private MetricValueCollection OnCalculateValues(MetricSampleInterval interval, int intervals, DateTimeOffset startDateTime, DateTimeOffset endDateTime)
{
EnsureSorted();
MetricValueCollection newMetricValueCollection = new MetricValueCollection("Log Messages", "The number of log messages recorded per interval.", interval, intervals, "Messages");
//And prep for our process loop
DateTimeOffset windowStartDateTime = startDateTime;
DateTimeOffset windowEndDateTime = CalculateOffset(windowStartDateTime, interval, intervals);
//because we're doing a simple count by time interval, it's easiest to iterate
//through all of the intervals and then count the matches within.
int curSampleIndex = 0;
//roll through the samples to find our first sample index we care about so we can count from there.
for (curSampleIndex = 0; curSampleIndex < Count; curSampleIndex++)
{
if (this[curSampleIndex].Timestamp >= startDateTime)
{
//bingo! this is the first one we want
break;
}
}
while (windowEndDateTime <= endDateTime)
{
//count how many messages we go through to get to our target.
int curMessageCount = 0;
while (curSampleIndex < Count)
{
if (this[curSampleIndex].Timestamp >= windowEndDateTime)
{
//this is the first one in the next interval (or later), so don't count it and stop looping.
break;
}
else
{
//this bad boy is in our range, count it
curMessageCount++;
}
//and make damn sure we advance our index by one to not get into an infinite loop
curSampleIndex++;
}
//record off this interval
new MetricValue(newMetricValueCollection, windowStartDateTime, curMessageCount);
//and prep for the next loop
windowStartDateTime = windowEndDateTime;
windowEndDateTime = CalculateOffset(windowStartDateTime, interval, intervals);
}
return(newMetricValueCollection);
}
/// <summary>Create a new metric value for the specified metric value set.</summary>
/// <remarks>The new metric value is automatically added to the provided metric value set.</remarks>
/// <param name="metricValueCollection">The metric value set this value is part of.</param>
/// <param name="timeStamp">The unique date and time of this value sample.</param>
/// <param name="value">The calculated value.</param>
public MetricValue(MetricValueCollection metricValueCollection, DateTimeOffset timeStamp, double value)
{
m_MetricValueCollection = metricValueCollection;
m_TimeStamp = timeStamp;
m_Value = value;
//get the unique sequence number from the metric
m_Sequence = metricValueCollection.GetSampleSequence();
//and add ourself to the metric value set
m_MetricValueCollection.Add(this);
}
private MetricValueCollection OnCalculateValuesShortest(DateTimeOffset startDateTime, DateTimeOffset endDateTime, IEventMetricValueDefinition trendValue)
{
//there are two possibilities for unit caption: Either use the caption from the trend definition or, if that's null, we'll just do Count.
string unitCaption = null;
if (trendValue != null)
{
unitCaption = trendValue.UnitCaption;
}
if (string.IsNullOrEmpty(unitCaption))
{
unitCaption = "Events";
}
MetricValueCollection newMetricValueCollection;
if (trendValue == null)
{
//initialize with our metric object for default caption/description behavior
newMetricValueCollection = new MetricValueCollection(this, MetricSampleInterval.Shortest, 0, unitCaption);
}
else
{
//initialize with our trend for trend-specific captions and descriptions
newMetricValueCollection = new MetricValueCollection((EventMetricValueDefinition)trendValue, MetricSampleInterval.Shortest, 0, unitCaption);
}
double lastValue = 0.0;
//First, we need to find the value for the start date & time and the sample index into the collection.
for (int curSampleIndex = 0; curSampleIndex < Samples.Count; curSampleIndex++)
{
//get the sample on deck
EventMetricSample curSample = Samples[curSampleIndex];
//Is this sample in our range?
if (curSample.Timestamp >= startDateTime)
{
//Go ahead and calculate the value, adding it to our set. We don't use a baseline because we're looking at each individual value.
