Examples with TimeRange com.linkedin.thirdeye.api.TimeRange used on opensource projects

Example 1 with TimeRange

use of com.linkedin.thirdeye.api.TimeRange in project pinot by linkedin.

the class AnomaliesResource method getTimeseriesOffsetedTimes.

private TimeRange getTimeseriesOffsetedTimes(long anomalyStartTime, long anomalyEndTime, DatasetConfigDTO datasetConfig) {
    TimeUnit dataTimeunit = datasetConfig.getTimeUnit();
    Period offsetPeriod;
    switch(dataTimeunit) {
        case // 3 days
        DAYS:
            offsetPeriod = new Period(0, 0, 0, 3, 0, 0, 0, 0);
            break;
        case // 10 hours
        HOURS:
            offsetPeriod = new Period(0, 0, 0, 0, 10, 0, 0, 0);
            break;
        case // 60 minutes
        MINUTES:
            offsetPeriod = new Period(0, 0, 0, 0, 0, 60, 0, 0);
            break;
        default:
            offsetPeriod = new Period();
    }
    DateTimeZone dateTimeZone = DateTimeZone.forID(datasetConfig.getTimezone());
    DateTime anomalyStartDateTime = new DateTime(anomalyStartTime, dateTimeZone);
    DateTime anomalyEndDateTime = new DateTime(anomalyEndTime, dateTimeZone);
    anomalyStartDateTime = anomalyStartDateTime.minus(offsetPeriod);
    anomalyEndDateTime = anomalyEndDateTime.plus(offsetPeriod);
    anomalyStartTime = anomalyStartDateTime.getMillis();
    anomalyEndTime = anomalyEndDateTime.getMillis();
    try {
        Long maxDataTime = CACHE_REGISTRY.getCollectionMaxDataTimeCache().get(datasetConfig.getDataset());
        if (anomalyEndTime > maxDataTime) {
            anomalyEndTime = maxDataTime;
        }
    } catch (ExecutionException e) {
        LOG.error("Exception when reading max time for {}", datasetConfig.getDataset(), e);
    }
    TimeRange range = new TimeRange(anomalyStartTime, anomalyEndTime);
    return range;
}

Example 2 with TimeRange

use of com.linkedin.thirdeye.api.TimeRange in project pinot by linkedin.

the class DataResource method getTimeRangeFromLabel.

/**
   *  convert label from WowSummaryModel to a TimeRange
   * @param dataset
   * @param timeZoneForCollection
   * @param label
   * @return
   */
private TimeRange getTimeRangeFromLabel(String dataset, DateTimeZone timeZoneForCollection, String label) {
    long start = 0;
    long end = 0;
    long datasetMaxTime = Utils.getMaxDataTimeForDataset(dataset);
    switch(label) {
        case "Most Recent Hour":
            end = datasetMaxTime;
            start = end - TimeUnit.MILLISECONDS.convert(1, TimeUnit.HOURS);
            break;
        case "Today":
            end = System.currentTimeMillis();
            start = new DateTime().withTimeAtStartOfDay().getMillis();
            break;
        case "Yesterday":
            end = new DateTime().withTimeAtStartOfDay().getMillis();
            start = end - TimeUnit.MILLISECONDS.convert(1, TimeUnit.DAYS);
            break;
        case "Last 7 Days":
            end = System.currentTimeMillis();
            start = new DateTime(end).minusDays(6).withTimeAtStartOfDay().getMillis();
            break;
        default:
    }
    TimeRange timeRange = new TimeRange(start, end);
    return timeRange;
}

Example 3 with TimeRange

use of com.linkedin.thirdeye.api.TimeRange in project pinot by linkedin.

the class AnomaliesResource method getAnomalyDetails.

