List of usage examples for org.jfree.util Log error
public static void error(final Object message, final Exception e)
From source file:de.csw.ontology.XWikiTextEnhancer.java
/** * The enhanced text contains links to the Lucene search page of the xWiki * system. The search terms are related to the annotated phrase. *///w ww .j a v a2s .com public String enhance(String text) { CSWGermanAnalyzer ga = new CSWGermanAnalyzer(); TokenStream ts = null; StringBuilder result = new StringBuilder(); initializeLinkIndex(text); try { Reader r = new BufferedReader(new StringReader(text)); ts = ga.tokenStream("", r); CharTermAttribute charTermAttribute = ts.addAttribute(CharTermAttribute.class); OffsetAttribute offsetAttribute = ts.addAttribute(OffsetAttribute.class); TypeAttribute typeAttribute = ts.addAttribute(TypeAttribute.class); String term; int lastEndIndex = 0; while (ts.incrementToken()) { result.append(text.substring(lastEndIndex, offsetAttribute.startOffset())); term = String.copyValueOf(charTermAttribute.buffer(), 0, charTermAttribute.length()); if (typeAttribute.type().equals(ConceptFilter.CONCEPT_TYPE) && isAnnotatable(offsetAttribute)) { log.debug("Annotating concept: " + term); annotateWithSearch(result, text.substring(offsetAttribute.startOffset(), offsetAttribute.endOffset()), term); } else { result.append(text.substring(offsetAttribute.startOffset(), offsetAttribute.endOffset())); } lastEndIndex = offsetAttribute.endOffset(); } result.append(text.subSequence(lastEndIndex, text.length())); } catch (IOException e) { Log.error("Error while processing the page content", e); } ga.close(); return result.toString(); }
From source file:com.ah.bo.hiveap.HiveApImageInfo.java
@Transient public void setReleaseData(String releaseData) { this.releaseData = releaseData; try {/*from w w w. j a v a2 s.c om*/ Date date = rlDataFormat.parse(releaseData); this.releaseTime = date.getTime(); } catch (Exception e) { Log.error("HOS Image release data\" + releaseData + \" parse error", e); } }
From source file:com.pedra.core.setup.CoreSystemSetup.java
private File getProjectdataUpdateDirectory(String relativeUpdateDirectory) { if (relativeUpdateDirectory == null) { relativeUpdateDirectory = ""; }/*www.j a v a 2 s .co m*/ String projectdataUpdateFolderProperty = Config.getString("projectdata.update.folder", "/pedracore/import/versions"); projectdataUpdateFolderProperty = projectdataUpdateFolderProperty + relativeUpdateDirectory; File projectdataUpdateFolder = null; try { projectdataUpdateFolder = new File(getClass().getResource(projectdataUpdateFolderProperty).toURI()); } catch (final URISyntaxException e) { Log.error("error finding project data update directory[" + projectdataUpdateFolderProperty + "]", e); return null; } if (!projectdataUpdateFolder.exists()) { Log.warn("project data update directory [" + projectdataUpdateFolderProperty + "] does not exist"); return null; } else if (ArrayUtils.isEmpty(projectdataUpdateFolder.listFiles())) { Log.info("Project datad update directory[" + projectdataUpdateFolderProperty + "] is empty"); } return projectdataUpdateFolder; }
From source file:com.redoute.datamap.dao.impl.PictureDAO.java
private void updateFilePicture(String id, String value) { Picture pic = findPictureByKey(id);/*from w w w . j a v a 2s .c om*/ pic.setBase64(value); try { if (DAOUtil.isEmpty(pic.getLocalPath())) { pic.setLocalPath(pictureFileHelper.createLocalPath(pic)); updatePicture(id, "localpath", pic.getLocalPath()); } pictureFileHelper.save(pic, true); } catch (HTML5CanvasURLParsingException e) { Log.error("Unable to update picture " + pic, e); } }
From source file:org.jenkinsci.plugins.GitLabSecurityRealm.java
