private void CalculateTransformation(Messages.TransformSeries msg)
{
// Get the transform from the series
var transform = msg.Transforms.Dequeue();
// Calculate the rolling average and use it as the base noise level
string saveName = (transform.Parameters.ContainsKey(SAVE_NAME)) ? transform.Parameters[SAVE_NAME] :
SAVE_NAME_DEFAULT_VALUE;
// Construct the UPSERT msg so the values can be saved in the correct MetricStore
var um = new MetricStoreActor.UpsertMetric(saveName, msg.Measurements.Values);
// Find the correct MetricStore actor and send it the UPSERT msg
var actorName = "/user/*/MetricStore:" + msg.VmName + ":" + msg.VmDate;
var actor = Context.ActorSelection(actorName);
actor.Tell(um);
// Route the Metric unchanged to the next transform
var series = new Messages.TransformSeries(msg.Measurements, msg.Transforms, msg.GroupID, msg.ConnectionId, msg.VmName, msg.VmDate);
RouteTransform(series);
}
private void SendMetrics()
{
foreach (KeyValuePair <string, SortedDictionary <long, float> > entry in metrics)
{
// do something with entry.Value or entry.Key
var um = new MetricStoreActor.UpsertMetric(entry.Key, entry.Value);
metricStoreActor.Tell(um);
}
// Tell all the metric accumulators dispatchers that this actor is finishing
// / user / STARTUP_ACTOR / MetricAccumulatorDispatcher /
// var selection = Context.ActorSelection("/*/MetricAccumulatorDispatcher*");
var selection = Context.ActorSelection("/user/*/MetricAccumulatorDispatcher");
selection.Tell(new Messages.Stopping());
// Tell the associated MetricStoreActor that this actor is finishing
metricStoreActor.Tell(new Messages.Stopping());
Context.Stop(Context.Self);
}