List of usage examples for java.util TreeMap keySet
public Set<K> keySet()
From source file:net.spfbl.core.Analise.java
protected static void dumpClusterCIDR(StringBuilder builder) { TreeMap<String, Short[]> map = getClusterMap(); for (String token : map.keySet()) { Short[] dist = map.get(token); int spam = dist[1]; if (spam > 512) { int ham = dist[0]; float total = ham + spam; float reputation = spam / total; if (reputation > CLUSTER_RED) { if (Subnet.isValidCIDR(token)) { if (!Block.contains(token)) { builder.append(token); builder.append(' '); builder.append(ham); builder.append(' '); builder.append(spam); builder.append('\n'); }// w ww . jav a2s . co m } } } } }
From source file:net.spfbl.core.Analise.java
protected static void dumpClusterMask(StringBuilder builder) { TreeMap<String, Short[]> map = getClusterMap(); for (String token : map.keySet()) { if (token.contains("#") || token.contains(".H.")) { Short[] dist = map.get(token); int spam = dist[1]; if (spam > 512) { int ham = dist[0]; float total = ham + spam; float reputation = spam / total; if (reputation > CLUSTER_RED) { if (!Generic.containsGenericExact(token)) { String hostname = token.replace("#", "0"); hostname = hostname.replace(".H.", ".0a."); if (!Block.contains(hostname)) { builder.append(token); builder.append(' '); builder.append(ham); builder.append(' '); builder.append(spam); builder.append('\n'); }//from ww w.j a v a 2s . c om } } } } } }
From source file:edu.umm.radonc.ca_dash.controllers.PieChartController.java
public void updateChart(String dataSet) { TreeMap<String, Long> mtxcounts; TreeMap<String, Long> dptcounts; TreeMap<String, SynchronizedDescriptiveStatistics> mptstats; TreeMap<String, SynchronizedDescriptiveStatistics> ptstats; pieChart.clear();//from w ww .j ava 2 s . c o m dstats.clear(); dstatsPerDoc.clear(); dstatsPerRTM.clear(); JSONArray labels = new JSONArray(); if (dataSet.equals("DR")) { dptcounts = getFacade().doctorPtCounts(startDate, endDate, selectedFacility, selectedFilters); ptstats = getFacade().doctorStats(startDate, endDate, selectedFacility, selectedFilters); for (String doctor : dptcounts.keySet()) { Long count = dptcounts.get(doctor); DoctorStats newItem = new DoctorStats(); newItem.setTotalPatients(count); newItem.setAverageDailyPatients(ptstats.get(doctor)); dstatsPerDoc.put(doctor, newItem); pieChart.set(doctor, newItem.getAverageDailyPatients().getMean()); dstats.addValue(count); try { String item = doctor + "<br/>( mean: " + Math.round(newItem.getAverageDailyPatients().getMean()) + ", σ: " + decf.format(newItem.getAverageDailyPatients().getStandardDeviation()) + " )"; labels.put(item); } catch (Exception e) { //FIXME } } pieChart.setTitle("Physician Workload: " + df.format(startDate) + " - " + df.format(endDate)); } else { mtxcounts = getFacade().machineTxCounts(startDate, endDate, selectedFacility, selectedFilters); mptstats = getFacade().machineStats(startDate, endDate, selectedFacility, selectedFilters); pieChart.setTitle("Tx per Machine: " + df.format(startDate) + " - " + df.format(endDate)); for (String machine : mtxcounts.keySet()) { Long count = mtxcounts.get(machine); DoctorStats newItem = new DoctorStats(); newItem.setTotalPatients(count); newItem.setAverageDailyPatients(mptstats.get(machine)); dstatsPerRTM.put(machine, newItem); pieChart.set(machine, newItem.getAverageDailyPatients().getMean()); dstats.addValue(count); try { String item = machine + "<br/>( mean: " + Math.round(newItem.getAverageDailyPatients().getMean()) + ", σ: " + decf.format(newItem.getAverageDailyPatients().getStandardDeviation()) + " )"; labels.put(item); } catch (Exception e) { //FIXME } } } //pieChart.setLegendPosition("ne"); pieChart.setShowDataLabels(true); pieChart.setShadow(false); //pieChart.setDataFormat("value"); pieChart.setSeriesColors("8C3130, E0AB5D, 4984D0, 2C2A29, A2B85C, BBBEC3, D8C9B6, BD8A79, 3C857A, CD3935"); pieChart.setExtender("function(){ this.cfg.seriesDefaults.rendererOptions.dataLabels = " + labels.toString() + "; " + "this.cfg.seriesDefaults.rendererOptions.dataLabelPositionFactor = 1.21; " + "this.cfg.seriesDefaults.rendererOptions.diameter = 600; " + "this.cfg.seriesDefaults.rendererOptions.dataLabelThreshold = 0.5;" + "this.cfg.sliceMargin = 3; " + "this.legend = {show:false} }"); }