private String extractToken(String content) { try {//from w ww . ja va 2 s .c o m ObjectMapper mapper = new ObjectMapper(); JsonNode jsonTree = mapper.readTree(content); JsonNode node = jsonTree.get("access_token"); if (node != null) { return node.asText(); } } catch (JsonProcessingException e) { Log.error(e.getMessage(), e); } catch (IOException e) { Log.error(e.getMessage(), e); } return null; }
From source file:com.digitalpebble.behemoth.mahout.SparseVectorsFromBehemoth.java
public int run(String[] args) throws Exception { DefaultOptionBuilder obuilder = new DefaultOptionBuilder(); ArgumentBuilder abuilder = new ArgumentBuilder(); GroupBuilder gbuilder = new GroupBuilder(); Option inputDirOpt = DefaultOptionCreator.inputOption().create(); Option outputDirOpt = DefaultOptionCreator.outputOption().create(); Option minSupportOpt = obuilder.withLongName("minSupport") .withArgument(abuilder.withName("minSupport").withMinimum(1).withMaximum(1).create()) .withDescription("(Optional) Minimum Support. Default Value: 2").withShortName("s").create(); Option typeNameOpt = obuilder.withLongName("typeToken").withRequired(false) .withArgument(abuilder.withName("typeToken").withMinimum(1).withMaximum(1).create()) .withDescription("The annotation type for Tokens").withShortName("t").create(); Option featureNameOpt = obuilder.withLongName("featureName").withRequired(false) .withArgument(abuilder.withName("featureName").withMinimum(1).withMaximum(1).create()) .withDescription(// w w w . j a v a 2s.c o m "The name of the feature containing the token values, uses the text if unspecified") .withShortName("f").create(); Option analyzerNameOpt = obuilder.withLongName("analyzerName") .withArgument(abuilder.withName("analyzerName").withMinimum(1).withMaximum(1).create()) .withDescription("The class name of the analyzer").withShortName("a").create(); Option chunkSizeOpt = obuilder.withLongName("chunkSize") .withArgument(abuilder.withName("chunkSize").withMinimum(1).withMaximum(1).create()) .withDescription("The chunkSize in MegaBytes. 100-10000 MB").withShortName("chunk").create(); Option weightOpt = obuilder.withLongName("weight").withRequired(false) .withArgument(abuilder.withName("weight").withMinimum(1).withMaximum(1).create()) .withDescription("The kind of weight to use. Currently TF or TFIDF").withShortName("wt").create(); Option minDFOpt = obuilder.withLongName("minDF").withRequired(false) .withArgument(abuilder.withName("minDF").withMinimum(1).withMaximum(1).create()) .withDescription("The minimum document frequency. Default is 1").withShortName("md").create(); Option maxDFPercentOpt = obuilder.withLongName("maxDFPercent").withRequired(false) .withArgument(abuilder.withName("maxDFPercent").withMinimum(1).withMaximum(1).create()) .withDescription( "The max percentage of docs for the DF. Can be used to remove really high frequency terms." + " Expressed as an integer between 0 and 100. Default is 99. If maxDFSigma is also set, it will override this value.") .withShortName("x").create(); Option maxDFSigmaOpt = obuilder.withLongName("maxDFSigma").withRequired(false) .withArgument(abuilder.withName("maxDFSigma").withMinimum(1).withMaximum(1).create()) .withDescription( "What portion of the tf (tf-idf) vectors to be used, expressed in times the standard deviation (sigma) of the document frequencies of these vectors." + " Can be used to remove really high frequency terms." + " Expressed as a double value. Good value to be specified is 3.0. In case the value is less then 0 no vectors " + "will be filtered out. Default is -1.0. Overrides maxDFPercent") .withShortName("xs").create(); Option minLLROpt = obuilder.withLongName("minLLR").withRequired(false) .withArgument(abuilder.withName("minLLR").withMinimum(1).withMaximum(1).create()) .withDescription("(Optional)The minimum Log Likelihood Ratio(Float) Default is " + LLRReducer.DEFAULT_MIN_LLR) .withShortName("ml").create(); Option numReduceTasksOpt = obuilder.withLongName("numReducers") .withArgument(abuilder.withName("numReducers").withMinimum(1).withMaximum(1).create()) .withDescription("(Optional) Number of reduce tasks. Default Value: 1").withShortName("nr") .create(); Option powerOpt = obuilder.withLongName("norm").withRequired(false) .withArgument(abuilder.withName("norm").withMinimum(1).withMaximum(1).create()) .withDescription( "The norm to use, expressed as either a float or \"INF\" if you want to use the Infinite norm. " + "Must be greater or equal to 0. The default is not to normalize") .withShortName("n").create(); Option logNormalizeOpt = obuilder.withLongName("logNormalize").withRequired(false) .withDescription("(Optional) Whether output vectors should be logNormalize. If set true else false") .withShortName("lnorm").create(); Option maxNGramSizeOpt = obuilder.withLongName("maxNGramSize").withRequired(false) .withArgument(abuilder.withName("ngramSize").withMinimum(1).withMaximum(1).create()) .withDescription("(Optional) The maximum size of ngrams to create" + " (2 = bigrams, 3 = trigrams, etc) Default Value:1") .withShortName("ng").create(); Option sequentialAccessVectorOpt = obuilder.withLongName("sequentialAccessVector").withRequired(false) .withDescription( "(Optional) Whether output vectors should be SequentialAccessVectors. If set true else false") .withShortName("seq").create(); Option namedVectorOpt = obuilder.withLongName("namedVector").withRequired(false) .withDescription("(Optional) Whether output vectors should be NamedVectors. If set true else false") .withShortName("nv").create(); Option overwriteOutput = obuilder.withLongName("overwrite").withRequired(false) .withDescription("If set, overwrite the output directory").withShortName("ow").create(); Option labelMDOpt = obuilder.withLongName("labelMDKey").withRequired(false) .withArgument(abuilder.withName("label_md_key").create()) .withDescription("Document metadata holding the label").withShortName("label").create(); Option helpOpt = obuilder.withLongName("help").withDescription("Print out help").withShortName("h") .create(); Group group = gbuilder.withName("Options").withOption(minSupportOpt).withOption(typeNameOpt) .withOption(featureNameOpt).withOption(analyzerNameOpt).withOption(chunkSizeOpt) .withOption(outputDirOpt).withOption(inputDirOpt).withOption(minDFOpt).withOption(maxDFSigmaOpt) .withOption(maxDFPercentOpt).withOption(weightOpt).withOption(powerOpt).withOption(minLLROpt) .withOption(numReduceTasksOpt).withOption(maxNGramSizeOpt).withOption(overwriteOutput) .withOption(helpOpt).withOption(sequentialAccessVectorOpt).withOption(namedVectorOpt) .withOption(logNormalizeOpt).withOption(labelMDOpt).create(); CommandLine cmdLine = null; try { Parser parser = new Parser(); parser.setGroup(group); parser.setHelpOption(helpOpt); cmdLine = parser.parse(args); if (cmdLine.hasOption(helpOpt)) { CommandLineUtil.printHelp(group); return -1; } if (!cmdLine.hasOption(inputDirOpt)) { CommandLineUtil.printHelp(group); return -1; } if (!cmdLine.hasOption(outputDirOpt)) { CommandLineUtil.printHelp(group); return -1; } } catch (OptionException e) { log.error("Exception", e); CommandLineUtil.printHelp(group); return -1; } Path inputDir = new Path((String) cmdLine.getValue(inputDirOpt)); Path outputDir = new Path((String) cmdLine.getValue(outputDirOpt)); int chunkSize = 100; if (cmdLine.hasOption(chunkSizeOpt)) { chunkSize = Integer.parseInt((String) cmdLine.getValue(chunkSizeOpt)); } int minSupport = 2; if (cmdLine.hasOption(minSupportOpt)) { String minSupportString = (String) cmdLine.getValue(minSupportOpt); minSupport = Integer.parseInt(minSupportString); } int maxNGramSize = 1; if (cmdLine.hasOption(maxNGramSizeOpt)) { try { maxNGramSize = Integer.parseInt(cmdLine.getValue(maxNGramSizeOpt).toString()); } catch (NumberFormatException ex) { log.warn("Could not parse ngram size option"); } } log.info("Maximum n-gram size is: {}", maxNGramSize); if (cmdLine.hasOption(overwriteOutput)) { HadoopUtil.delete(getConf(), outputDir); } float minLLRValue = LLRReducer.DEFAULT_MIN_LLR; if (cmdLine.hasOption(minLLROpt)) { minLLRValue = Float.parseFloat(cmdLine.getValue(minLLROpt).toString()); } log.info("Minimum LLR value: {}", minLLRValue); int reduceTasks = 1; if (cmdLine.hasOption(numReduceTasksOpt)) { reduceTasks = Integer.parseInt(cmdLine.getValue(numReduceTasksOpt).toString()); } log.info("Number of reduce tasks: {}", reduceTasks); Class<? extends Analyzer> analyzerClass = DefaultAnalyzer.class; if (cmdLine.hasOption(analyzerNameOpt)) { String className = cmdLine.getValue(analyzerNameOpt).toString(); analyzerClass = Class.forName(className).asSubclass(Analyzer.class); // try instantiating it, b/c there isn't any point in setting it // if // you can't instantiate it ClassUtils.instantiateAs(analyzerClass, Analyzer.class); } String type = null; String featureName = ""; if (cmdLine.hasOption(typeNameOpt)) { type = cmdLine.getValue(typeNameOpt).toString(); Object tempFN = cmdLine.getValue(featureNameOpt); if (tempFN != null) { featureName = tempFN.toString(); log.info("Getting tokens from " + type + "." + featureName.toString()); } else log.info("Getting tokens from " + type); } boolean processIdf; if (cmdLine.hasOption(weightOpt)) { String wString = cmdLine.getValue(weightOpt).toString(); if ("tf".equalsIgnoreCase(wString)) { processIdf = false; } else if ("tfidf".equalsIgnoreCase(wString)) { processIdf = true; } else { throw new OptionException(weightOpt); } } else { processIdf = true; } int minDf = 1; if (cmdLine.hasOption(minDFOpt)) { minDf = Integer.parseInt(cmdLine.getValue(minDFOpt).toString()); } int maxDFPercent = 99; if (cmdLine.hasOption(maxDFPercentOpt)) { maxDFPercent = Integer.parseInt(cmdLine.getValue(maxDFPercentOpt).toString()); } double maxDFSigma = -1.0; if (cmdLine.hasOption(maxDFSigmaOpt)) { maxDFSigma = Double.parseDouble(cmdLine.getValue(maxDFSigmaOpt).toString()); } float norm = PartialVectorMerger.NO_NORMALIZING; if (cmdLine.hasOption(powerOpt)) { String power = cmdLine.getValue(powerOpt).toString(); if ("INF".equals(power)) { norm = Float.POSITIVE_INFINITY; } else { norm = Float.parseFloat(power); } } boolean logNormalize = false; if (cmdLine.hasOption(logNormalizeOpt)) { logNormalize = true; } String labelMDKey = null; if (cmdLine.hasOption(labelMDOpt)) { labelMDKey = cmdLine.getValue(labelMDOpt).toString(); } Configuration conf = getConf(); Path tokenizedPath = new Path(outputDir, DocumentProcessor.TOKENIZED_DOCUMENT_OUTPUT_FOLDER); // no annotation type degfin if (type != null) { BehemothDocumentProcessor.tokenizeDocuments(inputDir, type, featureName, tokenizedPath); } // no annotation type defined : rely on Lucene's analysers else { BehemothDocumentProcessor.tokenizeDocuments(inputDir, analyzerClass, tokenizedPath, conf); } boolean sequentialAccessOutput = false; if (cmdLine.hasOption(sequentialAccessVectorOpt)) { sequentialAccessOutput = true; } boolean namedVectors = false; if (cmdLine.hasOption(namedVectorOpt)) { namedVectors = true; } boolean shouldPrune = maxDFSigma >= 0.0; String tfDirName = shouldPrune ? DictionaryVectorizer.DOCUMENT_VECTOR_OUTPUT_FOLDER + "-toprune" : DictionaryVectorizer.DOCUMENT_VECTOR_OUTPUT_FOLDER; try { if (!processIdf) { DictionaryVectorizer.createTermFrequencyVectors(tokenizedPath, outputDir, tfDirName, conf, minSupport, maxNGramSize, minLLRValue, norm, logNormalize, reduceTasks, chunkSize, sequentialAccessOutput, namedVectors); } else { DictionaryVectorizer.createTermFrequencyVectors(tokenizedPath, outputDir, tfDirName, conf, minSupport, maxNGramSize, minLLRValue, -1.0f, false, reduceTasks, chunkSize, sequentialAccessOutput, namedVectors); } Pair<Long[], List<Path>> docFrequenciesFeatures = null; // Should document frequency features be processed if (shouldPrune || processIdf) { docFrequenciesFeatures = TFIDFConverter.calculateDF(new Path(outputDir, tfDirName), outputDir, conf, chunkSize); } long maxDF = maxDFPercent; // if we are pruning by std dev, then // this will get changed if (shouldPrune) { Path dfDir = new Path(outputDir, TFIDFConverter.WORDCOUNT_OUTPUT_FOLDER); Path stdCalcDir = new Path(outputDir, HighDFWordsPruner.STD_CALC_DIR); // Calculate the standard deviation double stdDev = BasicStats.stdDevForGivenMean(dfDir, stdCalcDir, 0.0, conf); long vectorCount = docFrequenciesFeatures.getFirst()[1]; maxDF = (int) (100.0 * maxDFSigma * stdDev / vectorCount); // Prune the term frequency vectors Path tfDir = new Path(outputDir, tfDirName); Path prunedTFDir = new Path(outputDir, DictionaryVectorizer.DOCUMENT_VECTOR_OUTPUT_FOLDER); Path prunedPartialTFDir = new Path(outputDir, DictionaryVectorizer.DOCUMENT_VECTOR_OUTPUT_FOLDER + "-partial"); if (processIdf) { HighDFWordsPruner.pruneVectors(tfDir, prunedTFDir, prunedPartialTFDir, maxDF, conf, docFrequenciesFeatures, -1.0f, false, reduceTasks); } else { HighDFWordsPruner.pruneVectors(tfDir, prunedTFDir, prunedPartialTFDir, maxDF, conf, docFrequenciesFeatures, norm, logNormalize, reduceTasks); } HadoopUtil.delete(new Configuration(conf), tfDir); } if (processIdf) { TFIDFConverter.processTfIdf(new Path(outputDir, DictionaryVectorizer.DOCUMENT_VECTOR_OUTPUT_FOLDER), outputDir, conf, docFrequenciesFeatures, minDf, maxDF, norm, logNormalize, sequentialAccessOutput, namedVectors, reduceTasks); } // dump labels? if (labelMDKey != null) { conf.set(BehemothDocumentProcessor.MD_LABEL, labelMDKey); BehemothDocumentProcessor.dumpLabels(inputDir, new Path(outputDir, "labels"), conf); } } catch (RuntimeException e) { Log.error("Exception caught", e); return -1; } return 0; }
From source file:com.evolveum.midpoint.model.impl.controller.ModelController.java
@Override public void importObjectsFromFile(File input, ImportOptionsType options, Task task, OperationResult parentResult) throws FileNotFoundException { OperationResult result = parentResult.createSubresult(IMPORT_OBJECTS_FROM_FILE); FileInputStream fis;/*from ww w . j a v a 2 s .c o m*/ try { fis = new FileInputStream(input); } catch (FileNotFoundException e) { String msg = "Error reading from file " + input + ": " + e.getMessage(); result.recordFatalError(msg, e); throw e; } try { importObjectsFromStream(fis, options, task, parentResult); } catch (RuntimeException e) { result.recordFatalError(e); throw e; } finally { try { fis.close(); } catch (IOException e) { Log.error("Error closing file " + input + ": " + e.getMessage(), e); } } result.computeStatus(); }
From source file:org.egov.eis.web.controller.reports.EmployeeAssignmentReportPDFController.java
