Example usage for java.util HashSet size

List of usage examples for java.util HashSet size

Introduction

In this page you can find the example usage for java.util HashSet size.

Prototype

public int size() 

Source Link

Document

Returns the number of elements in this set (its cardinality).

Usage

From source file:expansionBlocks.ProcessCommunities.java

public static Pair<Map<Entity, Double>, Map<Entity, Double>> execute(Configuration configuration, Query query)
        throws Exception {
    Map<Set<Long>, Map<Entity, Double>> mapPathCommunities = query.getCommunities();
    HashSet<Map<Entity, Double>> initialCommunities = new HashSet<>(mapPathCommunities.values());

    Set<Map<Entity, Double>> scaledCommunities = new HashSet<>();

    AbstractCommunityScalator as = configuration.getAbstractCommunityScalator();

    for (Map<Entity, Double> community : initialCommunities) {
        Map<Entity, Double> scaledCommunity = as.scaledEmphasisArticlesInCommunity(configuration, query,
                community);//from ww  w. j  av  a  2s. c om
        scaledCommunities.add(scaledCommunity);
    }

    Set<Map<Entity, Double>> communitiesFusioned = getCommunitiesFromCommunitiesBasedOnSimilarity(
            scaledCommunities, configuration.getFusionThreshold());
    if (configuration.DEBUG_INFO) {
        println("Fusion communities based on similarity communities: ");
        for (Map<Entity, Double> community : communitiesFusioned) {
            println(community);

        }
    }
    println(initialCommunities.size() + " communities have been fusioned into " + communitiesFusioned.size());

    println("[[WARNING]] - Select best community algorithm seems to differ from select best path. You may want to double ckeck it.");
    Set<Map<Entity, Double>> selectBestCommunities = selectBestCommunities(configuration, communitiesFusioned,
            query.getTokenNames());

    if (configuration.DEBUG_INFO) {
        println("Selected best communities: ");
        for (Map<Entity, Double> community : selectBestCommunities) {
            println(StringUtilsQueryExpansion.MapDoubleValueToString(community));
        }
    }

    Map<Entity, Double> result = agregateCommunities(selectBestCommunities);

    if (configuration.DEBUG_INFO) {
        println("Agragated community(size: " + result.size() + "): ");
        println(StringUtilsQueryExpansion.MapDoubleValueToString(result));
    }

    Set<Entity> entitiesToRemove = new HashSet<>();
    /*for (Map.Entry<Entity, Double> e : result.entrySet())
     {
     Set<Category> categories = e.getKey().getCategories();
     println("Categories of \"" + e.getKey() + "\": " + categories);
     if (categories.isEmpty())
     entitiesToRemove.add(e.getKey());
     }*/

    entitiesToRemove.addAll(removableAccordingToCategories(result));

    Map<Entity, Double> filteredCommunity = new HashMap<>(result);
    for (Entity e : entitiesToRemove) {
        filteredCommunity.remove(e);
    }
    println("Based on category analisy I would suggest to remove: " + entitiesToRemove);
    println("New Community  in case of category based filtering"
            + StringUtilsQueryExpansion.MapDoubleValueToString(filteredCommunity));

    query.setCommunityAfterRemoval(filteredCommunity);
    query.setCommunity(result);
    return new Pair<>(result, filteredCommunity);

}

From source file:com.ibm.bi.dml.runtime.matrix.CMCOVMR.java

public static JobReturn runJob(MRJobInstruction inst, String[] inputs, InputInfo[] inputInfos, long[] rlens,
        long[] clens, int[] brlens, int[] bclens, String instructionsInMapper, String cmNcomInstructions,
        int numReducers, int replication, byte[] resultIndexes, String[] outputs, OutputInfo[] outputInfos)
        throws Exception {
    JobConf job = new JobConf(CMCOVMR.class);
    job.setJobName("CM-COV-MR");

    //whether use block representation or cell representation
    MRJobConfiguration.setMatrixValueClassForCM_N_COM(job, true);

    //added for handling recordreader instruction
    String[] realinputs = inputs;
    InputInfo[] realinputInfos = inputInfos;
    long[] realrlens = rlens;
    long[] realclens = clens;
    int[] realbrlens = brlens;
    int[] realbclens = bclens;
    byte[] realIndexes = new byte[inputs.length];
    for (byte b = 0; b < realIndexes.length; b++)
        realIndexes[b] = b;//  w  ww . j  a  v  a  2s.c o m