From source file:com.sfs.whichdoctor.webservice.RotationXmlOutputImpl.java
/** * Gets the tool count xml./*from w w w . ja va2 s.c o m*/ * * @param type the type * @param toolCounts the tool counts * @return the tool count xml */ private Element getToolCountXml(final String type, final TreeMap<String, ToolCount> toolCounts) { Element tctXml = new Element("ToolCountType"); tctXml.setAttribute("name", type); for (String id : toolCounts.keySet()) { ToolCount tc = toolCounts.get(id); Element tcXml = new Element("ToolCount"); tcXml.setAttribute("name", tc.getName()); tcXml.setAttribute("subName", tc.getSubName()); tcXml.setAttribute("STP", tc.getTrainingProgramShortName()); tcXml.addContent(String.valueOf(tc.getCount())); tctXml.addContent(tcXml); } return tctXml; }
From source file:org.intermine.bio.web.displayer.MouseAllelesDisplayer.java
@SuppressWarnings({ "unchecked", "unused" })
@Override// ww w. j a v a 2s. c om
public void display(HttpServletRequest request, ReportObject reportObject) {
HttpSession session = request.getSession();
im = SessionMethods.getInterMineAPI(session);
Model model = im.getModel();
PathQueryExecutor executor = im.getPathQueryExecutor(SessionMethods.getProfile(session));
// Counts of HLPT Names
PathQuery q = new PathQuery(model);
Integer alleleCount = 0;
Boolean mouser = false;
if (!MouseAllelesDisplayer.isThisAMouser(reportObject)) {
// to give us some homologue identifier and the actual terms to tag-cloudize
q.addViews("Gene.symbol", "Gene.primaryIdentifier", "Gene.id",
"Gene.homologues.homologue.alleles.genotypes.phenotypeTerms.name");
// add this rubbish so we do not filter out the same terms
q.addViews("Gene.homologues.homologue.id", "Gene.homologues.homologue.alleles.id",
"Gene.homologues.homologue.alleles.genotypes.id");
// mouse homologues only
q.addConstraint(Constraints.eq("Gene.homologues.homologue.organism.shortName", "M. musculus"), "A");
// for our gene object
q.addConstraint(Constraints.eq("Gene.id", reportObject.getObject().getId().toString()), "B");
// we want only those homologues that have a non-empty alleles collection
q.addConstraint(Constraints.isNotNull("Gene.homologues.homologue.alleles.id"));
q.setConstraintLogic("A and B");
// order by the homologue db id, just to keep the alleles in a reasonable order
q.addOrderBy("Gene.homologues.homologue.id", OrderDirection.ASC);
// allele count
PathQuery cq = new PathQuery(im.getModel());
cq.addViews("Gene.homologues.homologue.alleles.primaryIdentifier");
cq.addConstraint(Constraints.eq("Gene.homologues.homologue.organism.shortName", "M. musculus"), "A");
cq.addConstraint(Constraints.eq("Gene.id", reportObject.getObject().getId().toString()), "B");
cq.setConstraintLogic("A and B");
try {
alleleCount = executor.count(cq);
} catch (ObjectStoreException e) {
// couldn't get count
}
} else {
mouser = true;
// to give us some homologue identifier and the actual terms to tag-cloudize
q.addViews("Gene.symbol", "Gene.primaryIdentifier", "Gene.id",
"Gene.alleles.genotypes.phenotypeTerms.name");
// add this rubbish so we do not filter out the same terms
q.addViews("Gene.alleles.id", "Gene.alleles.genotypes.id");
// for our gene object
q.addConstraint(Constraints.eq("Gene.id", reportObject.getObject().getId().toString()), "A");
// we want only those homologues that have a non-empty alleles collection
q.addConstraint(Constraints.isNotNull("Gene.alleles.id"));
// mouser has a collection table of alleles as well
for (FieldDescriptor fd : reportObject.getClassDescriptor().getAllFieldDescriptors()) {
if ("alleles".equals(fd.getName()) && fd.isCollection()) {
// fetch the collection
Collection<?> collection = null;
try {
collection = (Collection<?>) reportObject.getObject().getFieldValue("alleles");
} catch (IllegalAccessException e) {
e.printStackTrace();
}
List<Class<?>> lc = PathQueryResultHelper.queryForTypesInCollection(reportObject.getObject(),
"alleles", im.getObjectStore());
if (collection == null) {
return;
}
// create an InlineResultsTable
InlineResultsTable t = new InlineResultsTable(collection, fd.getClassDescriptor().getModel(),
SessionMethods.getWebConfig(request), im.getClassKeys(), collection.size(), false, lc);
request.setAttribute("collection", t);
// Get the number of alleles.
