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From p..@apache.org
Subject [47/51] [partial] mahout git commit: MAHOUT-1655 Refactors mr-legacy into mahout-hdfs and mahout-mr, closes apache/mahout#86
Date Wed, 01 Apr 2015 18:08:18 GMT
http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/RecommenderJob.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/RecommenderJob.java b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/RecommenderJob.java
new file mode 100644
index 0000000..643b2c3
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/RecommenderJob.java
@@ -0,0 +1,337 @@
+/*
+ * 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.mahout.cf.taste.hadoop.item;
+
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.Path;
+import org.apache.hadoop.io.DoubleWritable;
+import org.apache.hadoop.mapreduce.Job;
+import org.apache.hadoop.mapreduce.JobContext;
+import org.apache.hadoop.mapreduce.OutputFormat;
+import org.apache.hadoop.mapreduce.lib.input.MultipleInputs;
+import org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat;
+import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
+import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat;
+import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
+import org.apache.hadoop.util.ToolRunner;
+import org.apache.mahout.cf.taste.hadoop.EntityEntityWritable;
+import org.apache.mahout.cf.taste.hadoop.RecommendedItemsWritable;
+import org.apache.mahout.cf.taste.hadoop.preparation.PreparePreferenceMatrixJob;
+import org.apache.mahout.cf.taste.hadoop.similarity.item.ItemSimilarityJob;
+import org.apache.mahout.common.AbstractJob;
+import org.apache.mahout.common.HadoopUtil;
+import org.apache.mahout.common.iterator.sequencefile.PathType;
+import org.apache.mahout.math.VarIntWritable;
+import org.apache.mahout.math.VarLongWritable;
+import org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob;
+import org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasures;
+
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.atomic.AtomicInteger;
+import java.util.regex.Matcher;
+import java.util.regex.Pattern;
+
+/**
+ * <p>Runs a completely distributed recommender job as a series of mapreduces.</p>
+ * <p/>
+ * <p>Preferences in the input file should look like {@code userID, itemID[, preferencevalue]}</p>
+ * <p/>
+ * <p>
+ * Preference value is optional to accommodate applications that have no notion of a preference value (that is, the user
+ * simply expresses a preference for an item, but no degree of preference).
+ * </p>
+ * <p/>
+ * <p>
+ * The preference value is assumed to be parseable as a {@code double}. The user IDs and item IDs are
+ * parsed as {@code long}s.
+ * </p>
+ * <p/>
+ * <p>Command line arguments specific to this class are:</p>
+ * <p/>
+ * <ol>
+ * <li>--input(path): Directory containing one or more text files with the preference data</li>
+ * <li>--output(path): output path where recommender output should go</li>
+ * <li>--similarityClassname (classname): Name of vector similarity class to instantiate or a predefined similarity
+ * from {@link org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasure}</li>
+ * <li>--usersFile (path): only compute recommendations for user IDs contained in this file (optional)</li>
+ * <li>--itemsFile (path): only include item IDs from this file in the recommendations (optional)</li>
+ * <li>--filterFile (path): file containing comma-separated userID,itemID pairs. Used to exclude the item from the
+ * recommendations for that user (optional)</li>
+ * <li>--numRecommendations (integer): Number of recommendations to compute per user (10)</li>
+ * <li>--booleanData (boolean): Treat input data as having no pref values (false)</li>
+ * <li>--maxPrefsPerUser (integer): Maximum number of preferences considered per user in final
+ *   recommendation phase (10)</li>
+ * <li>--maxSimilaritiesPerItem (integer): Maximum number of similarities considered per item (100)</li>
+ * <li>--minPrefsPerUser (integer): ignore users with less preferences than this in the similarity computation (1)</li>
+ * <li>--maxPrefsPerUserInItemSimilarity (integer): max number of preferences to consider per user in
+ *   the item similarity computation phase,
+ * users with more preferences will be sampled down (1000)</li>
+ * <li>--threshold (double): discard item pairs with a similarity value below this</li>
+ * </ol>
+ * <p/>
+ * <p>General command line options are documented in {@link AbstractJob}.</p>
+ * <p/>
+ * <p>Note that because of how Hadoop parses arguments, all "-D" arguments must appear before all other
+ * arguments.</p>
+ */
+public final class RecommenderJob extends AbstractJob {
+
+  public static final String BOOLEAN_DATA = "booleanData";
+  public static final String DEFAULT_PREPARE_PATH = "preparePreferenceMatrix";
+
+  private static final int DEFAULT_MAX_SIMILARITIES_PER_ITEM = 100;
+  private static final int DEFAULT_MAX_PREFS = 500;
+  private static final int DEFAULT_MIN_PREFS_PER_USER = 1;
+
+  @Override
+  public int run(String[] args) throws Exception {
+
+    addInputOption();
+    addOutputOption();
+    addOption("numRecommendations", "n", "Number of recommendations per user",
+            String.valueOf(AggregateAndRecommendReducer.DEFAULT_NUM_RECOMMENDATIONS));
+    addOption("usersFile", null, "File of users to recommend for", null);
+    addOption("itemsFile", null, "File of items to recommend for", null);
+    addOption("filterFile", "f", "File containing comma-separated userID,itemID pairs. Used to exclude the item from "
+            + "the recommendations for that user (optional)", null);
+    addOption("userItemFile", "uif", "File containing comma-separated userID,itemID pairs (optional). "
+            + "Used to include only these items into recommendations. "
+            + "Cannot be used together with usersFile or itemsFile", null);
+    addOption("booleanData", "b", "Treat input as without pref values", Boolean.FALSE.toString());
+    addOption("maxPrefsPerUser", "mxp",
+            "Maximum number of preferences considered per user in final recommendation phase",
+            String.valueOf(UserVectorSplitterMapper.DEFAULT_MAX_PREFS_PER_USER_CONSIDERED));
+    addOption("minPrefsPerUser", "mp", "ignore users with less preferences than this in the similarity computation "
+            + "(default: " + DEFAULT_MIN_PREFS_PER_USER + ')', String.valueOf(DEFAULT_MIN_PREFS_PER_USER));
+    addOption("maxSimilaritiesPerItem", "m", "Maximum number of similarities considered per item ",
+            String.valueOf(DEFAULT_MAX_SIMILARITIES_PER_ITEM));
+    addOption("maxPrefsInItemSimilarity", "mpiis", "max number of preferences to consider per user or item in the "
+            + "item similarity computation phase, users or items with more preferences will be sampled down (default: "
+        + DEFAULT_MAX_PREFS + ')', String.valueOf(DEFAULT_MAX_PREFS));
+    addOption("similarityClassname", "s", "Name of distributed similarity measures class to instantiate, " 
+            + "alternatively use one of the predefined similarities (" + VectorSimilarityMeasures.list() + ')', true);
+    addOption("threshold", "tr", "discard item pairs with a similarity value below this", false);
+    addOption("outputPathForSimilarityMatrix", "opfsm", "write the item similarity matrix to this path (optional)",
+        false);
+    addOption("randomSeed", null, "use this seed for sampling", false);
+    addFlag("sequencefileOutput", null, "write the output into a SequenceFile instead of a text file");
+
+    Map<String, List<String>> parsedArgs = parseArguments(args);
+    if (parsedArgs == null) {
