Examples with Analyzers org.talend.dataquality.common.inference.Analyzers used on opensource projects

Example 1 with Analyzers

use of org.talend.dataquality.common.inference.Analyzers in project data-prep by Talend.

the class AnalyzerService method build.

/**
 * Build a {@link Analyzer} to analyze records with columns (in <code>columns</code>). <code>settings</code> give
 * all the wanted analysis settings for the analyzer.
 *
 * @param columns  A list of columns, may be null or empty.
 * @param settings A varargs with {@link Analysis}. Duplicates are possible in varargs but will be considered only
 *                 once.
 * @return A ready to use {@link Analyzer}.
 */
public Analyzer<Analyzers.Result> build(List<ColumnMetadata> columns, Analysis... settings) {
    if (columns == null || columns.isEmpty()) {
        return Analyzers.with(NullAnalyzer.INSTANCE);
    }
    // Get all needed analysis
    final Set<Analysis> all = EnumSet.noneOf(Analysis.class);
    for (Analysis setting : settings) {
        if (setting != null) {
            all.add(setting);
            all.addAll(Arrays.asList(setting.dependencies));
        }
    }
    if (all.isEmpty()) {
        return Analyzers.with(NullAnalyzer.INSTANCE);
    }
    // Column types
    DataTypeEnum[] types = TypeUtils.convert(columns);
    // Semantic domains
    List<String> domainList = // 
    columns.stream().map(// 
    ColumnMetadata::getDomain).map(// 
    d -> StringUtils.isBlank(d) ? SemanticCategoryEnum.UNKNOWN.getId() : d).collect(Collectors.toList());
    final String[] domains = domainList.toArray(new String[domainList.size()]);
    DictionarySnapshot dictionarySnapshot = dictionarySnapshotProvider.get();
    // Build all analyzers
    List<Analyzer> analyzers = new ArrayList<>();
    for (Analysis setting : settings) {
        switch(setting) {
            case SEMANTIC:
                final SemanticAnalyzer semanticAnalyzer = new SemanticAnalyzer(dictionarySnapshot);
                semanticAnalyzer.setLimit(Integer.MAX_VALUE);
                semanticAnalyzer.setMetadata(Metadata.HEADER_NAME, extractColumnNames(columns));
                analyzers.add(semanticAnalyzer);
                break;
            case HISTOGRAM:
                analyzers.add(new StreamDateHistogramAnalyzer(columns, types, dateParser));
                analyzers.add(new StreamNumberHistogramAnalyzer(types));
                break;
            case QUALITY:
                final DataTypeQualityAnalyzer dataTypeQualityAnalyzer = new DataTypeQualityAnalyzer(types);
                columns.forEach(c -> dataTypeQualityAnalyzer.addCustomDateTimePattern(RowMetadataUtils.getMostUsedDatePattern(c)));
                analyzers.add(new ValueQualityAnalyzer(dataTypeQualityAnalyzer, new SemanticQualityAnalyzer(dictionarySnapshot, domains, false), // NOSONAR
                true));
                break;
            case CARDINALITY:
                analyzers.add(new CardinalityAnalyzer());
                break;
            case PATTERNS:
                analyzers.add(buildPatternAnalyzer(columns));
                break;
            case LENGTH:
                analyzers.add(new TextLengthAnalyzer());
                break;
            case QUANTILES:
                boolean acceptQuantiles = false;
                for (DataTypeEnum type : types) {
                    if (type == DataTypeEnum.INTEGER || type == DataTypeEnum.DOUBLE) {
                        acceptQuantiles = true;
                        break;
                    }
                }
                if (acceptQuantiles) {
                    analyzers.add(new QuantileAnalyzer(types));
                }
                break;
            case SUMMARY:
                analyzers.add(new SummaryAnalyzer(types));
                break;
            case TYPE:
                boolean shouldUseTypeAnalysis = true;
                for (Analysis analysis : settings) {
                    if (analysis == Analysis.QUALITY) {
                        shouldUseTypeAnalysis = false;
                        break;
                    }
                }
                if (shouldUseTypeAnalysis) {
                    final List<String> mostUsedDatePatterns = getMostUsedDatePatterns(columns);
                    analyzers.add(new DataTypeAnalyzer(mostUsedDatePatterns));
                } else {
                    LOGGER.warn("Disabled {} analysis (conflicts with {}).", setting, Analysis.QUALITY);
                }
                break;
            case FREQUENCY:
                analyzers.add(new DataTypeFrequencyAnalyzer());
                break;
            default:
                throw new IllegalArgumentException("Missing support for '" + setting + "'.");
        }
    }
    // Merge all analyzers into one
    final Analyzer<Analyzers.Result> analyzer = Analyzers.with(analyzers.toArray(new Analyzer[analyzers.size()]));
    analyzer.init();
    if (LOGGER.isDebugEnabled()) {
        // Wrap analyzer for usage monitoring (to diagnose non-closed analyzer issues).
        return new ResourceMonitoredAnalyzer(analyzer);
    } else {
        return analyzer;
    }
}

Example 2 with Analyzers

use of org.talend.dataquality.common.inference.Analyzers in project data-prep by Talend.

the class SchemaAnalysis method analyze.

@Override
public void analyze(String dataSetId) {
    if (StringUtils.isEmpty(dataSetId)) {
        throw new IllegalArgumentException("Data set id cannot be null or empty.");
    }
    DistributedLock datasetLock = repository.createDatasetMetadataLock(dataSetId);
    datasetLock.lock();
    try {
        DataSetMetadata metadata = repository.get(dataSetId);
        if (metadata == null) {
            LOGGER.info("Unable to analyze schema of data set #{}: seems to be removed.", dataSetId);
            return;
        }
        // Schema analysis
        try (Stream<DataSetRow> stream = store.stream(metadata, 100)) {
            LOGGER.info("Analyzing schema in dataset #{}...", dataSetId);
            // Configure analyzers
            final List<ColumnMetadata> columns = metadata.getRowMetadata().getColumns();
            try (Analyzer<Analyzers.Result> analyzer = analyzerService.schemaAnalysis(columns)) {
                // Determine schema for the content.
                stream.limit(100).map(row -> row.toArray(DataSetRow.SKIP_TDP_ID)).forEach(analyzer::analyze);
                // Find the best suitable type
                adapter.adapt(columns, analyzer.getResult());
                LOGGER.info("Analyzed schema in dataset #{}.", dataSetId);
                metadata.getLifecycle().schemaAnalyzed(true);
                repository.save(metadata);
            }
        } catch (Exception e) {
            LOGGER.error("Unable to analyse schema for dataset " + dataSetId + ".", e);
            TDPException.rethrowOrWrap(e, UNABLE_TO_ANALYZE_COLUMN_TYPES);
        }
    } finally {
        datasetLock.unlock();
    }
}