Java Code Examples for org.apache.commons.collections4.MapUtils#getDoubleValue()

public BaselineAlgorithm(DataProvider provider, DetectionConfigDTO config, long startTime, long endTime) {
  super(provider, config, startTime, endTime);

  Preconditions.checkArgument(config.getProperties().containsKey(PROP_METRIC_URN));

  String metricUrn = MapUtils.getString(config.getProperties(), PROP_METRIC_URN);
  MetricEntity me = MetricEntity.fromURN(metricUrn);
  this.slice = MetricSlice.from(me.getId(), this.startTime, this.endTime, me.getFilters());

  int weeks = MapUtils.getIntValue(config.getProperties(), PROP_WEEKS, PROP_WEEKS_DEFAULT);
  BaselineAggregateType aggregation = BaselineAggregateType.valueOf(MapUtils.getString(config.getProperties(), PROP_AGGREGATION, PROP_AGGREGATION_DEFAULT));
  DateTimeZone timezone = DateTimeZone.forID(MapUtils.getString(this.config.getProperties(), PROP_TIMEZONE, PROP_TIMEZONE_DEFAULT));
  this.baseline = BaselineAggregate.fromWeekOverWeek(aggregation, weeks, 1, timezone);

  this.change = MapUtils.getDoubleValue(config.getProperties(), PROP_CHANGE, PROP_CHANGE_DEFAULT);
  this.difference = MapUtils.getDoubleValue(config.getProperties(), PROP_DIFFERENCE, PROP_DIFFERENCE_DEFAULT);
}
 

public CallGraphPipeline(String outputName, Set<String> inputNames, Map<String, Object> properties) {
  super(outputName, inputNames);
  this.metricDAO = DAORegistry.getInstance().getMetricConfigDAO();
  this.datasetDAO = DAORegistry.getInstance().getDatasetConfigDAO();
  this.cache = ThirdEyeCacheRegistry.getInstance().getQueryCache();
  this.dataset = MapUtils.getString(properties, PROP_DATASET, PROP_DATASET_DEFAULT);
  this.metricCount = MapUtils.getString(properties, PROP_METRIC_COUNT, PROP_METRIC_COUNT_DEFAULT);
  this.metricLatency = MapUtils.getString(properties, PROP_METRIC_LATENCY, PROP_METRIC_LATENCY_DEFAULT);
  this.k = MapUtils.getIntValue(properties, PROP_K, PROP_K_DEFAULT);
  this.cutoffFraction = MapUtils.getDoubleValue(properties, PROP_CUTOFF_FRACTION, PROP_CUTOFF_FRACTION_DEFAULT);

  if (properties.containsKey(PROP_INCLUDE_DIMENSIONS)) {
    this.includeDimensions = new HashSet<>((Collection<String>) properties.get(PROP_INCLUDE_DIMENSIONS));
  } else {
    this.includeDimensions = new HashSet<>();
  }

  if (properties.containsKey(PROP_EXCLUDE_DIMENSIONS)) {
    this.excludeDimensions = new HashSet<>((Collection<String>) properties.get(PROP_EXCLUDE_DIMENSIONS));
  } else {
    this.excludeDimensions = new HashSet<>();
  }
}
 

/**
 * Returns a DataFrame populated with mock data for a given config and time range.
 *
 * @param config metric generator config
 * @param start start time
 * @param end end time
 * @param interval time granularity
 * @return DataFrame with mock data
 */
private static DataFrame makeData(Map<String, Object> config, DateTime start, DateTime end, Period interval) {
  List<Long> timestamps = new ArrayList<>();
  List<Double> values = new ArrayList<>();

  double mean = MapUtils.getDoubleValue(config, "mean", 0);
  double std = MapUtils.getDoubleValue(config, "std", 1);
  double daily = MapUtils.getDoubleValue(config, "daily", mean);
  double weekly = MapUtils.getDoubleValue(config, "weekly", daily);
  NormalDistribution dist = new NormalDistribution(mean, std);

  DateTime origin = start.withFields(DataFrameUtils.makeOrigin(PeriodType.days()));
  while (origin.isBefore(end)) {
    if (origin.isBefore(start)) {
      origin = origin.plus(interval);
      continue;
    }

    timestamps.add(origin.getMillis());

    double compDaily = weekly * (COMPONENT_ALPHA_WEEKLY + Math.sin(origin.getDayOfWeek() / 7.0 * 2 * Math.PI + 1) / 2 * (1 - COMPONENT_ALPHA_WEEKLY));
    double compHourly = daily * (COMPONENT_ALPHA_DAILY + Math.sin(origin.getHourOfDay() / 24.0 * 2 * Math.PI + 1) / 2 * (1 - COMPONENT_ALPHA_DAILY));
    double compEpsilon = dist.sample();

    values.add((double) Math.max(Math.round(compDaily + compHourly + compEpsilon), 0));
    origin = origin.plus(interval);
  }

  return new DataFrame()
      .addSeries(COL_TIME, ArrayUtils.toPrimitive(timestamps.toArray(new Long[0])))
      .addSeries(COL_VALUE, ArrayUtils.toPrimitive(values.toArray(new Double[0])))
      .setIndex(COL_TIME);
}
 

public DimensionWrapper(DataProvider provider, DetectionConfigDTO config, long startTime, long endTime) {
  super(provider, config, startTime, endTime);