+      return -1;
+    }
+
+    Path outputPath = getOutputPath();
+    int numRecommendations = Integer.parseInt(getOption("numRecommendations"));
+    String usersFile = getOption("usersFile");
+    String itemsFile = getOption("itemsFile");
+    String filterFile = getOption("filterFile");
+    String userItemFile = getOption("userItemFile");
+    boolean booleanData = Boolean.valueOf(getOption("booleanData"));
+    int maxPrefsPerUser = Integer.parseInt(getOption("maxPrefsPerUser"));
+    int minPrefsPerUser = Integer.parseInt(getOption("minPrefsPerUser"));
+    int maxPrefsInItemSimilarity = Integer.parseInt(getOption("maxPrefsInItemSimilarity"));
+    int maxSimilaritiesPerItem = Integer.parseInt(getOption("maxSimilaritiesPerItem"));
+    String similarityClassname = getOption("similarityClassname");
+    double threshold = hasOption("threshold")
+        ? Double.parseDouble(getOption("threshold")) : RowSimilarityJob.NO_THRESHOLD;
+    long randomSeed = hasOption("randomSeed")
+        ? Long.parseLong(getOption("randomSeed")) : RowSimilarityJob.NO_FIXED_RANDOM_SEED;
+
+
+    Path prepPath = getTempPath(DEFAULT_PREPARE_PATH);
+    Path similarityMatrixPath = getTempPath("similarityMatrix");
+    Path explicitFilterPath = getTempPath("explicitFilterPath");
+    Path partialMultiplyPath = getTempPath("partialMultiply");
+
+    AtomicInteger currentPhase = new AtomicInteger();
+
+    int numberOfUsers = -1;
+
+    if (shouldRunNextPhase(parsedArgs, currentPhase)) {
+      ToolRunner.run(getConf(), new PreparePreferenceMatrixJob(), new String[]{
+        "--input", getInputPath().toString(),
+        "--output", prepPath.toString(),
+        "--minPrefsPerUser", String.valueOf(minPrefsPerUser),
+        "--booleanData", String.valueOf(booleanData),
+        "--tempDir", getTempPath().toString(),
+      });
+
+      numberOfUsers = HadoopUtil.readInt(new Path(prepPath, PreparePreferenceMatrixJob.NUM_USERS), getConf());
+    }
+
+
+    if (shouldRunNextPhase(parsedArgs, currentPhase)) {
+
+      /* special behavior if phase 1 is skipped */
+      if (numberOfUsers == -1) {
+        numberOfUsers = (int) HadoopUtil.countRecords(new Path(prepPath, PreparePreferenceMatrixJob.USER_VECTORS),
+                PathType.LIST, null, getConf());
+      }
+
+      //calculate the co-occurrence matrix
+      ToolRunner.run(getConf(), new RowSimilarityJob(), new String[]{
+        "--input", new Path(prepPath, PreparePreferenceMatrixJob.RATING_MATRIX).toString(),
+        "--output", similarityMatrixPath.toString(),
+        "--numberOfColumns", String.valueOf(numberOfUsers),
+        "--similarityClassname", similarityClassname,
+        "--maxObservationsPerRow", String.valueOf(maxPrefsInItemSimilarity),
+        "--maxObservationsPerColumn", String.valueOf(maxPrefsInItemSimilarity),
+        "--maxSimilaritiesPerRow", String.valueOf(maxSimilaritiesPerItem),
+        "--excludeSelfSimilarity", String.valueOf(Boolean.TRUE),
+        "--threshold", String.valueOf(threshold),
+        "--randomSeed", String.valueOf(randomSeed),
+        "--tempDir", getTempPath().toString(),
+      });
+
+      // write out the similarity matrix if the user specified that behavior
+      if (hasOption("outputPathForSimilarityMatrix")) {
+        Path outputPathForSimilarityMatrix = new Path(getOption("outputPathForSimilarityMatrix"));
+
+        Job outputSimilarityMatrix = prepareJob(similarityMatrixPath, outputPathForSimilarityMatrix,
+            SequenceFileInputFormat.class, ItemSimilarityJob.MostSimilarItemPairsMapper.class,
+            EntityEntityWritable.class, DoubleWritable.class, ItemSimilarityJob.MostSimilarItemPairsReducer.class,
+            EntityEntityWritable.class, DoubleWritable.class, TextOutputFormat.class);
+
+        Configuration mostSimilarItemsConf = outputSimilarityMatrix.getConfiguration();
+        mostSimilarItemsConf.set(ItemSimilarityJob.ITEM_ID_INDEX_PATH_STR,
+            new Path(prepPath, PreparePreferenceMatrixJob.ITEMID_INDEX).toString());
+        mostSimilarItemsConf.setInt(ItemSimilarityJob.MAX_SIMILARITIES_PER_ITEM, maxSimilaritiesPerItem);
+        outputSimilarityMatrix.waitForCompletion(true);
+      }
+    }
+
+    //start the multiplication of the co-occurrence matrix by the user vectors
+    if (shouldRunNextPhase(parsedArgs, currentPhase)) {
+      Job partialMultiply = new Job(getConf(), "partialMultiply");
+      Configuration partialMultiplyConf = partialMultiply.getConfiguration();
+
+      MultipleInputs.addInputPath(partialMultiply, similarityMatrixPath, SequenceFileInputFormat.class,
+                                  SimilarityMatrixRowWrapperMapper.class);
+      MultipleInputs.addInputPath(partialMultiply, new Path(prepPath, PreparePreferenceMatrixJob.USER_VECTORS),
+          SequenceFileInputFormat.class, UserVectorSplitterMapper.class);
+      partialMultiply.setJarByClass(ToVectorAndPrefReducer.class);
+      partialMultiply.setMapOutputKeyClass(VarIntWritable.class);
+      partialMultiply.setMapOutputValueClass(VectorOrPrefWritable.class);
+      partialMultiply.setReducerClass(ToVectorAndPrefReducer.class);
+      partialMultiply.setOutputFormatClass(SequenceFileOutputFormat.class);
+      partialMultiply.setOutputKeyClass(VarIntWritable.class);
+      partialMultiply.setOutputValueClass(VectorAndPrefsWritable.class);
+      partialMultiplyConf.setBoolean("mapred.compress.map.output", true);
+      partialMultiplyConf.set("mapred.output.dir", partialMultiplyPath.toString());
+
+      if (usersFile != null) {
+        partialMultiplyConf.set(UserVectorSplitterMapper.USERS_FILE, usersFile);
+      }
+      
+      if (userItemFile != null) {
+        partialMultiplyConf.set(IDReader.USER_ITEM_FILE, userItemFile);
+      }
+      
+      partialMultiplyConf.setInt(UserVectorSplitterMapper.MAX_PREFS_PER_USER_CONSIDERED, maxPrefsPerUser);
+
+      boolean succeeded = partialMultiply.waitForCompletion(true);
+      if (!succeeded) {
+        return -1;
+      }
+    }
+
+    if (shouldRunNextPhase(parsedArgs, currentPhase)) {
+      //filter out any users we don't care about
+      /* convert the user/item pairs to filter if a filterfile has been specified */
+      if (filterFile != null) {
+        Job itemFiltering = prepareJob(new Path(filterFile), explicitFilterPath, TextInputFormat.class,
+                ItemFilterMapper.class, VarLongWritable.class, VarLongWritable.class,
+                ItemFilterAsVectorAndPrefsReducer.class, VarIntWritable.class, VectorAndPrefsWritable.class,
+                SequenceFileOutputFormat.class);
+        boolean succeeded = itemFiltering.waitForCompletion(true);
+        if (!succeeded) {
+          return -1;
+        }
+      }
+
+      String aggregateAndRecommendInput = partialMultiplyPath.toString();
+      if (filterFile != null) {
+        aggregateAndRecommendInput += "," + explicitFilterPath;
+      }
+
+      Class<? extends OutputFormat> outputFormat = parsedArgs.containsKey("--sequencefileOutput")
+          ? SequenceFileOutputFormat.class : TextOutputFormat.class;
+
+      //extract out the recommendations
+      Job aggregateAndRecommend = prepareJob(
+              new Path(aggregateAndRecommendInput), outputPath, SequenceFileInputFormat.class,
+              PartialMultiplyMapper.class, VarLongWritable.class, PrefAndSimilarityColumnWritable.class,
+              AggregateAndRecommendReducer.class, VarLongWritable.class, RecommendedItemsWritable.class,
+              outputFormat);
+      Configuration aggregateAndRecommendConf = aggregateAndRecommend.getConfiguration();
+      if (itemsFile != null) {