CalculateSample(newMetricValueCollection, new List <EventMetricSample>(new[] { curSample }), lastValue, curSampleIndex, curSample.Timestamp, (EventMetricValueDefinition)trendValue);
}
else if (curSample.Timestamp > endDateTime)
{
//we're done - there are no more samples to consider, break out of the for loop
break;
}
}
return(newMetricValueCollection);
}
/// <summary>
/// Calculate one effective value from the provided objects
/// </summary>
/// <param name="metricValueCollection">The value set to add the new value to</param>
/// <param name="baselineSample">The baseline to calculate from. Only used (and required) for metrics that require multiple samples.</param>
/// <param name="valueSample">The value sample to perform the calculation with.</param>
/// <param name="timeStampOverride">An optional override timestamp</param>
private static double CalculateSample(MetricValueCollection metricValueCollection, SampledMetricSample baselineSample, SampledMetricSample valueSample, DateTimeOffset?timeStampOverride)
{
double calculatedValue;
if (valueSample.RequiresMultipleSamples == false)
{
calculatedValue = valueSample.ComputeValue(); //we just need one
}
else
{
calculatedValue = valueSample.ComputeValue(baselineSample);
}
DateTimeOffset timeStamp = ((timeStampOverride == null) ? valueSample.Timestamp : (DateTimeOffset)timeStampOverride);
//now create & add the value to our values collection.
new MetricValue(metricValueCollection, timeStamp, calculatedValue);
return(calculatedValue);
}
private MetricValueCollection OnCalculateValuesInterval(MetricSampleInterval interval, int intervals, DateTimeOffset startDateTime, DateTimeOffset endDateTime, IEventMetricValueDefinition trendValue)
{
//there are two possibilities for unit caption: Either use the caption from the trend definition or, if that's null, we'll just do Count.
string unitCaption = null;
if (trendValue != null)
{
unitCaption = trendValue.UnitCaption;
}
if (string.IsNullOrEmpty(unitCaption))
{
unitCaption = "Events";
}
MetricValueCollection newMetricValueCollection;
if (trendValue == null)
{
//initialize with our metric object for default caption/description behavior
newMetricValueCollection = new MetricValueCollection(this, interval, intervals, unitCaption);
}
else
{
//initialize with our trend for trend-specific captions and descriptions
newMetricValueCollection = new MetricValueCollection((EventMetricValueDefinition)trendValue, interval, intervals, unitCaption);
}
//And prep for our process loop
DateTimeOffset windowStartDateTime = startDateTime;
DateTimeOffset windowEndDateTime = CalculateOffset(windowStartDateTime, interval, intervals);
double lastValue = 0.0;
//now loop through all of the intervals in the range to create the sample ranges.
int lastUsedSampleIndex = 0;
while (windowStartDateTime < endDateTime)
{
//find all of the samples in the current range...
List <EventMetricSample> samples = new List <EventMetricSample>();
for (int curSampleIndex = lastUsedSampleIndex; curSampleIndex < Samples.Count; curSampleIndex++)
{
//get the sample on deck
EventMetricSample curSample = Samples[curSampleIndex];
//if we're outside of the window (before or after) then break out because we've found this whole bucket.
if ((curSample.Timestamp < windowStartDateTime) || (curSample.Timestamp > windowEndDateTime))
{
//we'll need to look at this sample in the next window to see if it fits.
lastUsedSampleIndex = curSampleIndex;
break;
}
//this sample is in the bucket
samples.Add(curSample);
}
//add a metric value for this bucket now that we know everything in it.
lastValue = CalculateSample(newMetricValueCollection, samples, lastValue, lastUsedSampleIndex, windowEndDateTime, (EventMetricValueDefinition)trendValue);
//and now we have recorded a metric value for the requested date & time if possible, move that forward.