/**
   * Generates Anomaly Details for each merged anomaly
   * @param mergedAnomaly
   * @param datasetConfig
   * @param timeSeriesDateFormatter
   * @param startEndDateFormatterHours
   * @param startEndDateFormatterDays
   * @param externalUrl
   * @return
   */
private AnomalyDetails getAnomalyDetails(MergedAnomalyResultDTO mergedAnomaly, DatasetConfigDTO datasetConfig, DateTimeFormatter timeSeriesDateFormatter, DateTimeFormatter startEndDateFormatterHours, DateTimeFormatter startEndDateFormatterDays, String externalUrl) throws Exception {
    String dataset = datasetConfig.getDataset();
    String metricName = mergedAnomaly.getMetric();
    AnomalyFunctionDTO anomalyFunctionSpec = anomalyFunctionDAO.findById(mergedAnomaly.getFunctionId());
    BaseAnomalyFunction anomalyFunction = anomalyFunctionFactory.fromSpec(anomalyFunctionSpec);
    String aggGranularity = constructAggGranularity(datasetConfig);
    long anomalyStartTime = mergedAnomaly.getStartTime();
    long anomalyEndTime = mergedAnomaly.getEndTime();
    TimeRange range = getTimeseriesOffsetedTimes(anomalyStartTime, anomalyEndTime, datasetConfig);
    long currentStartTime = range.getStart();
    long currentEndTime = range.getEnd();
    DimensionMap dimensions = mergedAnomaly.getDimensions();
    TimeGranularity timeGranularity = Utils.getAggregationTimeGranularity(aggGranularity, anomalyFunctionSpec.getCollection());
    long bucketMillis = timeGranularity.toMillis();
    AnomalyDetails anomalyDetails = null;
    try {
        AnomalyDetectionInputContext adInputContext = TimeBasedAnomalyMerger.fetchDataByDimension(currentStartTime, currentEndTime, dimensions, anomalyFunction, mergedAnomalyResultDAO, overrideConfigDAO, true);
        MetricTimeSeries metricTimeSeries = adInputContext.getDimensionKeyMetricTimeSeriesMap().get(dimensions);
        // Transform time series with scaling factor
        List<ScalingFactor> scalingFactors = adInputContext.getScalingFactors();
        if (CollectionUtils.isNotEmpty(scalingFactors)) {
            Properties properties = anomalyFunction.getProperties();
            MetricTransfer.rescaleMetric(metricTimeSeries, currentStartTime, scalingFactors, anomalyFunctionSpec.getTopicMetric(), properties);
        }
        List<MergedAnomalyResultDTO> knownAnomalies = adInputContext.getKnownMergedAnomalies().get(dimensions);
        // Known anomalies are ignored (the null parameter) because 1. we can reduce users' waiting time and 2. presentation
        // data does not need to be as accurate as the one used for detecting anomalies
        AnomalyTimelinesView anomalyTimelinesView = anomalyFunction.getTimeSeriesView(metricTimeSeries, bucketMillis, anomalyFunctionSpec.getTopicMetric(), currentStartTime, currentEndTime, knownAnomalies);
        anomalyDetails = constructAnomalyDetails(metricName, dataset, datasetConfig, mergedAnomaly, anomalyFunctionSpec, currentStartTime, currentEndTime, anomalyTimelinesView, timeSeriesDateFormatter, startEndDateFormatterHours, startEndDateFormatterDays, externalUrl);
    } catch (Exception e) {
        LOG.error("Exception in constructing anomaly wrapper for anomaly {}", mergedAnomaly.getId(), e);
    }
    return anomalyDetails;
}

Example 4 with TimeRange

use of com.linkedin.thirdeye.api.TimeRange in project pinot by linkedin.

the class DataResource method getWowSummary.