    //set up the input files and their format information
    MRJobConfiguration.setUpMultipleInputs(job, realIndexes, realinputs, realinputInfos, realbrlens, realbclens,
            true, ConvertTarget.WEIGHTEDCELL);

    //set up the dimensions of input matrices
    MRJobConfiguration.setMatricesDimensions(job, realIndexes, realrlens, realclens);

    //set up the block size
    MRJobConfiguration.setBlocksSizes(job, realIndexes, realbrlens, realbclens);

    //set up unary instructions that will perform in the mapper
    MRJobConfiguration.setInstructionsInMapper(job, instructionsInMapper);

    //set up the aggregate instructions that will happen in the combiner and reducer
    MRJobConfiguration.setCM_N_COMInstructions(job, cmNcomInstructions);

    //set up the replication factor for the results
    job.setInt("dfs.replication", replication);

    //set up what matrices are needed to pass from the mapper to reducer
    HashSet<Byte> mapoutputIndexes = MRJobConfiguration.setUpOutputIndexesForMapper(job, realIndexes,
            instructionsInMapper, null, cmNcomInstructions, resultIndexes);

    //set up the multiple output files, and their format information
    MRJobConfiguration.setUpMultipleOutputs(job, resultIndexes, new byte[resultIndexes.length], outputs,
            outputInfos, false);

    // configure mapper and the mapper output key value pairs
    job.setMapperClass(CMCOVMRMapper.class);

    job.setMapOutputKeyClass(TaggedFirstSecondIndexes.class);
    job.setMapOutputValueClass(CM_N_COVCell.class);
    job.setOutputKeyComparatorClass(TaggedFirstSecondIndexes.Comparator.class);
    job.setPartitionerClass(TaggedFirstSecondIndexes.TagPartitioner.class);

    //configure reducer
    job.setReducerClass(CMCOVMRReducer.class);
    //job.setReducerClass(PassThroughReducer.class);

    MatrixCharacteristics[] stats = MRJobConfiguration.computeMatrixCharacteristics(job, realIndexes,
            instructionsInMapper, null, null, cmNcomInstructions, resultIndexes, mapoutputIndexes, false).stats;

    //set up the number of reducers
    MRJobConfiguration.setNumReducers(job, mapoutputIndexes.size(), numReducers);//each output tag is a group

    // Print the complete instruction
    if (LOG.isTraceEnabled())
        inst.printCompleteMRJobInstruction(stats);

    // By default, the job executes in "cluster" mode.
    // Determine if we can optimize and run it in "local" mode.
    MatrixCharacteristics[] inputStats = new MatrixCharacteristics[inputs.length];
    for (int i = 0; i < inputs.length; i++) {
        inputStats[i] = new MatrixCharacteristics(rlens[i], clens[i], brlens[i], bclens[i]);
    }

    //set unique working dir
    MRJobConfiguration.setUniqueWorkingDir(job);

    RunningJob runjob = JobClient.runJob(job);

    return new JobReturn(stats, outputInfos, runjob.isSuccessful());
}

From source file:gov.nih.nci.firebird.data.AnnualRegistrationPersistenceTest.java

@Test
public void testNotificationEmailAddresses() {
    AnnualRegistration registration = createNewRegistration();
    String email1 = ValueGenerator.getUniqueEmailAddress();
    String email2 = ValueGenerator.getUniqueEmailAddress();
    String email3 = ValueGenerator.getUniqueEmailAddress();
    HashSet<String> emailsAsSet = Sets.newHashSet(email1, email2, email3);
    registration.getNotificationEmailAddresses().addAll(emailsAsSet);
    saveAndFlush(registration);/*from w  w w  .  ja va  2  s  .c o m*/

    AnnualRegistration retrievedRegistration = reloadObject(registration);
    assertEquals(emailsAsSet.size(), retrievedRegistration.getNotificationEmailAddresses().size());
    assertTrue(retrievedRegistration.getNotificationEmailAddresses().containsAll(emailsAsSet));
}

From source file:opennlp.tools.parse_thicket.opinion_processor.StopList.java

public String getRandomFirstName() {
    HashSet<String> firstNames = m_stopHash.get("FIRST_NAMES");
    int indexRand = (int) (Math.random() * new Float(firstNames.size()));
    Iterator iter = firstNames.iterator();
    for (int i = 0; i < indexRand; i++) {
        iter.next();//from ww  w . j a  va 2  s .com
    }
    return ((String) iter.next()).toLowerCase();
}