windowStartDateTime = windowEndDateTime; //we're moving on to the next window
windowEndDateTime = CalculateOffset(windowEndDateTime, interval, intervals);
//if the target is beyond our end date & time, set to the end date and time so we calculate our last sample
if (windowEndDateTime > endDateTime)
{
windowEndDateTime = endDateTime;
}
}
return(newMetricValueCollection);
}
/// <summary>
/// Calculate one effective value from the provided objects
/// </summary>
/// <param name="metricValueCollection">Optional. The value set to add the new value to</param>
/// <param name="samples">The set of samples to put in this value</param>
/// <param name="previousValue">The value of the prior sample in time.</param>
/// <param name="previousCount">The number of event metric samples previously used (for running average)</param>
/// <param name="timeStamp">The timestamp to use for the sample</param>
/// <param name="trendValue">The specific event metric value to trend</param>
internal double CalculateSample(MetricValueCollection metricValueCollection, IList <EventMetricSample> samples, double previousValue, int previousCount, DateTimeOffset timeStamp, EventMetricValueDefinition trendValue)
{
double calculatedValue;
//There are three totally different routes we go: Either we are calculating an explicit trend value,
//or we are just going to count the # of events. This varies depending on whether the caller specified
//a trend value
if (trendValue == null)
{
//just count them
calculatedValue = samples.Count;
}
//There are two overall ways we trend things: Either we count the # of non-null values for non-trendables, or
//we actually make a numeric trend
else if ((trendValue.IsTrendable == false) || (trendValue.DefaultTrend == EventMetricValueTrend.Count))
{
//count the number of things.
int itemCount = 0;
if (samples.Count > 0)
{
int valueIndex = Definition.Values.IndexOf(trendValue); //the zero-based index in the value collection of the value we want
//Now count all of the samples with a non-null value, including us (inclusive)
foreach (EventMetricSample sample in samples)
{
if (sample.Values[valueIndex] != null)
{
itemCount++;
}
}
}
calculatedValue = itemCount;
}
else
{
//ohh kay, now we either sum or average.
double sumValue = 0; //sum or average, we need the sum.
int items = samples.Count; //for an average we will need the item count.
int valueIndex = Definition.Values.IndexOf(trendValue); //the zero-based index in the value collection of the value we want
//if it's a running value we need to start with the previous sample's state
if ((trendValue.DefaultTrend == EventMetricValueTrend.RunningAverage) ||
(trendValue.DefaultTrend == EventMetricValueTrend.RunningSum))
{
//we need the previous running data.
sumValue = previousValue;
items += previousCount;
}
//Now add up the effective value of the requested trend line for every sample in the range, inclusive
foreach (EventMetricSample currentSample in samples)
{
sumValue += currentSample.GetEffectiveValue(valueIndex);
}
//figure out the calculated value. For performance and safety, don't do a divide we don't have to
if ((items > 1) &&
((trendValue.DefaultTrend == EventMetricValueTrend.Average) ||
(trendValue.DefaultTrend == EventMetricValueTrend.RunningAverage)))
{
calculatedValue = sumValue / items;
}
else
{
calculatedValue = sumValue;
}
}
//now create & add the value to our values collection.
if (metricValueCollection != null)
{
new MetricValue(metricValueCollection, timeStamp, calculatedValue);
}
return(calculatedValue);
}
/// <summary>
/// Calculate the value set for the provided date range inclusive with samples exactly on the provided interval.
/// </summary>
/// <remarks></remarks>
/// <param name="interval">The interval to bias to.</param>
/// <param name="intervals">The number of intervals to have between each value exactly.</param>
/// <param name="startDateTime">The exact date and time desired to start the value set.</param>
/// <param name="endDateTime">The exact end date and time to not exceed.</param>
/// <returns>A new metric value set with all calculated values.</returns>
private MetricValueCollection OnCalculateValuesOnInterval(MetricSampleInterval interval, int intervals, DateTimeOffset startDateTime, DateTimeOffset endDateTime)
{
MetricValueCollection newMetricValueCollection = new MetricValueCollection(this, interval, intervals, Definition.UnitCaption);
//based on the requested interval, calculate the delta between each sample and the tolerance (how close we have to be
//to the requested time to be pulled forward in time as the best sample)
TimeSpan sampleTolerance = CalculateOffsetTolerance(interval);
DateTimeOffset targetDateTime = startDateTime;
DateTimeOffset targetToleranceDateTime = targetDateTime + sampleTolerance;
SampledMetricSample baselineSample = null;
double previousMetricValue = 0;
int firstSampleIndex = 0;
//First, we need to find the value for the start date & time and the sample index into the collection.