+        aggregateAndRecommendConf.set(AggregateAndRecommendReducer.ITEMS_FILE, itemsFile);
+      }
+      
+      if (userItemFile != null) {
+        aggregateAndRecommendConf.set(IDReader.USER_ITEM_FILE, userItemFile);
+      }
+
+      if (filterFile != null) {
+        setS3SafeCombinedInputPath(aggregateAndRecommend, getTempPath(), partialMultiplyPath, explicitFilterPath);
+      }
+      setIOSort(aggregateAndRecommend);
+      aggregateAndRecommendConf.set(AggregateAndRecommendReducer.ITEMID_INDEX_PATH,
+              new Path(prepPath, PreparePreferenceMatrixJob.ITEMID_INDEX).toString());
+      aggregateAndRecommendConf.setInt(AggregateAndRecommendReducer.NUM_RECOMMENDATIONS, numRecommendations);
+      aggregateAndRecommendConf.setBoolean(BOOLEAN_DATA, booleanData);
+      boolean succeeded = aggregateAndRecommend.waitForCompletion(true);
+      if (!succeeded) {
+        return -1;
+      }
+    }
+
+    return 0;
+  }
+
+  private static void setIOSort(JobContext job) {
+    Configuration conf = job.getConfiguration();
+    conf.setInt("io.sort.factor", 100);
+    String javaOpts = conf.get("mapred.map.child.java.opts"); // new arg name
+    if (javaOpts == null) {
+      javaOpts = conf.get("mapred.child.java.opts"); // old arg name
+    }
+    int assumedHeapSize = 512;
+    if (javaOpts != null) {
+      Matcher m = Pattern.compile("-Xmx([0-9]+)([mMgG])").matcher(javaOpts);
+      if (m.find()) {
+        assumedHeapSize = Integer.parseInt(m.group(1));
+        String megabyteOrGigabyte = m.group(2);
+        if ("g".equalsIgnoreCase(megabyteOrGigabyte)) {
+          assumedHeapSize *= 1024;
+        }
+      }
+    }
+    // Cap this at 1024MB now; see https://issues.apache.org/jira/browse/MAPREDUCE-2308
+    conf.setInt("io.sort.mb", Math.min(assumedHeapSize / 2, 1024));
+    // For some reason the Merger doesn't report status for a long time; increase
+    // timeout when running these jobs
+    conf.setInt("mapred.task.timeout", 60 * 60 * 1000);
+  }
+
+  public static void main(String[] args) throws Exception {
+    ToolRunner.run(new Configuration(), new RecommenderJob(), args);
+  }
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/SimilarityMatrixRowWrapperMapper.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/SimilarityMatrixRowWrapperMapper.java b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/SimilarityMatrixRowWrapperMapper.java
new file mode 100644
index 0000000..8ae8215
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/SimilarityMatrixRowWrapperMapper.java
@@ -0,0 +1,54 @@
+/*
+ * 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.mahout.cf.taste.hadoop.item;
+
+import java.io.IOException;
+
+import org.apache.hadoop.io.IntWritable;
+import org.apache.hadoop.mapreduce.Mapper;
+import org.apache.mahout.math.VarIntWritable;
+import org.apache.mahout.math.Vector;
+import org.apache.mahout.math.VectorWritable;
+
+/**
+ * maps a row of the similarity matrix to a {@link VectorOrPrefWritable}
+ * 
+ * actually a column from that matrix has to be used but as the similarity matrix is symmetric, 
+ * we can use a row instead of having to transpose it
+ */
+public final class SimilarityMatrixRowWrapperMapper extends
+    Mapper<IntWritable,VectorWritable,VarIntWritable,VectorOrPrefWritable> {
+
+  private final VarIntWritable index = new VarIntWritable();
+  private final VectorOrPrefWritable vectorOrPref = new VectorOrPrefWritable();
+
+  @Override
+  protected void map(IntWritable key,
+                     VectorWritable value,
+                     Context context) throws IOException, InterruptedException {
+    Vector similarityMatrixRow = value.get();
+    /* remove self similarity */
+    similarityMatrixRow.set(key.get(), Double.NaN);
+
+    index.set(key.get());
+    vectorOrPref.set(similarityMatrixRow);
+
+    context.write(index, vectorOrPref);
+  }
+
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/ToUserVectorsReducer.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/ToUserVectorsReducer.java b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/ToUserVectorsReducer.java
new file mode 100644
index 0000000..e6e47fd
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/ToUserVectorsReducer.java
@@ -0,0 +1,84 @@
+/*
+ * 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.mahout.cf.taste.hadoop.item;
+
+import java.io.IOException;
+
+import org.apache.hadoop.mapreduce.Reducer;
+import org.apache.mahout.cf.taste.hadoop.EntityPrefWritable;
+import org.apache.mahout.cf.taste.hadoop.TasteHadoopUtils;
+import org.apache.mahout.math.RandomAccessSparseVector;
+import org.apache.mahout.math.VarLongWritable;
+import org.apache.mahout.math.Vector;
+import org.apache.mahout.math.VectorWritable;
+
+/**
+ * <h1>Input</h1>
+ * 
+ * <p>
+ * Takes user IDs as {@link VarLongWritable} mapped to all associated item IDs and preference values, as
+ * {@link EntityPrefWritable}s.
+ * </p>
+ * 
+ * <h1>Output</h1>
+ * 
+ * <p>
+ * The same user ID mapped to a {@link RandomAccessSparseVector} representation of the same item IDs and
+ * preference values. Item IDs are used as vector indexes; they are hashed into ints to work as indexes with
+ * {@link TasteHadoopUtils#idToIndex(long)}. The mapping is remembered for later with a combination of
+ * {@link ItemIDIndexMapper} and {@link ItemIDIndexReducer}.
+ * </p>
+ */
+public final class ToUserVectorsReducer extends
+    Reducer<VarLongWritable,VarLongWritable,VarLongWritable,VectorWritable> {
+
+  public static final String MIN_PREFERENCES_PER_USER = ToUserVectorsReducer.class.getName() 
+      + ".minPreferencesPerUser";
+
+  private int minPreferences;
+
+  public enum Counters { USERS }
+
+  private final VectorWritable userVectorWritable = new VectorWritable();
+
+  @Override
+  protected void setup(Context ctx) throws IOException, InterruptedException {
+    super.setup(ctx);
+    minPreferences = ctx.getConfiguration().getInt(MIN_PREFERENCES_PER_USER, 1);
+  }
+
+  @Override
+  protected void reduce(VarLongWritable userID,
+                        Iterable<VarLongWritable> itemPrefs,
+                        Context context) throws IOException, InterruptedException {
+    Vector userVector = new RandomAccessSparseVector(Integer.MAX_VALUE, 100);
+    for (VarLongWritable itemPref : itemPrefs) {
+      int index = TasteHadoopUtils.idToIndex(itemPref.get());
+      float value = itemPref instanceof EntityPrefWritable ? ((EntityPrefWritable) itemPref).getPrefValue() : 1.0f;
+      userVector.set(index, value);
+    }
+
+    if (userVector.getNumNondefaultElements() >= minPreferences) {
+      userVectorWritable.set(userVector);
+      userVectorWritable.setWritesLaxPrecision(true);
+      context.getCounter(Counters.USERS).increment(1);
+      context.write(userID, userVectorWritable);
+    }
+  }
+  
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/ToVectorAndPrefReducer.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/ToVectorAndPrefReducer.java b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/ToVectorAndPrefReducer.java
new file mode 100644
index 0000000..74d30cb
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/ToVectorAndPrefReducer.java
@@ -0,0 +1,63 @@
+/*
+ * 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.mahout.cf.taste.hadoop.item;
+
+import java.io.IOException;
+import java.util.List;
+
+import com.google.common.collect.Lists;
+import org.apache.hadoop.mapreduce.Reducer;
+import org.apache.mahout.math.VarIntWritable;
+import org.apache.mahout.math.Vector;
+
+public final class ToVectorAndPrefReducer extends
+    Reducer<VarIntWritable,VectorOrPrefWritable,VarIntWritable,VectorAndPrefsWritable> {
+