  // the metric used in dimension exploration
  this.metricUrn = MapUtils.getString(config.getProperties(), "metricUrn", null);

  this.minContribution = MapUtils.getDoubleValue(config.getProperties(), "minContribution", Double.NaN);
  this.minValue = MapUtils.getDoubleValue(config.getProperties(), "minValue", Double.NaN);
  this.minValueHourly = MapUtils.getDoubleValue(config.getProperties(), "minValueHourly", Double.NaN);
  this.maxValueHourly = MapUtils.getDoubleValue(config.getProperties(), "maxValueHourly", Double.NaN);
  this.minValueDaily = MapUtils.getDoubleValue(config.getProperties(), "minValueDaily", Double.NaN);
  this.maxValueDaily = MapUtils.getDoubleValue(config.getProperties(), "maxValueDaily", Double.NaN);
  this.k = MapUtils.getIntValue(config.getProperties(), "k", -1);
  this.dimensions = ConfigUtils.getList(config.getProperties().get("dimensions"));
  this.lookback = ConfigUtils.parsePeriod(MapUtils.getString(config.getProperties(), "lookback", "1w"));
  this.timezone = DateTimeZone.forID(MapUtils.getString(config.getProperties(), "timezone", "America/Los_Angeles"));

  /*
   * A bucket of the time series is taken into consider only if its value is above the minLiveZone. In other words,
   * if a bucket's value is smaller than minLiveZone, then this bucket is ignored when calculating the average value.
   * Used for outlier removal. Replace legacy average threshold filter.
   */
  this.minLiveZone = MapUtils.getDoubleValue(config.getProperties(), "minLiveZone", Double.NaN);
  this.liveBucketPercentageThreshold = MapUtils.getDoubleValue(config.getProperties(), "liveBucketPercentageThreshold", 0.5);

  // the metric to run the detection for
  this.nestedMetricUrns = ConfigUtils.getList(config.getProperties().get(PROP_NESTED_METRIC_URNS), Collections.singletonList(this.metricUrn));
  this.nestedMetricUrnKey = MapUtils.getString(config.getProperties(), PROP_NESTED_METRIC_URN_KEY, PROP_NESTED_METRIC_URN_KEY_DEFAULT);
  this.nestedProperties = ConfigUtils.getList(config.getProperties().get(PROP_NESTED));

  this.start = new DateTime(this.startTime, this.timezone);
  this.end = new DateTime(this.endTime, this.timezone);

  DateTime minStart = this.end.minus(this.lookback);
  if (minStart.isBefore(this.start)) {
    this.start = minStart;
  }

  this.evaluationMetricUrns = new HashSet<>();
}
 

public BaselineRuleFilterWrapper(DataProvider provider, DetectionConfigDTO config, long startTime, long endTime) {
  super(provider, config, startTime, endTime);
  int weeks = MapUtils.getIntValue(config.getProperties(), PROP_WEEKS, PROP_WEEKS_DEFAULT);
  DateTimeZone timezone =
      DateTimeZone.forID(MapUtils.getString(this.config.getProperties(), PROP_TIMEZONE, PROP_TIMEZONE_DEFAULT));
  this.baseline = BaselineAggregate.fromWeekOverWeek(BaselineAggregateType.MEDIAN, weeks, 1, timezone);
  // percentage change
  this.change = MapUtils.getDoubleValue(config.getProperties(), PROP_CHANGE, PROP_CHANGE_DEFAULT);
  // absolute change
  this.difference = MapUtils.getDoubleValue(config.getProperties(), PROP_DIFFERENCE, PROP_DIFFERENCE_DEFAULT);
  // site wide impact
  this.siteWideImpactThreshold = MapUtils.getDoubleValue(config.getProperties(), PROP_SITEWIDE_THRESHOLD, PROP_SITEWIDE_THRESHOLD_DEFAULT);
  this.siteWideMetricUrn = MapUtils.getString(config.getProperties(), PROP_SITEWIDE_METRIC);
}
 

public ThresholdAlgorithm(DataProvider provider, DetectionConfigDTO config, long startTime, long endTime) {
  super(provider, config, startTime, endTime);
  this.min = MapUtils.getDoubleValue(config.getProperties(), "min", Double.NaN);
  this.max = MapUtils.getDoubleValue(config.getProperties(), "max", Double.NaN);

  String metricUrn = MapUtils.getString(config.getProperties(), "metricUrn");
  MetricEntity me = MetricEntity.fromURN(metricUrn);
  this.slice = MetricSlice.from(me.getId(), this.startTime, this.endTime, me.getFilters());
}
 