for (int curSampleIndex = 0; curSampleIndex < base.Samples.Count; curSampleIndex++)
{
SampledMetricSample curSample = (SampledMetricSample)Samples[curSampleIndex];
//is this the sample that exactly covers our target date & time? It is if it's equal to our target, or
//it is a more exact fit than the next sample.
if ((curSample.Timestamp == targetDateTime) ||
((curSample.Timestamp < targetToleranceDateTime) && (Samples[curSampleIndex + 1].Timestamp > targetToleranceDateTime)))
{
//yes, this sample is the best fit for our start date & time. The next one is after our "pull forward" tolerance.
//but to get a value, we may have to back up one more interval from this sample to establish its value
if (curSample.RequiresMultipleSamples)
{
//back up as much as we can - as close to one full interval as possible so we get the most accurate initial value sample
DateTimeOffset baselineTargetDateTime = CalculateOffset(targetDateTime, interval, -intervals);
//start with the first sample before us... if there is one.
for (int baselineSampleIndex = curSampleIndex - 1; baselineSampleIndex >= 0; baselineSampleIndex--)
{
//keep walking back until we are before our target (or run out of choices)
baselineSample = (SampledMetricSample)Samples[curSampleIndex];
if (baselineSample.Timestamp <= baselineTargetDateTime)
{
//this is our best fit - it's the first that covers our baseline date time.
break;
}
}
}
//we either got our baseline or we didn't - if we didn't and we need it we can't calculate value.
if ((baselineSample != null) || (curSample.RequiresMultipleSamples == false))
{
//Calculate the initial metric value sample and add it to the collection.
previousMetricValue =
CalculateSample(newMetricValueCollection, baselineSample, curSample, startDateTime);
}
//and this sample becomes our baseline into the next routine
baselineSample = curSample;
firstSampleIndex = curSampleIndex;
break; //and we're done - we only wanted to get the start value.
}
}
//Now that we've found our first sample, and the offset into the collection for the first sample, we can go on (provide there are more samples)
firstSampleIndex++; //because we used the current sample in the for loop above.
if (firstSampleIndex < (Samples.Count - 1))
{
//we now want to look for the first sample after the start date. If the user was silly and requested an end date that is less
//than one interval from the start date, we'll never get into our while loop this way.
targetDateTime = CalculateOffset(targetDateTime, interval, intervals);
targetToleranceDateTime = targetDateTime + sampleTolerance;
int curSampleIndex = firstSampleIndex; //we start with the first sample after what was used above.
SampledMetricSample curSample = null;
//keep looping until we fill up the timespan or run out of samples.
while ((targetDateTime <= endDateTime) && (curSampleIndex < (Samples.Count - 1)))
{
//if we have no sample on deck, we must have used it in the last pass of the loop (or this is the first pass)
//so get it now.
if (curSample == null)
{
curSample = (SampledMetricSample)Samples[curSampleIndex];
}
//is this the sample that exactly covers our target date & time? It is if it's equal to our target, or
//it is a more exact fit than the next sample.
if ((curSample.Timestamp == targetDateTime) ||
((curSample.Timestamp < targetToleranceDateTime) && (Samples[curSampleIndex + 1].Timestamp > targetToleranceDateTime)))
{
//yes, this sample is the best fit for our start date & time. The next one is after our "pull forward" tolerance.
if ((baselineSample != null) || (curSample.RequiresMultipleSamples == false))
{
//Calculate the next metric value sample and add it to the collection.
previousMetricValue =
CalculateSample(newMetricValueCollection, baselineSample, curSample, targetDateTime);
}
//and this sample becomes our baseline into the next round
baselineSample = curSample;
//and we need a new current sample.