@GET
@Path("dashboard/wowsummary")
public WowSummary getWowSummary(@QueryParam("dashboard") String dashboard, @QueryParam("timeRanges") String timeRanges) {
    WowSummary wowSummary = new WowSummary();
    if (StringUtils.isBlank(dashboard)) {
        return wowSummary;
    }
    List<Long> metricIds = getMetricIdsByDashboard(dashboard);
    List<String> timeRangeLabels = Lists.newArrayList(timeRanges.split(","));
    // Sort metric's id and metric expression by collections
    Multimap<String, Long> datasetToMetrics = ArrayListMultimap.create();
    Multimap<String, MetricExpression> datasetToMetricExpressions = ArrayListMultimap.create();
    Map<Long, MetricConfigDTO> metricIdToMetricConfig = new HashMap<>();
    for (long metricId : metricIds) {
        MetricConfigDTO metricConfig = metricConfigDAO.findById(metricId);
        metricIdToMetricConfig.put(metricId, metricConfig);
        datasetToMetrics.put(metricConfig.getDataset(), metricId);
        datasetToMetricExpressions.put(metricConfig.getDataset(), ThirdEyeUtils.getMetricExpressionFromMetricConfig(metricConfig));
    }
    Multimap<String, MetricSummary> metricAliasToMetricSummariesMap = ArrayListMultimap.create();
    // Create query request for each collection
    for (String dataset : datasetToMetrics.keySet()) {
        TabularViewRequest request = new TabularViewRequest();
        request.setCollection(dataset);
        request.setMetricExpressions(new ArrayList<>(datasetToMetricExpressions.get(dataset)));
        // user and server's timezone, including daylight saving time.
        for (String timeRangeLabel : timeRangeLabels) {
            DateTimeZone timeZoneForCollection = Utils.getDataTimeZone(dataset);
            TimeRange timeRange = getTimeRangeFromLabel(dataset, timeZoneForCollection, timeRangeLabel);
            long currentEnd = timeRange.getEnd();
            long currentStart = timeRange.getStart();
            System.out.println(timeRangeLabel + "Current start end " + new DateTime(currentStart) + " " + new DateTime(currentEnd));
            TimeGranularity timeGranularity = new TimeGranularity(1, TimeUnit.HOURS);
            request.setBaselineStart(new DateTime(currentStart, timeZoneForCollection).minusDays(7));
            request.setBaselineEnd(new DateTime(currentEnd, timeZoneForCollection).minusDays(7));
            request.setCurrentStart(new DateTime(currentStart, timeZoneForCollection));
            request.setCurrentEnd(new DateTime(currentEnd, timeZoneForCollection));
            request.setTimeGranularity(timeGranularity);
            TabularViewHandler handler = new TabularViewHandler(queryCache);
            try {
                TabularViewResponse tabularViewResponse = handler.process(request);
                for (String metric : tabularViewResponse.getMetrics()) {
                    MetricDataset metricDataset = new MetricDataset(metric, dataset);
                    MetricConfigDTO metricConfig = CACHE_REGISTRY_INSTANCE.getMetricConfigCache().get(metricDataset);
                    Long metricId = metricConfig.getId();
                    String metricAlias = metricConfig.getAlias();
                    GenericResponse response = tabularViewResponse.getData().get(metric);
                    MetricSummary metricSummary = new MetricSummary();
                    metricSummary.setMetricId(metricId);
                    metricSummary.setMetricName(metricConfig.getName());
                    metricSummary.setMetricAlias(metricAlias);
                    List<String[]> data = response.getResponseData();
                    double baselineValue = 0;
                    double currentValue = 0;
                    for (String[] responseData : data) {
                        baselineValue = baselineValue + Double.valueOf(responseData[0]);
                        currentValue = currentValue + Double.valueOf(responseData[1]);
                    }
                    double percentageChange = (currentValue - baselineValue) * 100 / baselineValue;
                    metricSummary.setBaselineValue(baselineValue);
                    metricSummary.setCurrentValue(currentValue);
                    metricSummary.setWowPercentageChange(percentageChange);
                    metricAliasToMetricSummariesMap.put(metricAlias, metricSummary);
                }
            } catch (Exception e) {
                LOG.error("Exception while processing /data/tabular call", e);
            }
        }
    }
    wowSummary.setMetricAliasToMetricSummariesMap(metricAliasToMetricSummariesMap);
    return wowSummary;
}