From source file:org.cloudgraph.hbase.mutation.Update.java

@Override
public void collect(DataGraph dataGraph, PlasmaDataObject dataObject, DistributedWriter graphWriter,
        TableWriter tableWriter, RowWriter rowWriter) throws IllegalAccessException, IOException {
    PlasmaType type = (PlasmaType) dataObject.getType();
    CoreNode dataNode = (CoreNode) dataObject;
    // FIXME: get rid of cast - define instance properties in 'base type'
    Timestamp snapshotDate = (Timestamp) dataNode.getValue(CoreConstants.PROPERTY_NAME_SNAPSHOT_TIMESTAMP);
    if (snapshotDate == null)
        throw new RequiredPropertyException(
                "instance property '" + CoreConstants.PROPERTY_NAME_SNAPSHOT_TIMESTAMP
                        + "' is required to update data object, " + dataObject);
    if (log.isDebugEnabled())
        log.debug(dataObject + " timestamp: " + String.valueOf(snapshotDate));

    Long sequence = (Long) dataNode.getValue(CloudGraphConstants.SEQUENCE);
    if (sequence == null)
        throw new RequiredPropertyException("instance property '" + CloudGraphConstants.SEQUENCE
                + "' is required to update data object, " + dataObject);

    if (log.isDebugEnabled())
        log.debug(dataObject + " (seq: " + sequence + ")");

    List<Setting> settingList = dataGraph.getChangeSummary().getOldValues(dataObject);
    HashSet<PlasmaProperty> properties = this.collectProperties(settingList);
    Iterator<PlasmaProperty> iter = properties.iterator();
    while (iter.hasNext()) {
        PlasmaProperty property = iter.next();

        if (property.getConcurrent() != null)
            return; // processed above

        if (property.isReadOnly())
            throw new IllegalAccessException("attempt to modify read-only property, " + property);

        Object dataValue = dataObject.get(property);
        if (dataValue != null)
            if (log.isDebugEnabled())
                log.debug("updating " + property.toString());
            else if (log.isDebugEnabled())
                log.debug("removing " + property.toString());

        if (!property.getType().isDataType()) {
            SettingCollector<PlasmaDataObject> settingCollector = new SettingCollector<>();
            HashSet<PlasmaDataObject> oldSettings = settingCollector.collect(property, settingList);
            HashSet<PlasmaDataObject> oldValues = new HashSet<>(oldSettings.size());
            for (PlasmaDataObject oldSettingObject : oldSettings) {
                if (!oldSettingObject.getDataGraph().getChangeSummary().isCreated(oldSettingObject))
                    oldValues.add(oldSettingObject);
            }//from  w w  w.j a  v a2 s . co  m

            EdgeWriter edgeWriter = rowWriter.getEdgeWriter(dataObject, property, sequence);
            if (!property.isMany()) {
                this.collectSingular(edgeWriter, dataObject, oldValues, property, dataValue);
            } else {
                this.collectMulti(edgeWriter, dataObject, oldValues, property, dataValue);
            }
            edgeWriter.write();
        } else {
            Increment increment = property.getIncrement();
            if (dataValue != null) {
                if (increment == null) {
                    byte[] valueBytes = HBaseDataConverter.INSTANCE.toBytes(property, dataValue);
                    rowWriter.writeRowData(dataObject, sequence, property, valueBytes);
                } else { // increment
                    if (type.isConcurrent())
                        throw new GraphServiceException(
                                "increment property, " + property + ", found on concurrent type, " + type
                                        + " - increment properties cannot coexist within a concurrent type");
                    DataType dataType = DataType.valueOf(property.getType().getName());
                    if (increment != null) { // user can increment/decrement by whatever
                                             // value
                        if (dataType.ordinal() != DataType.Long.ordinal())
                            throw new GraphServiceException("property, " + property + ", must be datatype "
                                    + DataType.Long + " to support increment operations");
                        long longDataValue = DataConverter.INSTANCE.toLong(property.getType(), dataValue);
                        rowWriter.incrementRowData(dataObject, sequence, property, longDataValue);
                    }
                }

            } else {
                rowWriter.deleteRowData(dataObject, sequence, property);
            }
        }
    }
}