curSample = null;
curSampleIndex++;
//and now we have recorded a metric value for the requested date & time if possible, move that forward.
targetDateTime = CalculateOffset(targetDateTime, interval, intervals);
targetToleranceDateTime = targetDateTime + sampleTolerance;
}
else if (curSample.Timestamp < targetToleranceDateTime)
{
//this sample AND the next sample are both before target tolerance - we're going to skip this guy and record nothing
//(because we have more samples than we need for the interval we want)
curSample = null;
curSampleIndex++;
}
else
{
//the sample on deck doesn't apply yet - it's in the future. We need to "invent" a sample for the current date and time.
//we'll just re-record the last metric value
new MetricValue(newMetricValueCollection, targetDateTime, previousMetricValue);
//and now we have definitely recorded a metric value for the requested date & time, move that forward.
targetDateTime = CalculateOffset(targetDateTime, interval, intervals);
targetToleranceDateTime = targetDateTime + sampleTolerance;
}
}
}
return(newMetricValueCollection);
}
/// <summary>
/// Calculate a value set for the provided date range inclusive using all of the sample data, even if
/// that produces irregular sample intervals.
/// </summary>
/// <param name="startDateTime">The exact date and time desired to start the value set.</param>
/// <param name="endDateTime">The exact end date and time to not exceed.</param>
/// <returns>A new metric value set with all calculated values.</returns>
private MetricValueCollection OnCalculateValuesShortest(DateTimeOffset startDateTime, DateTimeOffset endDateTime)
{
MetricValueCollection newMetricValueCollection = new MetricValueCollection(this, MetricSampleInterval.Shortest, 0, Definition.UnitCaption);
//ohhhhkay, now we need to figure out what samples we want to include and not include.
//we want to start by getting the sample one interval before the user wants to have values for so we can have a value exactly
//on that starting point
SampledMetricSample baselineSample = null;
SampledMetricSample previousBaselineSample = null;
foreach (SampledMetricSample curSample in base.Samples)
{
//is this sample in our range?
if (curSample.Timestamp < startDateTime)
{
//It isn't, but there are still reasons we'd be interested in it.
//because the next one could be in the range and we'll want to mess with this one.
previousBaselineSample = baselineSample;
baselineSample = curSample;
}
else if (curSample.Timestamp > endDateTime)
{
//no, BUT if it's the first sample after our range, and we didn't end EXACTLY
//on the range then we want to include it, but we'll short it back to the end of the timeframe.
if ((baselineSample != null) && (baselineSample.Timestamp < endDateTime))
{
CalculateSample(newMetricValueCollection, baselineSample, curSample, endDateTime);
}
//and no matter what, we're done. Either we got a special "Bracket" sample, or there isn't one.
break;
}
else
{
//the sample is in the range - neither after nor before. We definitely use this sample.
//but before we do this, is this the FIRST one in the range?
if ((baselineSample != null) && (baselineSample.Timestamp < startDateTime))
{
//yes it is - the baseline is before our start date, and we're after or equal.
//If it's not only the last before we get in but ALSO the first one in isn't EXACTLY on the line, we need to
//create a fake interim sample, based on this guy and the one BEFORE him.
if (curSample.Timestamp > startDateTime)
{
//we have to insert a fake sample based on the baseline and the guy that came before him.
//but guard against us not having enough previous information to do this (this will happen more often than not)
if ((previousBaselineSample != null) || (baselineSample.RequiresMultipleSamples == false))
{
CalculateSample(newMetricValueCollection, previousBaselineSample, baselineSample, startDateTime);
}
}
}
//calculate our sample, however we have to guard against there being no baseline
// (because we're the first sample of a metric that requires multiple samples)
if ((baselineSample != null) || (curSample.RequiresMultipleSamples == false))
{
CalculateSample(newMetricValueCollection, baselineSample, curSample, null);
}
//and this sample becomes the new baseline
baselineSample = curSample;
}
}
return(newMetricValueCollection);
}