alleleCount = collection.size();
break;
}
}
}
ExportResultsIterator qResults;
try {
qResults = executor.execute(q);
} catch (ObjectStoreException e) {
throw new RuntimeException(e);
}
// traverse so we get a nice map from homologue symbol to a map of allele term names (and
// some extras)
HashMap<String, HashMap<String, Object>> counts = new HashMap<String, HashMap<String, Object>>();
while (qResults.hasNext()) {
List<ResultElement> row = qResults.next();
String sourceGeneSymbol = getIdentifier(row);
// a per source gene map
HashMap<String, Integer> terms;
if (!counts.containsKey(sourceGeneSymbol)) {
HashMap<String, Object> wrapper = new HashMap<String, Object>();
terms = new LinkedHashMap<String, Integer>();
wrapper.put("terms", terms);
wrapper.put("homologueId",
(mouser) ? row.get(2).getField().toString() : row.get(4).getField().toString());
wrapper.put("isMouser", mouser);
counts.put(sourceGeneSymbol, wrapper);
} else {
terms = (HashMap<String, Integer>) counts.get(sourceGeneSymbol).get("terms");
}
// populate the allele term with count
String alleleTerm = row.get(3).getField().toString();
if (!alleleTerm.isEmpty()) {
if (!terms.containsKey(alleleTerm)) {
terms.put(alleleTerm, 1);
} else {
terms.put(alleleTerm, terms.get(alleleTerm) + 1);
}
}
}
// Now give us a map of top 20 per homologue
HashMap<String, HashMap<String, Object>> top = new HashMap<String, HashMap<String, Object>>();
for (String symbol : counts.keySet()) {
HashMap<String, Object> gene = counts.get(symbol);
LinkedHashMap<String, Integer> terms = (LinkedHashMap<String, Integer>) gene.get("terms");
if (terms != null) {
// sorted by value
TreeMap<String, Integer> sorted = new TreeMap<String, Integer>(new IntegerValueComparator(terms));
// deep copy
for (String term : terms.keySet()) {
sorted.put(term, terms.get(term));
}
// "mark" top 20 and order by natural order - the keys
TreeMap<String, Map<String, Object>> marked = new TreeMap<String, Map<String, Object>>();
Integer i = 0;
for (String term : sorted.keySet()) {
// wrapper map
HashMap<String, Object> m = new HashMap<String, Object>();
// am I top dog?
Boolean topTerm = false;
if (i < 20) {
topTerm = true;
}
m.put("top", topTerm);
m.put("count", sorted.get(term));
m.put("url", getUrl((String) gene.get("homologueId"), term));
// save it
marked.put(term, m);
i++;
}
HashMap<String, Object> wrapper = new HashMap<String, Object>();
wrapper.put("terms", marked);
wrapper.put("homologueId", gene.get("homologueId"));
wrapper.put("isMouser", gene.get("isMouser"));
top.put(symbol, wrapper);
}
}
request.setAttribute("thisIsAMouser", mouser);
request.setAttribute("counts", top);
request.setAttribute("alleleCount", alleleCount);
}
From source file:se.sics.gvod.common.GraphUtil.java
public GraphUtil(TreeMap<VodAddress, VodNeighbors> alivePeers) { super();//from ww w . j av a2 s . c om n = alivePeers.size(); m = new byte[n][n]; dist = new int[n][n]; inDegree = new double[n]; outDegree = new int[n]; clustering = new double[n]; a = new VodAddress[n]; map = new HashMap<VodAddress, Integer>(); neighbors = new int[n][]; inStats = new SummaryStatistics(); outStats = new SummaryStatistics(); // map all alive nodes to a contiguous sequence of integers { int p = 0; for (VodAddress address : alivePeers.keySet()) { VodAddress src = (VodAddress) address; utilitySetNbChange += (alivePeers.get(src).getUtilitySetNbChange() / alivePeers.get(src).getNbCycles()); upperSetNbChange += (alivePeers.get(src).getUpperSetNbChange() / alivePeers.get(src).getNbCycles()); nbCycles += alivePeers.get(src).getNbCycles(); a[p] = src; map.put(src, p); p++; } } // build adjacency matrix int d = -1; { try { for (int s = 0; s < a.length; s++) { VodAddress src = a[s]; VodNeighbors neigh = alivePeers.get(src); int