Examples with MetricSummary com.linkedin.thirdeye.dashboard.resources.v2.pojo.MetricSummary used on opensource projects

Example 1 with MetricSummary

use of com.linkedin.thirdeye.dashboard.resources.v2.pojo.MetricSummary 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;
}

Example 2 with MetricSummary

use of com.linkedin.thirdeye.dashboard.resources.v2.pojo.MetricSummary in project pinot by linkedin.

the class DataResource method getMetricSummary.

/**
   * Returns percentage change between current values and baseline values. The values are
   * aggregated according to the number of buckets. If the bucket number is 1, then all values
   * between the given time ranges are sorted to the corresponding bucket and aggregated.
   *
   * Note: For current implementation, we assume the number of buckets is always 1.
   */
@GET
@Path("dashboard/metricsummary")
public List<MetricSummary> getMetricSummary(@QueryParam("dashboard") String dashboard, @QueryParam("timeRange") String timeRange) {
    List<MetricSummary> metricsSummary = new ArrayList<>();
    if (StringUtils.isBlank(dashboard)) {
        return metricsSummary;
    }
    List<Long> metricIds = getMetricIdsByDashboard(dashboard);
    // 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));
    }
    // 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)));
        // The input start and end time (i.e., currentStart, currentEnd, baselineStart, and
        // baselineEnd) are given in millisecond since epoch, which is timezone insensitive. On the
        // other hand, the start and end time of the request to be sent to backend database (e.g.,
        // Pinot) could be converted to SimpleDateFormat, which is timezone sensitive. Therefore,
        // we need to store user's start and end time in DateTime objects with data's timezone
        // in order to ensure that the conversion to SimpleDateFormat is always correct regardless
        // user and server's timezone, including daylight saving time.
        String[] tokens = timeRange.split("_");
        TimeGranularity timeGranularity = new TimeGranularity(Integer.valueOf(tokens[0]), TimeUnit.valueOf(tokens[1]));
        long currentEnd = Utils.getMaxDataTimeForDataset(dataset);
        long currentStart = currentEnd - TimeUnit.MILLISECONDS.convert(Long.valueOf(tokens[0]), TimeUnit.valueOf(tokens[1]));
        DateTimeZone timeZoneForCollection = Utils.getDataTimeZone(dataset);
        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();
                GenericResponse response = tabularViewResponse.getData().get(metric);
                MetricSummary metricSummary = new MetricSummary();
                metricSummary.setMetricId(metricId);
                metricSummary.setMetricName(metricConfig.getName());
                metricSummary.setMetricAlias(metricConfig.getAlias());
                String[] responseData = response.getResponseData().get(0);
                double baselineValue = Double.valueOf(responseData[0]);
                double curentvalue = Double.valueOf(responseData[1]);
                double percentageChange = (curentvalue - baselineValue) * 100 / baselineValue;
                metricSummary.setBaselineValue(baselineValue);
                metricSummary.setCurrentValue(curentvalue);
                metricSummary.setWowPercentageChange(percentageChange);
                AnomaliesSummary anomaliesSummary = anomaliesResoure.getAnomalyCountForMetricInRange(metricId, currentStart, currentEnd);
                metricSummary.setAnomaliesSummary(anomaliesSummary);
                metricsSummary.add(metricSummary);
            }
        } catch (Exception e) {
            LOG.error("Exception while processing /data/tabular call", e);
        }
    }
    return metricsSummary;
}