+  private final VectorAndPrefsWritable vectorAndPrefs = new VectorAndPrefsWritable();
+
+  @Override
+  protected void reduce(VarIntWritable key,
+                        Iterable<VectorOrPrefWritable> values,
+                        Context context) throws IOException, InterruptedException {
+
+    List<Long> userIDs = Lists.newArrayList();
+    List<Float> prefValues = Lists.newArrayList();
+    Vector similarityMatrixColumn = null;
+    for (VectorOrPrefWritable value : values) {
+      if (value.getVector() == null) {
+        // Then this is a user-pref value
+        userIDs.add(value.getUserID());
+        prefValues.add(value.getValue());
+      } else {
+        // Then this is the column vector
+        if (similarityMatrixColumn != null) {
+          throw new IllegalStateException("Found two similarity-matrix columns for item index " + key.get());
+        }
+        similarityMatrixColumn = value.getVector();
+      }
+    }
+
+    if (similarityMatrixColumn == null) {
+      return;
+    }
+
+    vectorAndPrefs.set(similarityMatrixColumn, userIDs, prefValues);
+    context.write(key, vectorAndPrefs);
+  }
+
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/UserVectorSplitterMapper.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/UserVectorSplitterMapper.java b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/UserVectorSplitterMapper.java
new file mode 100644
index 0000000..2290d06
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/UserVectorSplitterMapper.java
@@ -0,0 +1,116 @@
+/*
+ * 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.mahout.cf.taste.hadoop.item;
+
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.mapreduce.Mapper;
+import org.apache.lucene.util.PriorityQueue;
+import org.apache.mahout.cf.taste.impl.common.FastIDSet;
+import org.apache.mahout.math.VarIntWritable;
+import org.apache.mahout.math.VarLongWritable;
+import org.apache.mahout.math.Vector;
+import org.apache.mahout.math.Vector.Element;
+import org.apache.mahout.math.VectorWritable;
+
+import java.io.IOException;
+
+import org.slf4j.Logger;
+import org.slf4j.LoggerFactory;
+
+public final class UserVectorSplitterMapper extends
+    Mapper<VarLongWritable,VectorWritable, VarIntWritable,VectorOrPrefWritable> {
+
+  private static final Logger log = LoggerFactory.getLogger(UserVectorSplitterMapper.class);
+
+  static final String USERS_FILE = "usersFile";
+  static final String MAX_PREFS_PER_USER_CONSIDERED = "maxPrefsPerUserConsidered";
+  static final int DEFAULT_MAX_PREFS_PER_USER_CONSIDERED = 10;
+
+  private int maxPrefsPerUserConsidered;
+  private FastIDSet usersToRecommendFor;
+
+  private final VarIntWritable itemIndexWritable = new VarIntWritable();
+  private final VectorOrPrefWritable vectorOrPref = new VectorOrPrefWritable();
+
+  @Override
+  protected void setup(Context context) throws IOException {
+    Configuration jobConf = context.getConfiguration();
+    maxPrefsPerUserConsidered = jobConf.getInt(MAX_PREFS_PER_USER_CONSIDERED, DEFAULT_MAX_PREFS_PER_USER_CONSIDERED);
+    
+    IDReader idReader = new IDReader (jobConf);
+    idReader.readIDs();
+    usersToRecommendFor = idReader.getUserIds();    
+  }
+
+  @Override
+  protected void map(VarLongWritable key,
+                     VectorWritable value,
+                     Context context) throws IOException, InterruptedException {
+    long userID = key.get();
+
+    log.info("UserID = {}", userID);
+
+    if (usersToRecommendFor != null && !usersToRecommendFor.contains(userID)) {
+      return;
+    }
+    Vector userVector = maybePruneUserVector(value.get());
+
+    for (Element e : userVector.nonZeroes()) {
+      itemIndexWritable.set(e.index());
+      vectorOrPref.set(userID, (float) e.get());
+      context.write(itemIndexWritable, vectorOrPref);
+    }
+  }
+
+  private Vector maybePruneUserVector(Vector userVector) {
+    if (userVector.getNumNondefaultElements() <= maxPrefsPerUserConsidered) {
+      return userVector;
+    }
+
+    float smallestLargeValue = findSmallestLargeValue(userVector);
+
+    // "Blank out" small-sized prefs to reduce the amount of partial products
+    // generated later. They're not zeroed, but NaN-ed, so they come through
+    // and can be used to exclude these items from prefs.
+    for (Element e : userVector.nonZeroes()) {
+      float absValue = Math.abs((float) e.get());
+      if (absValue < smallestLargeValue) {
+        e.set(Float.NaN);
+      }
+    }
+
+    return userVector;
+  }
+
+  private float findSmallestLargeValue(Vector userVector) {
+
+    PriorityQueue<Float> topPrefValues = new PriorityQueue<Float>(maxPrefsPerUserConsidered) {
+      @Override
+      protected boolean lessThan(Float f1, Float f2) {
+        return f1 < f2;
+      }
+    };
+
+    for (Element e : userVector.nonZeroes()) {
+      float absValue = Math.abs((float) e.get());
+      topPrefValues.insertWithOverflow(absValue);
+    }
+    return topPrefValues.top();
+  }
+
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/VectorAndPrefsWritable.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/VectorAndPrefsWritable.java b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/VectorAndPrefsWritable.java
new file mode 100644
index 0000000..495a920
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/VectorAndPrefsWritable.java
@@ -0,0 +1,92 @@
+/*
+ * 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.mahout.cf.taste.hadoop.item;
+
+import java.io.DataInput;
+import java.io.DataOutput;
+import java.io.IOException;
+import java.util.List;
+
+import com.google.common.collect.Lists;
+import org.apache.hadoop.io.Writable;
+import org.apache.mahout.math.Varint;
+import org.apache.mahout.math.Vector;
+import org.apache.mahout.math.VectorWritable;
+
+public final class VectorAndPrefsWritable implements Writable {
+
+  private Vector vector;
+  private List<Long> userIDs;
+  private List<Float> values;
+
+  public VectorAndPrefsWritable() {
+  }
+
+  public VectorAndPrefsWritable(Vector vector, List<Long> userIDs, List<Float> values) {
+    set(vector, userIDs, values);
+  }
+
+  public void set(Vector vector, List<Long> userIDs, List<Float> values) {
+    this.vector = vector;
+    this.userIDs = userIDs;
+    this.values = values;
+  }
+
+  public Vector getVector() {
+    return vector;
+  }
+
+  public List<Long> getUserIDs() {
+    return userIDs;
+  }
+
+  public List<Float> getValues() {
+    return values;
+  }
+
+  @Override
+  public void write(DataOutput out) throws IOException {
+    VectorWritable vw = new VectorWritable(vector);
+    vw.setWritesLaxPrecision(true);
+    vw.write(out);
+    Varint.writeUnsignedVarInt(userIDs.size(), out);
+    for (int i = 0; i < userIDs.size(); i++) {
+      Varint.writeSignedVarLong(userIDs.get(i), out);
+      out.writeFloat(values.get(i));
+    }
+  }
+
+  @Override
+  public void readFields(DataInput in) throws IOException {
+    VectorWritable writable = new VectorWritable();
+    writable.readFields(in);
+    vector = writable.get();
+    int size = Varint.readUnsignedVarInt(in);
+    userIDs = Lists.newArrayListWithCapacity(size);
+    values = Lists.newArrayListWithCapacity(size);
+    for (int i = 0; i < size; i++) {
+      userIDs.add(Varint.readSignedVarLong(in));
+      values.add(in.readFloat());
+    }
+  }
+
+  @Override
+  public String toString() {
+    return vector + "\t" + userIDs + '\t' + values;
+  }
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/VectorOrPrefWritable.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/VectorOrPrefWritable.java b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/VectorOrPrefWritable.java
new file mode 100644
index 0000000..515d7ea
