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84 vFoglight

Web Component Guide

to weight the average, the host that was sampled more frequently would skew the

result.

• For a sum aggregation, it aggregates the average property of the metric values,

and stores it back into the sum property in the aggregated MetricValue.

• The only situation in which each history object within the Metric is not

aggregated is if the timeRange used for the Query uses RAW granularity, which

means that each observation from the agent gets its own history row. In this case,

the history lists from the various metrics being aggregated do not match up (in

number, or in date/times), so there is no way they could be aggregated.

• The most likely properties that you will be interested in, when doing aggregations

on Metric properties, are as follows:

• For a max aggregation, the period/max under the Metric, which gives the

maximum value for the whole timeRange.

•For a min aggregation, the period/min under the Metric, which gives the

minimum value for the whole timeRange.

• For an average aggregation, the period/average under the Metric, which gives

the average value for the whole timeRange.

• For a sum aggregation, the current/sum under the Metric, which gives the sum

of the values on the most current observations.

Note You are not limited to using these values if something else is desired.

Removing an Aggregation

To remove an aggregation:

• Click the button at the right side of the aggregation type.

Identifying Values

The expected use case for Identifying Values is as a label for a query that returns an

aggregated result.

Within each aggregation (except for ones using the operation count), you can also create

Identifying Values for the object returned by the query. This is a way to assign fixed

string values to other properties within the data object that is created as the result of

choosing an aggregation. For instance, if you created an aggregation of events to get

their maximum severity, you might add Identifying Values that returns just the Name

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