nn = 0; for (VodDescriptor desc : neigh.getRandomSetDescriptors()) { VodAddress dst = desc.getVodAddress(); if (!map.containsKey(dst)) { continue; } d = map.get(dst); m[s][d] = 1; inDegree[d]++; outDegree[s]++; nn++; } neighbors[s] = new int[nn]; nn = 0; for (VodDescriptor desc : neigh.getRandomSetDescriptors()) { VodAddress dst = desc.getVodAddress(); if (map.containsKey(dst)) { neighbors[s][nn++] = map.get(dst); } } } } catch (Exception e) { e.printStackTrace(); System.exit(1); } } // build distance matrix, clustering coefficient, average path length // diameter and average degrees { for (int i = 0; i < n; i++) { bfs(i, dist[i]); // we compute the clustering coefficient here int neigh[] = neighbors[i]; if (neigh.length <= 1) { clustering[i] = 1.0; continue; } int edges = 0; for (int j = 0; j < neigh.length; j++) { for (int k = j + 1; k < neigh.length; k++) { if (m[neigh[j]][neigh[k]] > 0 || m[neigh[k]][neigh[j]] > 0) { ++edges; } } } clustering[i] = ((edges * 2.0) / neigh.length) / (neigh.length - 1); } int k = 0; for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { if (i == j) continue; if (dist[i][j] == n) { infinitePathCount++; continue; } if (dist[i][j] > diameter) { diameter = dist[i][j]; } avgPathLength = (avgPathLength * k + dist[i][j]) / (k + 1); k++; } inStats.addValue(inDegree[i]); outStats.addValue(outDegree[i]); // avgIn = (avgIn * i + inDegree[i]) / (i + 1); // minIn = minIn > inDegree[i] ? inDegree[i] : minIn; // maxIn = maxIn < inDegree[i] ? inDegree[i] : maxIn; // avgOut = (avgOut * i + outDegree[i]) / (i + 1); avgClustering = (avgClustering * i + clustering[i]) / (i + 1); } } }
From source file:se.sics.kompics.p2p.overlay.cyclon.GraphUtil.java
public GraphUtil(TreeMap<OverlayAddress, CyclonNeighbors> alivePeers) { super();/*from w w w .j a v a 2s . co m*/ n = alivePeers.size(); m = new byte[n][n]; dist = new int[n][n]; inDegree = new double[n]; outDegree = new int[n]; clustering = new double[n]; a = new CyclonAddress[n]; map = new HashMap<CyclonAddress, Integer>(); neighbors = new int[n][]; inStats = new SummaryStatistics(); outStats = new SummaryStatistics(); // map all alive nodes to a contiguous sequence of integers { int p = 0; for (OverlayAddress address : alivePeers.keySet()) { CyclonAddress src = (CyclonAddress) address; a[p] = src; map.put(src, p); p++; } } // build adjacency matrix int d = -1; { try { for (int s = 0; s < a.length; s++) { CyclonAddress src = a[s]; CyclonNeighbors neigh = alivePeers.get(src); int nn = 0; for (CyclonNodeDescriptor desc : neigh.getDescriptors()) { CyclonAddress dst = desc.getCyclonAddress(); if (!map.containsKey(dst)) { continue; } d = map.get(dst); m[s][d] = 1; inDegree[d]++; outDegree[s]++; nn++; } neighbors[s] = new int[nn]; nn = 0; for (CyclonNodeDescriptor desc : neigh.getDescriptors()) { CyclonAddress dst = desc.getCyclonAddress(); if (map.containsKey(dst)) { neighbors[s][nn++] = map.get(dst); } } } } catch (Exception e) { e.printStackTrace(); System.exit(1); } } // build distance matrix, clustering coefficient, average path length // diameter and average degrees { for (int i = 0; i < n; i++) { bfs(i, dist[i]); // we compute the clustering coefficient here int neigh[] = neighbors[i]; if (neigh.length <= 1) { clustering[i] = 1.0; continue; } int edges = 0; for (int j = 0; j < neigh.length; j++) { for (int k = j + 1; k < neigh.length; k++) { if (m[neigh[j]][neigh[k]] > 0 || m[neigh[k]][neigh[j]] > 0) { ++edges; } } } clustering[i] = ((edges * 2.0) / neigh.length) / (neigh.length - 1); } int k = 0; for (int i = 0; i < n; i++) { for (int j = 0; j < n; j++) { if (i == j) continue; if (dist[i][j] == n) { infinitePathCount++; continue; } if (dist[i][j] > diameter) { diameter = dist[i][j]; } avgPathLength = (avgPathLength * k + dist[i][j]) / (k + 1); k++; } inStats.addValue(inDegree[i]); outStats.addValue(outDegree[i]); // avgIn = (avgIn * i + inDegree[i]) / (i + 1); // minIn = minIn > inDegree[i] ? inDegree[i] : minIn; // maxIn = maxIn < inDegree[i] ? inDegree[i] : maxIn; // avgOut = (avgOut * i + outDegree[i]) / (i + 1); avgClustering = (avgClustering * i + clustering[i]) / (i + 1); } } }