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/item/VectorOrPrefWritable.java
@@ -0,0 +1,104 @@
+/**
+ * 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.mahout.cf.taste.hadoop.item;
+
+import java.io.DataInput;
+import java.io.DataOutput;
+import java.io.IOException;
+
+import org.apache.hadoop.io.Writable;
+import org.apache.mahout.math.Varint;
+import org.apache.mahout.math.Vector;
+import org.apache.mahout.math.VectorWritable;
+
+public final class VectorOrPrefWritable implements Writable {
+
+  private Vector vector;
+  private long userID;
+  private float value;
+
+  public VectorOrPrefWritable() {
+  }
+
+  public VectorOrPrefWritable(Vector vector) {
+    this.vector = vector;
+  }
+
+  public VectorOrPrefWritable(long userID, float value) {
+    this.userID = userID;
+    this.value = value;
+  }
+
+  public Vector getVector() {
+    return vector;
+  }
+
+  public long getUserID() {
+    return userID;
+  }
+
+  public float getValue() {
+    return value;
+  }
+
+  void set(Vector vector) {
+    this.vector = vector;
+    this.userID = Long.MIN_VALUE;
+    this.value = Float.NaN;
+  }
+
+  public void set(long userID, float value) {
+    this.vector = null;
+    this.userID = userID;
+    this.value = value;
+  }
+
+  @Override
+  public void write(DataOutput out) throws IOException {
+    if (vector == null) {
+      out.writeBoolean(false);
+      Varint.writeSignedVarLong(userID, out);
+      out.writeFloat(value);
+    } else {
+      out.writeBoolean(true);
+      VectorWritable vw = new VectorWritable(vector);
+      vw.setWritesLaxPrecision(true);
+      vw.write(out);
+    }
+  }
+
+  @Override
+  public void readFields(DataInput in) throws IOException {
+    boolean hasVector = in.readBoolean();
+    if (hasVector) {
+      VectorWritable writable = new VectorWritable();
+      writable.readFields(in);
+      set(writable.get());
+    } else {
+      long theUserID = Varint.readSignedVarLong(in);
+      float theValue = in.readFloat();
+      set(theUserID, theValue);
+    }
+  }
+
+  @Override
+  public String toString() {
+    return vector == null ? userID + ":" + value : vector.toString();
+  }
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/preparation/PreparePreferenceMatrixJob.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/preparation/PreparePreferenceMatrixJob.java b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/preparation/PreparePreferenceMatrixJob.java
new file mode 100644
index 0000000..c64ee38
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/preparation/PreparePreferenceMatrixJob.java
@@ -0,0 +1,115 @@
+/**
+ * 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.mahout.cf.taste.hadoop.preparation;
+
+import org.apache.hadoop.io.IntWritable;
+import org.apache.hadoop.mapreduce.Job;
+import org.apache.hadoop.mapreduce.lib.input.TextInputFormat;
+import org.apache.hadoop.mapreduce.lib.output.SequenceFileOutputFormat;
+import org.apache.hadoop.util.ToolRunner;
+import org.apache.mahout.cf.taste.hadoop.EntityPrefWritable;
+import org.apache.mahout.cf.taste.hadoop.ToEntityPrefsMapper;
+import org.apache.mahout.cf.taste.hadoop.ToItemPrefsMapper;
+import org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexMapper;
+import org.apache.mahout.cf.taste.hadoop.item.ItemIDIndexReducer;
+import org.apache.mahout.cf.taste.hadoop.item.RecommenderJob;
+import org.apache.mahout.cf.taste.hadoop.item.ToUserVectorsReducer;
+import org.apache.mahout.common.AbstractJob;
+import org.apache.mahout.common.HadoopUtil;
+import org.apache.mahout.math.VarIntWritable;
+import org.apache.mahout.math.VarLongWritable;
+import org.apache.mahout.math.VectorWritable;
+
+import java.util.List;
+import java.util.Map;
+
+public class PreparePreferenceMatrixJob extends AbstractJob {
+
+  public static final String NUM_USERS = "numUsers.bin";
+  public static final String ITEMID_INDEX = "itemIDIndex";
+  public static final String USER_VECTORS = "userVectors";
+  public static final String RATING_MATRIX = "ratingMatrix";
+
+  private static final int DEFAULT_MIN_PREFS_PER_USER = 1;
+
+  public static void main(String[] args) throws Exception {
+    ToolRunner.run(new PreparePreferenceMatrixJob(), args);
+  }
+
+  @Override
+  public int run(String[] args) throws Exception {
+
+    addInputOption();
+    addOutputOption();
+    addOption("minPrefsPerUser", "mp", "ignore users with less preferences than this "
+            + "(default: " + DEFAULT_MIN_PREFS_PER_USER + ')', String.valueOf(DEFAULT_MIN_PREFS_PER_USER));
+    addOption("booleanData", "b", "Treat input as without pref values", Boolean.FALSE.toString());
+    addOption("ratingShift", "rs", "shift ratings by this value", "0.0");
+
+    Map<String, List<String>> parsedArgs = parseArguments(args);
+    if (parsedArgs == null) {
+      return -1;
+    }
+
+    int minPrefsPerUser = Integer.parseInt(getOption("minPrefsPerUser"));
+    boolean booleanData = Boolean.valueOf(getOption("booleanData"));
+    float ratingShift = Float.parseFloat(getOption("ratingShift"));
+    //convert items to an internal index
+    Job itemIDIndex = prepareJob(getInputPath(), getOutputPath(ITEMID_INDEX), TextInputFormat.class,
+            ItemIDIndexMapper.class, VarIntWritable.class, VarLongWritable.class, ItemIDIndexReducer.class,
+            VarIntWritable.class, VarLongWritable.class, SequenceFileOutputFormat.class);
+    itemIDIndex.setCombinerClass(ItemIDIndexReducer.class);
+    boolean succeeded = itemIDIndex.waitForCompletion(true);
+    if (!succeeded) {
+      return -1;
+    }
+    //convert user preferences into a vector per user
+    Job toUserVectors = prepareJob(getInputPath(),
+                                   getOutputPath(USER_VECTORS),
+                                   TextInputFormat.class,
+                                   ToItemPrefsMapper.class,
+                                   VarLongWritable.class,
+                                   booleanData ? VarLongWritable.class : EntityPrefWritable.class,
+                                   ToUserVectorsReducer.class,
+                                   VarLongWritable.class,
+                                   VectorWritable.class,
+                                   SequenceFileOutputFormat.class);
+    toUserVectors.getConfiguration().setBoolean(RecommenderJob.BOOLEAN_DATA, booleanData);
+    toUserVectors.getConfiguration().setInt(ToUserVectorsReducer.MIN_PREFERENCES_PER_USER, minPrefsPerUser);
+    toUserVectors.getConfiguration().set(ToEntityPrefsMapper.RATING_SHIFT, String.valueOf(ratingShift));
+    succeeded = toUserVectors.waitForCompletion(true);
+    if (!succeeded) {
+      return -1;
+    }
+    //we need the number of users later
+    int numberOfUsers = (int) toUserVectors.getCounters().findCounter(ToUserVectorsReducer.Counters.USERS).getValue();
+    HadoopUtil.writeInt(numberOfUsers, getOutputPath(NUM_USERS), getConf());
+    //build the rating matrix
+    Job toItemVectors = prepareJob(getOutputPath(USER_VECTORS), getOutputPath(RATING_MATRIX),
+            ToItemVectorsMapper.class, IntWritable.class, VectorWritable.class, ToItemVectorsReducer.class,
+            IntWritable.class, VectorWritable.class);
+    toItemVectors.setCombinerClass(ToItemVectorsReducer.class);
+
+    succeeded = toItemVectors.waitForCompletion(true);
+    if (!succeeded) {
+      return -1;
+    }
+
+    return 0;
+  }
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/preparation/ToItemVectorsMapper.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/preparation/ToItemVectorsMapper.java b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/preparation/ToItemVectorsMapper.java