From source file:org.metaservice.core.AbstractDispatcher.java

public static List<Statement> getGeneratedStatements(RepositoryConnection resultConnection,
        Set<Statement> loadedStatements) throws RepositoryException {
    RepositoryResult<Statement> all = resultConnection.getStatements(null, null, null, true);
    ArrayList<Statement> allList = new ArrayList<>();
    HashSet<Resource> undefined = new HashSet<>();
    while (all.hasNext()) {
        Statement s = all.next();
        if (!loadedStatements.contains(s)) {
            if (s.getPredicate().equals(RDFS.SUBPROPERTYOF) || s.getPredicate().equals(RDFS.SUBCLASSOF)
                    || s.getPredicate().equals(RDF.TYPE) && s.getObject().equals(RDFS.RESOURCE)
                    || s.getPredicate().equals(RDF.TYPE) && s.getObject().equals(OWL.THING)
                    || s.getPredicate().equals(RDF.TYPE) && s.getObject().equals(RDF.PROPERTY)) {
                if (!s.getSubject().stringValue().startsWith("http://metaservice.org/d/")) {
                    LOGGER.debug("UNDEFINED {} {} {}", s.getSubject(), s.getPredicate(), s.getObject());
                    undefined.add(s.getSubject());
                }// ww w  . jav a  2 s. c o  m
            } else {
                if (s.getSubject() instanceof BNode || s.getObject() instanceof BNode) {
                    LOGGER.error("ATTENTION - BNodes are not supported by Metaservice, skipping statement");
                    continue;
                }
                allList.add(s);
            }
        }
    }
    if (undefined.size() != 0) {
        //grep for logfiles:
        //grep "not defi"  *| sed -e 's/^.*WARN.*define://' | uniq | sort | uniq | sed -e 's/,/\n/g' | tr -d ' ' | sort | uniq
        LOGGER.warn("Did not define: {}", StringUtils.join(undefined, ", "));
    }
    return allList;
}

From source file:org.apache.sysml.runtime.matrix.CMCOVMR.java

public static JobReturn runJob(MRJobInstruction inst, String[] inputs, InputInfo[] inputInfos, long[] rlens,
        long[] clens, int[] brlens, int[] bclens, String instructionsInMapper, String cmNcomInstructions,
        int numReducers, int replication, byte[] resultIndexes, String[] outputs, OutputInfo[] outputInfos)
        throws Exception {
    JobConf job = new JobConf(CMCOVMR.class);
    job.setJobName("CM-COV-MR");

    //whether use block representation or cell representation
    MRJobConfiguration.setMatrixValueClassForCM_N_COM(job, true);

    //added for handling recordreader instruction
    String[] realinputs = inputs;
    InputInfo[] realinputInfos = inputInfos;
    long[] realrlens = rlens;
    long[] realclens = clens;
    int[] realbrlens = brlens;
    int[] realbclens = bclens;
    byte[] realIndexes = new byte[inputs.length];
    for (byte b = 0; b < realIndexes.length; b++)
        realIndexes[b] = b;/*from   ww w  .  j a v  a2  s. c  o  m*/

    //set up the input files and their format information
    MRJobConfiguration.setUpMultipleInputs(job, realIndexes, realinputs, realinputInfos, realbrlens, realbclens,
            true, ConvertTarget.WEIGHTEDCELL);

    //set up the dimensions of input matrices
    MRJobConfiguration.setMatricesDimensions(job, realIndexes, realrlens, realclens);

    //set up the block size
    MRJobConfiguration.setBlocksSizes(job, realIndexes, realbrlens, realbclens);

    //set up unary instructions that will perform in the mapper
    MRJobConfiguration.setInstructionsInMapper(job, instructionsInMapper);

    //set up the aggregate instructions that will happen in the combiner and reducer
    MRJobConfiguration.setCM_N_COMInstructions(job, cmNcomInstructions);

    //set up the replication factor for the results
    job.setInt(MRConfigurationNames.DFS_REPLICATION, replication);

    //set up custom map/reduce configurations 
    DMLConfig config = ConfigurationManager.getDMLConfig();
    MRJobConfiguration.setupCustomMRConfigurations(job, config);

    //set up what matrices are needed to pass from the mapper to reducer
    HashSet<Byte> mapoutputIndexes = MRJobConfiguration.setUpOutputIndexesForMapper(job, realIndexes,
            instructionsInMapper, null, cmNcomInstructions, resultIndexes);