/**
 * Alternate constructor for RCAFrameworkLoader
 *
 * @param outputName pipeline output name
 * @param inputNames input pipeline names
 * @param properties configuration properties ({@code PROP_COEFFICIENT}, {@code PROP_DIRECTION})
 */
public MetricDatasetPipeline(String outputName, Set<String> inputNames, Map<String, Object> properties) {
  super(outputName, inputNames);
  this.metricDAO = DAORegistry.getInstance().getMetricConfigDAO();
  this.datasetDAO = DAORegistry.getInstance().getDatasetConfigDAO();
  this.coefficient = MapUtils.getDoubleValue(properties, PROP_COEFFICIENT, PROP_COEFFICIENT_DEFAULT);
  this.direction = MappingDirection.valueOf(MapUtils.getString(properties, PROP_DIRECTION, PROP_DIRECTION_DEFAULT));
}
 

public ThresholdRuleFilterWrapper(DataProvider provider, DetectionConfigDTO config, long startTime, long endTime) {
  super(provider, config, startTime, endTime);
  this.min = MapUtils.getDoubleValue(config.getProperties(), PROP_MIN, PROP_MIN_DEFAULT);
  this.max = MapUtils.getDoubleValue(config.getProperties(), PROP_MAX, PROP_MAX_DEFAULT);
}
 

public MovingWindowAlgorithm(DataProvider provider, DetectionConfigDTO config, long startTime, long endTime) {
  super(provider, config, startTime, endTime);

  Preconditions.checkArgument(config.getProperties().containsKey(PROP_METRIC_URN));

  String metricUrn = MapUtils.getString(config.getProperties(), PROP_METRIC_URN);
  MetricEntity me = MetricEntity.fromURN(metricUrn);

  this.quantileMin = MapUtils.getDoubleValue(config.getProperties(), "quantileMin", Double.NaN);
  this.quantileMax = MapUtils.getDoubleValue(config.getProperties(), "quantileMax", Double.NaN);
  this.zscoreMin = MapUtils.getDoubleValue(config.getProperties(), "zscoreMin", Double.NaN);
  this.zscoreMax = MapUtils.getDoubleValue(config.getProperties(), "zscoreMax", Double.NaN);
  this.zscoreOutlier = MapUtils.getDoubleValue(config.getProperties(), "zscoreOutlier", Double.NaN);
  this.kernelSize = MapUtils.getIntValue(config.getProperties(), "kernelSize", 1);
  this.timezone = DateTimeZone.forID(MapUtils.getString(config.getProperties(), "timezone", "UTC"));
  this.windowSize = ConfigUtils.parsePeriod(MapUtils.getString(config.getProperties(), "windowSize", "1week"));
  this.lookbackPeriod = ConfigUtils.parsePeriod(MapUtils.getString(config.getProperties(), "lookbackPeriod", "1week"));
  this.reworkPeriod = ConfigUtils.parsePeriod(MapUtils.getString(config.getProperties(), "reworkPeriod", "1day"));
  this.changeDuration = ConfigUtils.parsePeriod(MapUtils.getString(config.getProperties(), "changeDuration", "5days"));
  this.changeFraction = MapUtils.getDoubleValue(config.getProperties(), "changeFraction", 0.666);
  this.baselineWeeks = MapUtils.getIntValue(config.getProperties(), "baselineWeeks", 0);
  this.applyLog = MapUtils.getBooleanValue(config.getProperties(), "applyLog", true);
  this.learningRate = MapUtils.getDoubleValue(config.getProperties(), "learningRate", 0.666);

  Preconditions.checkArgument(Double.isNaN(this.quantileMin) || (this.quantileMin >= 0 && this.quantileMin <= 1.0), "quantileMin must be between 0.0 and 1.0");
  Preconditions.checkArgument(Double.isNaN(this.quantileMax) || (this.quantileMax >= 0 && this.quantileMax <= 1.0), "quantileMax must be between 0.0 and 1.0");

  this.effectiveStartTime = new DateTime(startTime, this.timezone).minus(this.lookbackPeriod).getMillis();

  DateTime trainStart = new DateTime(this.effectiveStartTime, this.timezone).minus(this.windowSize);
  DateTime dataStart = trainStart.minus(new Period().withField(DurationFieldType.weeks(), baselineWeeks));
  DateTime detectionStart = new DateTime(startTime, this.timezone).minus(this.reworkPeriod);

  this.sliceData = MetricSlice.from(me.getId(), dataStart.getMillis(), endTime, me.getFilters());
  this.sliceDetection = MetricSlice.from(me.getId(), detectionStart.getMillis(), endTime, me.getFilters());

  AnomalySlice slice = new AnomalySlice().withStart(this.sliceData.getStart()).withEnd(this.sliceData.getEnd());
  if (this.config.getId() != null) {
    this.anomalySlice = slice.withDetectionId(this.config.getId());
  } else {
    this.anomalySlice = slice;
  }
}