public AnomalyDetectionJobManager(
Scheduler quartzScheduler,
AnomalyFunctionSpecDAO specDAO,
AnomalyFunctionRelationDAO relationDAO,
AnomalyResultDAO resultDAO,
SessionFactory sessionFactory,
MetricRegistry metricRegistry,
AnomalyFunctionFactory anomalyFunctionFactory,
FailureEmailConfiguration failureEmailConfig) {
this.queryCache = CACHE_REGISTRY_INSTANCE.getQueryCache();
timeSeriesHandler = new TimeSeriesHandler(queryCache);
timeSeriesResponseConverter = TimeSeriesResponseConverter.getInstance();
this.quartzScheduler = quartzScheduler;
this.specDAO = specDAO;
this.relationDAO = relationDAO;
this.resultDAO = resultDAO;
this.sessionFactory = sessionFactory;
this.metricRegistry = metricRegistry;
this.sync = new Object();
this.scheduledJobKeys = new HashMap<>();
this.anomalyFunctionFactory = anomalyFunctionFactory;
this.failureEmailConfig = failureEmailConfig;
}
private List<AnomalyResult> exploreCombination(TimeSeriesRequest request) throws Exception {
LOG.info("Exploring {}", request);
List<AnomalyResult> results = null;
// Query server
TimeSeriesResponse response;
try {
LOG.debug("Executing {}", request);
response = timeSeriesHandler.handle(request);
} catch (Exception e) {
throw new JobExecutionException(e);
}
Map<DimensionKey, MetricTimeSeries> res =
timeSeriesResponseConverter.toMap(response, collectionDimensions);
for (Map.Entry<DimensionKey, MetricTimeSeries> entry : res.entrySet()) {
if (entry.getValue().getTimeWindowSet().size() < 2) {
LOG.warn("Insufficient data for {} to run anomaly detection function", entry.getKey());
continue;
}
try {
// Run algorithm
DimensionKey dimensionKey = entry.getKey();
MetricTimeSeries metricTimeSeries = entry.getValue();
LOG.info(
"Analyzing anomaly function with dimensionKey: {}, windowStart: {}, windowEnd: {}",
dimensionKey,
windowStart,
windowEnd);
results =
anomalyFunction.analyze(
dimensionKey, metricTimeSeries, windowStart, windowEnd, knownAnomalies);
// Handle results
handleResults(results);
// Remove any known anomalies
results.removeAll(knownAnomalies);
LOG.info(
"{} has {} anomalies in window {} to {}",
entry.getKey(),
results.size(),
windowStart,
windowEnd);
anomalyCounter += results.size();
} catch (Exception e) {
LOG.error("Could not compute for {}", entry.getKey(), e);
}
}
return results;
}
public AnomalyDetectionTaskRunner() {
queryCache = CACHE_REGISTRY_INSTANCE.getQueryCache();
timeSeriesHandler = new TimeSeriesHandler(queryCache);
timeSeriesResponseConverter = TimeSeriesResponseConverter.getInstance();
}