; | ||
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public ShingleTokenizer(int size) { | ||
this.analyzer = new ShingleAnalyzerWrapper(new SimpleAnalyzer(), size); | ||
} | ||
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public List<String> tokenize(String cleanText) { | ||
try { | ||
TokenStream ts = analyzer.tokenStream("cleanText", cleanText); | ||
CharTermAttribute cattr = ts.addAttribute(CharTermAttribute.class); | ||
ts.reset(); | ||
List<String> tokens = new ArrayList<String>(); | ||
while (ts.incrementToken()) { | ||
String token = cattr.toString(); | ||
tokens.add(token); | ||
} | ||
ts.close(); | ||
return tokens; | ||
} catch (IOException e) { | ||
throw new RuntimeException("Shigle tokenization failed for string: "+cleanText, e); | ||
} | ||
} | ||
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public Set<String> tokensSet(String cleanText) { | ||
return new HashSet<String>(tokenize(cleanText)); | ||
} | ||
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public Set<Integer> hashedTokenSet(String cleanText) { | ||
HashSet<Integer> hashedTokens = new HashSet<>(); | ||
for(String token : tokenize(cleanText)) { | ||
hashedTokens.add(murmur.hashString(token, Charsets.UTF_8).asInt()); | ||
} | ||
return hashedTokens; | ||
} | ||
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} | ||
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public static ShingleTokenizer shingles(int size) { | ||
return new ShingleTokenizer(size); | ||
} | ||
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} |
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