From source file:org.egov.ptis.web.controller.rest.AssessmentServiceController.java
/** * This method is used to get all list of floor numbers. * @return responseJson - server response in JSON format * @throws IOException/*from w w w .jav a 2 s. c o m*/ */ @RequestMapping(value = "/property/floors", produces = APPLICATION_JSON_VALUE) public String getFloors() throws IOException { List<MasterCodeNamePairDetails> mstrCodeNamePairDetailsList = new ArrayList<>(); ErrorDetails errorDetails = null; String responseJson = null; //Boolean isAuthenticatedUser = propertyExternalService.authenticateUser(username, password); Boolean isAuthenticatedUser = true; if (isAuthenticatedUser) { TreeMap<Integer, String> floorMap = PropertyTaxConstants.FLOOR_MAP; Set<Integer> keys = floorMap.keySet(); for (Integer key : keys) { MasterCodeNamePairDetails mstrCodeNamePairDetails = new MasterCodeNamePairDetails(); mstrCodeNamePairDetails.setCode(key.toString()); mstrCodeNamePairDetails.setName(floorMap.get(key)); mstrCodeNamePairDetailsList.add(mstrCodeNamePairDetails); } responseJson = getJSONResponse(mstrCodeNamePairDetailsList); } else { errorDetails = getInvalidCredentialsErrorDetails(); responseJson = getJSONResponse(errorDetails); } return responseJson; }
From source file:eu.edisonproject.training.wsd.DisambiguatorImpl.java
private Term mapreduceDisambiguate(String term, Set<Term> possibleTerms, Set<String> ngarms, double minimumSimilarity) throws IOException { String filePath = ".." + File.separator + "etc" + File.separator + "Avro Document" + File.separator + term + File.separator + term + ".avro"; TermAvroSerializer ts = new TermAvroSerializer(filePath, Term.getClassSchema()); List<CharSequence> empty = new ArrayList<>(); empty.add(""); for (Term t : possibleTerms) { List<CharSequence> nuid = t.getNuids(); if (nuid == null || nuid.isEmpty() || nuid.contains(null)) { t.setNuids(empty);/*w w w . j a va 2 s . c o m*/ } List<CharSequence> buids = t.getBuids(); if (buids == null || buids.isEmpty() || buids.contains(null)) { t.setBuids(empty); } List<CharSequence> alt = t.getAltLables(); if (alt == null || alt.isEmpty() || alt.contains(null)) { t.setAltLables(empty); } List<CharSequence> gl = t.getGlosses(); if (gl == null || gl.isEmpty() || gl.contains(null)) { t.setGlosses(empty); } else { StringBuilder glosses = new StringBuilder(); for (CharSequence n : gl) { glosses.append(n).append(" "); } gl = new ArrayList<>(); stemer.setDescription(glosses.toString()); gl.add(stemer.execute()); t.setGlosses(gl); } List<CharSequence> cat = t.getCategories(); if (cat == null || cat.contains(null)) { t.setCategories(empty); } ts.serialize(t); } Term context = new Term(); context.setUid("context"); StringBuilder glosses = new StringBuilder(); context.setLemma(term); context.setOriginalTerm(term); context.setUrl("empty"); for (String n : ngarms) { glosses.append(n).append(" "); } List<CharSequence> contextGlosses = new ArrayList<>(); stemer.setDescription(glosses.toString()); contextGlosses.add(stemer.execute()); context.setGlosses(contextGlosses); List<CharSequence> nuid = context.getNuids(); if (nuid == null || nuid.isEmpty() || nuid.contains(null)) { context.setNuids(empty); } List<CharSequence> buids = context.getBuids(); if (buids == null || buids.isEmpty() || buids.contains(null)) { context.setBuids(empty); } List<CharSequence> alt = context.getAltLables(); if (alt == null || alt.isEmpty() || alt.contains(null)) { context.setAltLables(empty); } List<CharSequence> gl = context.getGlosses(); if (gl == null || gl.isEmpty() || gl.contains(null)) { context.setGlosses(empty); } List<CharSequence> cat = context.getCategories(); if (cat == null || cat.contains(null)) { context.setCategories(empty); } ts.serialize(context); ts.close(); ITFIDFDriver tfidfDriver = new TFIDFDriverImpl(term); tfidfDriver.executeTFIDF(new File(filePath).getParent()); Map<CharSequence, Map<String, Double>> featureVectors = CSVFileReader .tfidfResult2Map(TFIDFDriverImpl.OUTPUT_PATH4 + File.separator + "part-r-00000"); Map<String, Double> contextVector = featureVectors.remove("context"); Map<CharSequence, Double> scoreMap = new HashMap<>(); for (CharSequence key : featureVectors.keySet()) { Double similarity = cosineSimilarity(contextVector, featureVectors.get(key)); scoreMap.put(key, similarity); } if (scoreMap.isEmpty()) { return null; } ValueComparator bvc = new ValueComparator(scoreMap); TreeMap<CharSequence, Double> sorted_map = new TreeMap(bvc); sorted_map.putAll(scoreMap); Iterator<CharSequence> it = sorted_map.keySet().iterator(); CharSequence winner = it.next(); Double s1 = scoreMap.get(winner); if (s1 < getMinimumSimilarity()) { return null; } return getTermFromDB(winner); }
From source file:com.eucalyptus.tests.awssdk.S3ListMpuTests.java
@Test public void maxKeys() throws Exception { testInfo(this.getClass().getSimpleName() + " - maxKeys"); try {/*from w ww . j av a 2s .c om*/ int numKeys = 3 + random.nextInt(3); // 3-5 keys int numUploads = 3 + random.nextInt(3); // 3-5 uploads int maxUploads = numUploads - 1; int totalUploads = numKeys * numUploads; int counter = (totalUploads % maxUploads == 0) ? (totalUploads / maxUploads) : ((totalUploads / maxUploads) + 1); print("Number of keys: " + numKeys); print("Number of uploads per key: " + numUploads); print("Number of mpus per listing: " + maxUploads); // Generate some mpus TreeMap<String, List<String>> keyUploadIdMap = initiateMpusForMultipleKeys(s3ClientA, accountA, numKeys, numUploads, new String()); Iterator<String> keyIterator = keyUploadIdMap.keySet().iterator(); String key = keyIterator.next(); Iterator<String> uploadIdIterator = keyUploadIdMap.get(key).iterator(); String uploadId = null; String nextKeyMarker = null; String nextUploadIdMarker = null; MultipartUploadListing listing = null; for (int i = 1; i <= counter; i++) { if (i != counter) { listing = listMpu(s3ClientA, accountA, bucketName, nextKeyMarker, nextUploadIdMarker, null, null, maxUploads, true); assertTrue( "Expected " + maxUploads + " mpu listings, but got " + listing.getMultipartUploads().size(), maxUploads == listing.getMultipartUploads().size()); } else { listing = listMpu(s3ClientA, accountA, bucketName, nextKeyMarker, nextUploadIdMarker, null, null, maxUploads, false); assertTrue( "Expected " + totalUploads + " mpu listings, but got " + listing.getMultipartUploads().size(), totalUploads == listing.getMultipartUploads().size()); } for (MultipartUpload mpu : listing.getMultipartUploads()) { if (!uploadIdIterator.hasNext()) { key = keyIterator.next(); uploadIdIterator = keyUploadIdMap.get(key).iterator(); } uploadId = uploadIdIterator.next(); assertTrue("Expected key to be " + key + ", but got " + mpu.getKey(), mpu.getKey().equals(key)); assertTrue("Expected upload ID to be " + uploadId + ", but got " + mpu.getUploadId(), mpu.getUploadId().equals(uploadId)); verifyCommonElements(mpu); totalUploads--; } nextKeyMarker = key; nextUploadIdMarker = uploadId; } } catch (AmazonServiceException ase) { printException(ase); assertThat(false, "Failed to run maxKeys"); } }