    //set up the multiple output files, and their format information
    MRJobConfiguration.setUpMultipleOutputs(job, resultIndexes, new byte[resultIndexes.length], outputs,
            outputInfos, false);

    // configure mapper and the mapper output key value pairs
    job.setMapperClass(CMCOVMRMapper.class);

    job.setMapOutputKeyClass(TaggedFirstSecondIndexes.class);
    job.setMapOutputValueClass(CM_N_COVCell.class);
    job.setOutputKeyComparatorClass(TaggedFirstSecondIndexes.Comparator.class);
    job.setPartitionerClass(TaggedFirstSecondIndexes.TagPartitioner.class);

    //configure reducer
    job.setReducerClass(CMCOVMRReducer.class);
    //job.setReducerClass(PassThroughReducer.class);

    MatrixCharacteristics[] stats = MRJobConfiguration.computeMatrixCharacteristics(job, realIndexes,
            instructionsInMapper, null, null, cmNcomInstructions, resultIndexes, mapoutputIndexes, false).stats;

    //set up the number of reducers
    MRJobConfiguration.setNumReducers(job, mapoutputIndexes.size(), numReducers);//each output tag is a group

    // Print the complete instruction
    if (LOG.isTraceEnabled())
        inst.printCompleteMRJobInstruction(stats);

    // By default, the job executes in "cluster" mode.
    // Determine if we can optimize and run it in "local" mode.
    MatrixCharacteristics[] inputStats = new MatrixCharacteristics[inputs.length];
    for (int i = 0; i < inputs.length; i++) {
        inputStats[i] = new MatrixCharacteristics(rlens[i], clens[i], brlens[i], bclens[i]);
    }

    //set unique working dir
    MRJobConfiguration.setUniqueWorkingDir(job);

    RunningJob runjob = JobClient.runJob(job);

    return new JobReturn(stats, outputInfos, runjob.isSuccessful());
}

From source file:com.cloudera.recordservice.tests.MiniClusterController.java

/**
 * This method checks the current state of the MiniClusterController object
 * against the actual state of the system. Returns false if some running
 * cluster nodes are not tracked by this MiniClusterController, or if some
 * nodes tracked by this MiniClusterController are not running. Returns true
 * otherwise.//from w w  w. j av a 2s.  c  om
 */
public boolean isClusterStateCorrect() {
    HashSet<Integer> pidSet = getRunningMiniNodePids();
    // Check the cluster list
    if (pidSet.size() > 0 && (clusterList_ == null || clusterList_.size() <= 0)) {
        printPids(pidSet, "were found but are not being tracked by the MiniClusterController");
        return false;
    } else {
        for (MiniClusterNode node : clusterList_) {
            if (!pidSet.contains(node.pid_)) {
                System.err.println("Node with pid = " + node.pid_ + " was expected but not found");
                return false;
            }
            // Two nodes cannot share the same process ID
            pidSet.remove(node.pid_);
        }
        if (pidSet.size() > 0) {
            printPids(pidSet, "were found but are not being tracked by the MiniClusterController");
            return false;
        }
    }
    return true;
}

From source file:org.apache.fluo.recipes.core.export.it.ExportTestBase.java

protected void diff(Map<String, Set<String>> fr, Map<String, Set<String>> er) {
    HashSet<String> allKeys = new HashSet<>(fr.keySet());
    allKeys.addAll(er.keySet());//from  w  w  w  . j a v  a2s .c  om

    for (String k : allKeys) {
        Set<String> s1 = fr.getOrDefault(k, Collections.emptySet());
        Set<String> s2 = er.getOrDefault(k, Collections.emptySet());

        HashSet<String> sub1 = new HashSet<>(s1);
        sub1.removeAll(s2);

        HashSet<String> sub2 = new HashSet<>(s2);
        sub2.removeAll(s1);

        if (sub1.size() > 0 || sub2.size() > 0) {
            System.out.println(k + " " + sub1 + " " + sub2);
        }

    }
}

From source file:br.fapesp.myutils.MyUtils.java

public static int[] createArrayFromHashSet(HashSet<Integer> hash) {
    int[] ar = new int[hash.size()];
    int i = 0;/*from www .j  a  v a 2 s .c  o  m*/
    for (Integer val : hash) {
        ar[i++] = val;
    }
    return ar;
}