new file mode 100644
index 0000000..5a4144c
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/preparation/ToItemVectorsMapper.java
@@ -0,0 +1,56 @@
+/**
+ * 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.mahout.cf.taste.hadoop.preparation;
+
+import org.apache.hadoop.io.IntWritable;
+import org.apache.hadoop.mapreduce.Mapper;
+import org.apache.mahout.cf.taste.hadoop.TasteHadoopUtils;
+import org.apache.mahout.math.RandomAccessSparseVector;
+import org.apache.mahout.math.VarLongWritable;
+import org.apache.mahout.math.Vector;
+import org.apache.mahout.math.VectorWritable;
+
+import java.io.IOException;
+
+public class ToItemVectorsMapper
+    extends Mapper<VarLongWritable,VectorWritable,IntWritable,VectorWritable> {
+
+  private final IntWritable itemID = new IntWritable();
+  private final VectorWritable itemVectorWritable = new VectorWritable();
+
+  @Override
+  protected void map(VarLongWritable rowIndex, VectorWritable vectorWritable, Context ctx)
+    throws IOException, InterruptedException {
+    Vector userRatings = vectorWritable.get();
+
+    int column = TasteHadoopUtils.idToIndex(rowIndex.get());
+
+    itemVectorWritable.setWritesLaxPrecision(true);
+
+    Vector itemVector = new RandomAccessSparseVector(Integer.MAX_VALUE, 1);
+    for (Vector.Element elem : userRatings.nonZeroes()) {
+      itemID.set(elem.index());
+      itemVector.setQuick(column, elem.get());
+      itemVectorWritable.set(itemVector);
+      ctx.write(itemID, itemVectorWritable);
+      // reset vector for reuse
+      itemVector.setQuick(elem.index(), 0.0);
+    }
+  }
+
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/preparation/ToItemVectorsReducer.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/preparation/ToItemVectorsReducer.java b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/preparation/ToItemVectorsReducer.java
new file mode 100644
index 0000000..f74511b
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/preparation/ToItemVectorsReducer.java
@@ -0,0 +1,38 @@
+/**
+ * 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.mahout.cf.taste.hadoop.preparation;
+
+import org.apache.hadoop.io.IntWritable;
+import org.apache.hadoop.mapreduce.Reducer;
+import org.apache.mahout.math.VectorWritable;
+
+import java.io.IOException;
+
+public class ToItemVectorsReducer extends Reducer<IntWritable,VectorWritable,IntWritable,VectorWritable> {
+
+  private final VectorWritable merged = new VectorWritable();
+
+  @Override
+  protected void reduce(IntWritable row, Iterable<VectorWritable> vectors, Context ctx)
+    throws IOException, InterruptedException {
+
+    merged.setWritesLaxPrecision(true);
+    merged.set(VectorWritable.mergeToVector(vectors.iterator()));
+    ctx.write(row, merged);
+  }
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/similarity/item/ItemSimilarityJob.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/similarity/item/ItemSimilarityJob.java b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/similarity/item/ItemSimilarityJob.java
new file mode 100644
index 0000000..c50fa20
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/similarity/item/ItemSimilarityJob.java
@@ -0,0 +1,233 @@
+/**
+ * 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.mahout.cf.taste.hadoop.similarity.item;
+
+import java.io.IOException;
+import java.util.List;
+import java.util.Map;
+import java.util.concurrent.atomic.AtomicInteger;
+
+import com.google.common.base.Preconditions;
+import org.apache.hadoop.conf.Configuration;
+import org.apache.hadoop.fs.Path;
+
+import org.apache.hadoop.io.DoubleWritable;
+import org.apache.hadoop.io.IntWritable;
+import org.apache.hadoop.mapreduce.Job;
+import org.apache.hadoop.mapreduce.Mapper;
+import org.apache.hadoop.mapreduce.Reducer;
+import org.apache.hadoop.mapreduce.lib.input.SequenceFileInputFormat;
+import org.apache.hadoop.mapreduce.lib.output.TextOutputFormat;
+import org.apache.hadoop.util.ToolRunner;
+import org.apache.mahout.cf.taste.hadoop.EntityEntityWritable;
+import org.apache.mahout.cf.taste.hadoop.TasteHadoopUtils;
+import org.apache.mahout.cf.taste.hadoop.preparation.PreparePreferenceMatrixJob;
+import org.apache.mahout.cf.taste.similarity.precompute.SimilarItem;
+import org.apache.mahout.common.AbstractJob;
+import org.apache.mahout.common.HadoopUtil;
+import org.apache.mahout.math.Vector;
+import org.apache.mahout.math.VectorWritable;
+import org.apache.mahout.math.hadoop.similarity.cooccurrence.RowSimilarityJob;
+import org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasures;
+import org.apache.mahout.math.map.OpenIntLongHashMap;
+
+/**
+ * <p>Distributed precomputation of the item-item-similarities for Itembased Collaborative Filtering</p>
+ *
+ * <p>Preferences in the input file should look like {@code userID,itemID[,preferencevalue]}</p>
+ *
+ * <p>
+ * Preference value is optional to accommodate applications that have no notion of a preference value (that is, the user
+ * simply expresses a preference for an item, but no degree of preference).
+ * </p>
+ *
+ * <p>
+ * The preference value is assumed to be parseable as a {@code double}. The user IDs and item IDs are
+ * parsed as {@code long}s.
+ * </p>
+ *
+ * <p>Command line arguments specific to this class are:</p>
+ *
+ * <ol>
+ * <li>--input (path): Directory containing one or more text files with the preference data</li>
+ * <li>--output (path): output path where similarity data should be written</li>
+ * <li>--similarityClassname (classname): Name of distributed similarity measure class to instantiate or a predefined
+ *  similarity from {@link org.apache.mahout.math.hadoop.similarity.cooccurrence.measures.VectorSimilarityMeasure}</li>
+ * <li>--maxSimilaritiesPerItem (integer): Maximum number of similarities considered per item (100)</li>
+ * <li>--maxPrefsPerUser (integer): max number of preferences to consider per user, users with more preferences will
+ *  be sampled down (1000)</li>
+ * <li>--minPrefsPerUser (integer): ignore users with less preferences than this (1)</li>
+ * <li>--booleanData (boolean): Treat input data as having no pref values (false)</li>
+ * <li>--threshold (double): discard item pairs with a similarity value below this</li>
+ * </ol>
+ *
+ * <p>General command line options are documented in {@link AbstractJob}.</p>
+ *
+ * <p>Note that because of how Hadoop parses arguments, all "-D" arguments must appear before all other arguments.</p>
+ */
+public final class ItemSimilarityJob extends AbstractJob {
+
+  public static final String ITEM_ID_INDEX_PATH_STR = ItemSimilarityJob.class.getName() + ".itemIDIndexPathStr";
+  public static final String MAX_SIMILARITIES_PER_ITEM = ItemSimilarityJob.class.getName() + ".maxSimilarItemsPerItem";
+
+  private static final int DEFAULT_MAX_SIMILAR_ITEMS_PER_ITEM = 100;
+  private static final int DEFAULT_MAX_PREFS = 500;
+  private static final int DEFAULT_MIN_PREFS_PER_USER = 1;
+
+  public static void main(String[] args) throws Exception {
+    ToolRunner.run(new ItemSimilarityJob(), args);
+  }
+  
+  @Override
+  public int run(String[] args) throws Exception {
+
+    addInputOption();
+    addOutputOption();
+    addOption("similarityClassname", "s", "Name of distributed similarity measures class to instantiate, " 
+        + "alternatively use one of the predefined similarities (" + VectorSimilarityMeasures.list() + ')');
+    addOption("maxSimilaritiesPerItem", "m", "try to cap the number of similar items per item to this number "
+        + "(default: " + DEFAULT_MAX_SIMILAR_ITEMS_PER_ITEM + ')',
+        String.valueOf(DEFAULT_MAX_SIMILAR_ITEMS_PER_ITEM));