@RequestMapping(value = "/reports/employeeassignments/pdf", method = RequestMethod.GET) public @ResponseBody ResponseEntity<byte[]> generateEmployeeAssignmentsPDF(final HttpServletRequest request, @RequestParam("code") final String code, @RequestParam("name") final String name, @RequestParam("departmentId") final Long departmentId, @RequestParam("designationId") final Long designationId, @RequestParam("positionId") final Long positionId, @RequestParam("contentType") final String contentType, @RequestParam("date") final Date date, final HttpSession session, final Model model) throws DocumentException { final EmployeeAssignmentSearch employeeAssignmentSearch = new EmployeeAssignmentSearch(); employeeAssignmentSearch.setEmployeeCode(code); employeeAssignmentSearch.setEmployeeName(name); employeeAssignmentSearch.setDepartment(departmentId); employeeAssignmentSearch.setDesignation(designationId); employeeAssignmentSearch.setPosition(positionId); employeeAssignmentSearch.setAssignmentDate(date); final List<Employee> employeeList = assignmentService.searchEmployeeAssignments(employeeAssignmentSearch); final StringBuilder searchCriteria = new StringBuilder(); searchCriteria.append("Employee Assignment Report as on "); if (employeeAssignmentSearch.getAssignmentDate() != null) searchCriteria.append(DateUtils.getDefaultFormattedDate(employeeAssignmentSearch.getAssignmentDate())); if (StringUtils.isNotBlank(employeeAssignmentSearch.getEmployeeName())) searchCriteria.append(", Employee Name : ").append(employeeAssignmentSearch.getEmployeeName()) .append(""); if (StringUtils.isNotBlank(employeeAssignmentSearch.getEmployeeCode())) searchCriteria.append(", Employee Code : ").append(employeeAssignmentSearch.getEmployeeCode()) .append(" "); if (employeeAssignmentSearch.getDepartment() != null) { final Department department = departmentService .getDepartmentById(employeeAssignmentSearch.getDepartment()); searchCriteria.append(" for Department : ").append(department.getName()).append(" "); }/*w w w .ja v a 2 s . c o m*/ if (employeeAssignmentSearch.getDesignation() != null) { final Designation designation = designationService .getDesignationById(employeeAssignmentSearch.getDesignation()); searchCriteria.append(" and Designation : ").append(designation.getName()).append(" "); } if (employeeAssignmentSearch.getPosition() != null) { final Position position = positionMasterService.getPositionById(employeeAssignmentSearch.getPosition()); searchCriteria.append(" and Position : ").append(position.getName()).append(" "); } String searchString = StringUtils.EMPTY; if (searchCriteria.toString().endsWith(" ")) searchString = searchCriteria.substring(0, searchCriteria.length() - 1); final List<EmployeeAssignmentSearch> searchResult = new ArrayList<EmployeeAssignmentSearch>(); Map<String, String> tempAssignments = null; EmployeeAssignmentSearch empAssignmentSearch = null; int maxTempAssignments = 0; for (final Employee employee : employeeList) { int index = 0; tempAssignments = new HashMap<String, String>(); empAssignmentSearch = new EmployeeAssignmentSearch(); empAssignmentSearch.setEmployeeCode(employee.getCode()); empAssignmentSearch.setEmployeeName(employee.getName()); for (final Assignment assignment : employee.getAssignments()) if (assignment.getPrimary()) { empAssignmentSearch.setDepartmentName(assignment.getDepartment().getName()); empAssignmentSearch.setDesignationName(assignment.getDesignation().getName()); empAssignmentSearch.setPositionName(assignment.getPosition().getName()); empAssignmentSearch.setDateRange(DateUtils.getDefaultFormattedDate(assignment.getFromDate()) + " - " + DateUtils.getDefaultFormattedDate(assignment.getToDate())); } else { tempAssignments.put("department_" + String.valueOf(index), assignment.getDepartment().getName()); tempAssignments.put("designation_" + String.valueOf(index), assignment.getDesignation().getName()); tempAssignments.put("position_" + String.valueOf(index), assignment.getPosition().getName()); tempAssignments.put("daterange_" + String.valueOf(index), DateUtils.getDefaultFormattedDate(assignment.getFromDate()) + " - " + DateUtils.getDefaultFormattedDate(assignment.getToDate())); index++; } empAssignmentSearch.setTempPositionDetails(tempAssignments); searchResult.add(empAssignmentSearch); if (employee.getAssignments().size() >= maxTempAssignments) maxTempAssignments = employee.getAssignments().size(); } JasperPrint jasperPrint; ByteArrayOutputStream outputBytes = null; try { jasperPrint = generateEmployeeAssignmentReport(searchResult, maxTempAssignments, searchString); outputBytes = new ByteArrayOutputStream(MB); JasperExportManager.exportReportToPdfStream(jasperPrint, outputBytes); } catch (final Exception e) { Log.error("Error while generating employee assignment report ", e); } final ReportOutput reportOutput = new ReportOutput(); reportOutput.setReportOutputData(outputBytes.toByteArray()); final HttpHeaders headers = new HttpHeaders(); if (contentType.equalsIgnoreCase("pdf")) { reportOutput.setReportFormat(ReportFormat.PDF); reportOutput.setReportFormat(ReportFormat.PDF); headers.setContentType(MediaType.parseMediaType("application/pdf")); headers.add("content-disposition", "inline;filename=EmployeeAssignment.pdf"); } else { reportOutput.setReportFormat(ReportFormat.XLS); headers.setContentType(MediaType.parseMediaType("application/vnd.ms-excel")); headers.add("content-disposition", "inline;filename=EmployeeAssignment.xls"); } return new ResponseEntity<byte[]>(reportOutput.getReportOutputData(), headers, HttpStatus.CREATED); }
From source file:org.intermine.web.struts.InitialiserPlugin.java
/** * Load keys that describe how objects should be uniquely identified */// ww w. j ava 2s. c o m private BagQueryConfig loadBagQueries(ServletContext servletContext, ObjectStore os, Properties webProperties) { BagQueryConfig bagQueryConfig = null; InputStream is = servletContext.getResourceAsStream("/WEB-INF/bag-queries.xml"); if (is != null) { try { bagQueryConfig = BagQueryHelper.readBagQueryConfig(os.getModel(), is); } catch (Exception e) { Log.error("Error loading class bag queries. ", e); blockingErrorKeys.put("errors.init.bagqueries", e.getMessage()); } InputStream isBag = getClass().getClassLoader().getResourceAsStream("extraBag.properties"); Properties bagProperties = new Properties(); if (isBag != null) { try { bagProperties.load(isBag); bagQueryConfig.setConnectField(bagProperties.getProperty("extraBag.connectField")); bagQueryConfig.setExtraConstraintClassName(bagProperties.getProperty("extraBag.className")); bagQueryConfig.setConstrainField(bagProperties.getProperty("extraBag.constrainField")); } catch (IOException e) { Log.error("Error loading extraBag.properties. ", e); blockingErrorKeys.put("errors.init.extrabagloading", null); } } else { LOG.error("Could not find extraBag.properties file"); blockingErrorKeys.put("errors.init.extrabag", null); } } else { // can used defaults so just log a warning LOG.warn("No custom bag queries found - using default query"); } return bagQueryConfig; }
From source file:org.jenkinsci.plugins.viewer.XPathConfig.java
/** * Returns the xml block from the given file using the given xpath expression. * //from ww w . ja v a 2 s. co m * @return the xml block */ @SuppressWarnings("rawtypes") public Element getXmlBlock(File xmlFile) { if (StringUtils.isEmpty(this.getXpath())) { return null; } try { Document dom = new SAXReader().read(xmlFile); List nodes = dom.selectNodes(this.xpath); if (nodes.size() > 0) { return (Element) nodes.get(0); } } catch (Exception e) { Log.error("Exception getting xml block from config.xml: ", e); } return null; }