+    addOption("maxPrefs", "mppu", "max number of preferences to consider per user or item, " 
+        + "users or items with more preferences will be sampled down (default: " + DEFAULT_MAX_PREFS + ')',
+        String.valueOf(DEFAULT_MAX_PREFS));
+    addOption("minPrefsPerUser", "mp", "ignore users with less preferences than this "
+        + "(default: " + DEFAULT_MIN_PREFS_PER_USER + ')', String.valueOf(DEFAULT_MIN_PREFS_PER_USER));
+    addOption("booleanData", "b", "Treat input as without pref values", String.valueOf(Boolean.FALSE));
+    addOption("threshold", "tr", "discard item pairs with a similarity value below this", false);
+    addOption("randomSeed", null, "use this seed for sampling", false);
+
+    Map<String,List<String>> parsedArgs = parseArguments(args);
+    if (parsedArgs == null) {
+      return -1;
+    }
+
+    String similarityClassName = getOption("similarityClassname");
+    int maxSimilarItemsPerItem = Integer.parseInt(getOption("maxSimilaritiesPerItem"));
+    int maxPrefs = Integer.parseInt(getOption("maxPrefs"));
+    int minPrefsPerUser = Integer.parseInt(getOption("minPrefsPerUser"));
+    boolean booleanData = Boolean.valueOf(getOption("booleanData"));
+
+    double threshold = hasOption("threshold")
+        ? Double.parseDouble(getOption("threshold")) : RowSimilarityJob.NO_THRESHOLD;
+    long randomSeed = hasOption("randomSeed")
+        ? Long.parseLong(getOption("randomSeed")) : RowSimilarityJob.NO_FIXED_RANDOM_SEED;
+
+    Path similarityMatrixPath = getTempPath("similarityMatrix");
+    Path prepPath = getTempPath("prepareRatingMatrix");
+
+    AtomicInteger currentPhase = new AtomicInteger();
+
+    if (shouldRunNextPhase(parsedArgs, currentPhase)) {
+      ToolRunner.run(getConf(), new PreparePreferenceMatrixJob(), new String[] {
+        "--input", getInputPath().toString(),
+        "--output", prepPath.toString(),
+        "--minPrefsPerUser", String.valueOf(minPrefsPerUser),
+        "--booleanData", String.valueOf(booleanData),
+        "--tempDir", getTempPath().toString(),
+      });
+    }
+
+    if (shouldRunNextPhase(parsedArgs, currentPhase)) {
+      int numberOfUsers = HadoopUtil.readInt(new Path(prepPath, PreparePreferenceMatrixJob.NUM_USERS), getConf());
+
+      ToolRunner.run(getConf(), new RowSimilarityJob(), new String[] {
+        "--input", new Path(prepPath, PreparePreferenceMatrixJob.RATING_MATRIX).toString(),
+        "--output", similarityMatrixPath.toString(),
+        "--numberOfColumns", String.valueOf(numberOfUsers),
+        "--similarityClassname", similarityClassName,
+        "--maxObservationsPerRow", String.valueOf(maxPrefs),
+        "--maxObservationsPerColumn", String.valueOf(maxPrefs),
+        "--maxSimilaritiesPerRow", String.valueOf(maxSimilarItemsPerItem),
+        "--excludeSelfSimilarity", String.valueOf(Boolean.TRUE),
+        "--threshold", String.valueOf(threshold),
+        "--randomSeed", String.valueOf(randomSeed),
+        "--tempDir", getTempPath().toString(),
+      });
+    }
+
+    if (shouldRunNextPhase(parsedArgs, currentPhase)) {
+      Job mostSimilarItems = prepareJob(similarityMatrixPath, getOutputPath(), SequenceFileInputFormat.class,
+          MostSimilarItemPairsMapper.class, EntityEntityWritable.class, DoubleWritable.class,
+          MostSimilarItemPairsReducer.class, EntityEntityWritable.class, DoubleWritable.class, TextOutputFormat.class);
+      Configuration mostSimilarItemsConf = mostSimilarItems.getConfiguration();
+      mostSimilarItemsConf.set(ITEM_ID_INDEX_PATH_STR,
+          new Path(prepPath, PreparePreferenceMatrixJob.ITEMID_INDEX).toString());
+      mostSimilarItemsConf.setInt(MAX_SIMILARITIES_PER_ITEM, maxSimilarItemsPerItem);
+      boolean succeeded = mostSimilarItems.waitForCompletion(true);
+      if (!succeeded) {
+        return -1;
+      }
+    }
+
+    return 0;
+  }
+
+  public static class MostSimilarItemPairsMapper
+      extends Mapper<IntWritable,VectorWritable,EntityEntityWritable,DoubleWritable> {
+
+    private OpenIntLongHashMap indexItemIDMap;
+    private int maxSimilarItemsPerItem;
+
+    @Override
+    protected void setup(Context ctx) {
+      Configuration conf = ctx.getConfiguration();
+      maxSimilarItemsPerItem = conf.getInt(MAX_SIMILARITIES_PER_ITEM, -1);
+      indexItemIDMap = TasteHadoopUtils.readIDIndexMap(conf.get(ITEM_ID_INDEX_PATH_STR), conf);
+
+      Preconditions.checkArgument(maxSimilarItemsPerItem > 0, "maxSimilarItemsPerItem must be greater then 0!");
+    }
+
+    @Override
+    protected void map(IntWritable itemIDIndexWritable, VectorWritable similarityVector, Context ctx)
+      throws IOException, InterruptedException {
+
+      int itemIDIndex = itemIDIndexWritable.get();
+
+      TopSimilarItemsQueue topKMostSimilarItems = new TopSimilarItemsQueue(maxSimilarItemsPerItem);
+
+      for (Vector.Element element : similarityVector.get().nonZeroes()) {
+        SimilarItem top = topKMostSimilarItems.top();
+        double candidateSimilarity = element.get();
+        if (candidateSimilarity > top.getSimilarity()) {
+          top.set(indexItemIDMap.get(element.index()), candidateSimilarity);
+          topKMostSimilarItems.updateTop();
+        }
+      }
+
+      long itemID = indexItemIDMap.get(itemIDIndex);
+      for (SimilarItem similarItem : topKMostSimilarItems.getTopItems()) {
+        long otherItemID = similarItem.getItemID();
+        if (itemID < otherItemID) {
+          ctx.write(new EntityEntityWritable(itemID, otherItemID), new DoubleWritable(similarItem.getSimilarity()));
+        } else {
+          ctx.write(new EntityEntityWritable(otherItemID, itemID), new DoubleWritable(similarItem.getSimilarity()));
+        }
+      }
+    }
+  }
+
+  public static class MostSimilarItemPairsReducer
+      extends Reducer<EntityEntityWritable,DoubleWritable,EntityEntityWritable,DoubleWritable> {
+    @Override
+    protected void reduce(EntityEntityWritable pair, Iterable<DoubleWritable> values, Context ctx)
+      throws IOException, InterruptedException {
+      ctx.write(pair, values.iterator().next());
+    }
+  }
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/similarity/item/TopSimilarItemsQueue.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/similarity/item/TopSimilarItemsQueue.java b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/similarity/item/TopSimilarItemsQueue.java
new file mode 100644
index 0000000..b0ba24d
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/hadoop/similarity/item/TopSimilarItemsQueue.java
@@ -0,0 +1,60 @@
+/**
+ * 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.mahout.cf.taste.hadoop.similarity.item;
+
+import com.google.common.collect.Lists;
+import org.apache.lucene.util.PriorityQueue;
+import org.apache.mahout.cf.taste.similarity.precompute.SimilarItem;
+
+import java.util.Collections;
+import java.util.List;
+
+public class TopSimilarItemsQueue extends PriorityQueue<SimilarItem> {
+
+  private static final long SENTINEL_ID = Long.MIN_VALUE;
+
+  private final int maxSize;
+
+  public TopSimilarItemsQueue(int maxSize) {
+    super(maxSize);
+    this.maxSize = maxSize;
+  }
+
+  public List<SimilarItem> getTopItems() {
+    List<SimilarItem> items = Lists.newArrayListWithCapacity(maxSize);
+    while (size() > 0) {
+      SimilarItem topItem = pop();
+      // filter out "sentinel" objects necessary for maintaining an efficient priority queue
+      if (topItem.getItemID() != SENTINEL_ID) {
+        items.add(topItem);
+      }
+    }
+    Collections.reverse(items);
+    return items;
+  }
+
+  @Override
+  protected boolean lessThan(SimilarItem one, SimilarItem two) {
+    return one.getSimilarity() < two.getSimilarity();
+  }
+
+  @Override
+  protected SimilarItem getSentinelObject() {
+    return new SimilarItem(SENTINEL_ID, Double.MIN_VALUE);
+  }
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/impl/common/AbstractLongPrimitiveIterator.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/impl/common/AbstractLongPrimitiveIterator.java b/mr/src/main/java/org/apache/mahout/cf/taste/impl/common/AbstractLongPrimitiveIterator.java
new file mode 100644
index 0000000..f46785c
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/impl/common/AbstractLongPrimitiveIterator.java
@@ -0,0 +1,27 @@
+/**
+ * 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.mahout.cf.taste.impl.common;
+
+public abstract class AbstractLongPrimitiveIterator implements LongPrimitiveIterator {
+  
+  @Override
+  public Long next() {
+    return nextLong();
+  }
+  
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/impl/common/BitSet.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/impl/common/BitSet.java b/mr/src/main/java/org/apache/mahout/cf/taste/impl/common/BitSet.java
new file mode 100644
index 0000000..c46b4b6
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/impl/common/BitSet.java
@@ -0,0 +1,93 @@
+/**
+ * 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.mahout.cf.taste.impl.common;
+
+import java.io.Serializable;
+import java.util.Arrays;
+
+/** A simplified and streamlined version of {@link java.util.BitSet}. */
+final class BitSet implements Serializable, Cloneable {
+  
+  private final long[] bits;
+  
+  BitSet(int numBits) {
+    int numLongs = numBits >>> 6;
+    if ((numBits & 0x3F) != 0) {
+      numLongs++;
+    }
+    bits = new long[numLongs];
+  }
+  
+  private BitSet(long[] bits) {
+    this.bits = bits;
+  }
+  
+  boolean get(int index) {
+    // skipping range check for speed
+    return (bits[index >>> 6] & 1L << (index & 0x3F)) != 0L;
+  }
+  
+  void set(int index) {
+    // skipping range check for speed
+    bits[index >>> 6] |= 1L << (index & 0x3F);
+  }
+  
+  void clear(int index) {
+    // skipping range check for speed
+    bits[index >>> 6] &= ~(1L << (index & 0x3F));
+  }
+  
+  void clear() {
+    int length = bits.length;
+    for (int i = 0; i < length; i++) {
+      bits[i] = 0L;
+    }
+  }
+  
+  @Override
+  public BitSet clone() {
+    return new BitSet(bits.clone());
+  }
+
+  @Override
+  public int hashCode() {
+    return Arrays.hashCode(bits);
+  }
+
+  @Override
+  public boolean equals(Object o) {
+    if (!(o instanceof BitSet)) {
+      return false;
+    }
+    BitSet other = (BitSet) o;
+    return Arrays.equals(bits, other.bits);
+  }
+  
+  @Override
+  public String toString() {
+    StringBuilder result = new StringBuilder(64 * bits.length);
+    for (long l : bits) {
+      for (int j = 0; j < 64; j++) {
+        result.append((l & 1L << j) == 0 ? '0' : '1');
+      }
+      result.append(' ');
+    }
+    return result.toString();
+  }
+  
+}

http://git-wip-us.apache.org/repos/asf/mahout/blob/b988c493/mr/src/main/java/org/apache/mahout/cf/taste/impl/common/Cache.java
----------------------------------------------------------------------
diff --git a/mr/src/main/java/org/apache/mahout/cf/taste/impl/common/Cache.java b/mr/src/main/java/org/apache/mahout/cf/taste/impl/common/Cache.java
new file mode 100755
index 0000000..9f2a30b
--- /dev/null
+++ b/mr/src/main/java/org/apache/mahout/cf/taste/impl/common/Cache.java
@@ -0,0 +1,178 @@
+/**
+ * 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.mahout.cf.taste.impl.common;
+
+import com.google.common.base.Preconditions;
+import org.apache.mahout.cf.taste.common.TasteException;
+
+import java.util.Iterator;
+
+/**
+ * <p>
+ * An efficient Map-like class which caches values for keys. Values are not "put" into a {@link Cache};
+ * instead the caller supplies the instance with an implementation of {@link Retriever} which can load the
+ * value for a given key.
+ * </p>
+ *
+ * <p>
+ * The cache does not support {@code null} keys.
+ * </p>
+ *
+ * <p>
+ * Thanks to Amila Jayasooriya for helping evaluate performance of the rewrite of this class, as part of a
+ * Google Summer of Code 2007 project.
+ * </p>
+ */
+public final class Cache<K,V> implements Retriever<K,V> {
+
+  private static final Object NULL = new Object();
+  
+  private final FastMap<K,V> cache;
+  private final Retriever<? super K,? extends V> retriever;
+  
+  /**
+   * <p>
+   * Creates a new cache based on the given {@link Retriever}.
+   * </p>
+   * 
+   * @param retriever
+   *          object which can retrieve values for keys
+   */
+  public Cache(Retriever<? super K,? extends V> retriever) {
+    this(retriever, FastMap.NO_MAX_SIZE);
+  }
+  
+  /**
+   * <p>
+   * Creates a new cache based on the given {@link Retriever} and with given maximum size.
+   * </p>
+   * 
+   * @param retriever
+   *          object which can retrieve values for keys
+   * @param maxEntries
+   *          maximum number of entries the cache will store before evicting some
+   */
+  public Cache(Retriever<? super K,? extends V> retriever, int maxEntries) {
+    Preconditions.checkArgument(retriever != null, "retriever is null");
+    Preconditions.checkArgument(maxEntries >= 1, "maxEntries must be at least 1");
+    cache = new FastMap<K, V>(11, maxEntries);
+    this.retriever = retriever;
+  }
+  
+  /**
+   * <p>
+   * Returns cached value for a key. If it does not exist, it is loaded using a {@link Retriever}.
+   * </p>
+   * 
+   * @param key
+   *          cache key
+   * @return value for that key
+   * @throws TasteException
+   *           if an exception occurs while retrieving a new cached value
+   */
+  @Override
+  public V get(K key) throws TasteException {
+    V value;
+    synchronized (cache) {
+      value = cache.get(key);
+    }
+    if (value == null) {
+      return getAndCacheValue(key);
+    }
+    return value == NULL ? null : value;
+  }
+  
+  /**
+   * <p>
+   * Uncaches any existing value for a given key.
+   * </p>
+   * 
+   * @param key
+   *          cache key
+   */
+  public void remove(K key) {
+    synchronized (cache) {
+      cache.remove(key);
+    }
+  }
+
+  /**
+   * Clears all cache entries whose key matches the given predicate.
+   */
+  public void removeKeysMatching(MatchPredicate<K> predicate) {
+    synchronized (cache) {
+      Iterator<K> it = cache.keySet().iterator();
+      while (it.hasNext()) {
+        K key = it.next();
+        if (predicate.matches(key)) {
+          it.remove();
+        }
+      }
+    }
+  }
+
+  /**
+   * Clears all cache entries whose value matches the given predicate.
+   */
+  public void removeValueMatching(MatchPredicate<V> predicate) {
+    synchronized (cache) {
+      Iterator<V> it = cache.values().iterator();
+      while (it.hasNext()) {
+        V value = it.next();
+        if (predicate.matches(value)) {
+          it.remove();
+        }
+      }
+    }
+  }
+  
+  /**
+   * <p>
+   * Clears the cache.
+   * </p>
+   */
+  public void clear() {
+    synchronized (cache) {
+      cache.clear();
+    }
+  }
+  
+  private V getAndCacheValue(K key) throws TasteException {
+    V value = retriever.get(key);
+    if (value == null) {
+      value = (V) NULL;
+    }
+    synchronized (cache) {
+      cache.put(key, value);
+    }
+    return value;
+  }
+  
+  @Override
+  public String toString() {
+    return "Cache[retriever:" + retriever + ']';
+  }
+
+  /**
+   * Used by {#link #removeKeysMatching(Object)} to decide things that are matching.
+   */
+  public interface MatchPredicate<T> {
+    boolean matches(T thing);
+  }
+  
+}


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