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max

Max aggregation operator. There are two variants of the :max operator.

Aggregation

Input Stack:
query: Query
Output Stack:
AggregationFunction

Select the maximum value for corresponding times across all matching time series.

Parameters

  • query: A query expression that selects the time series to aggregate

Examples

Find the maximum CPU usage across all matching nodes:

name,ssCpuUser,:eq,
:max

When matching against the sample data in the table below, the highlighted time series would be included in the aggregate result:

Namenf.appnf.nodeData
ssCpuUser alerttest i-0123 [1.0, 2.0, NaN]
ssCpuSystem alerttest i-0123 [3.0, 4.0, 5.0]
ssCpuUser nccp i-0abc [8.0, 7.0, 6.0]
ssCpuSystem nccp i-0abc [6.0, 7.0, 8.0]
numRequests nccp i-0abc [1.0, 2.0, 4.0]
ssCpuUser api i-0456 [1.0, 2.0, 2.0]

The values from the corresponding intervals will be aggregated. For the first interval using the sample data above the values are 1.0, 8.0, and 1.0. The maximum of these non-NaN values is selected. This leads to a final result of:

NameData
ssCpuUser [8.0, 7.0, 6.0]

The only tags for the aggregated result are those that are matched exactly (:eq clause) as part of the choosing criteria or are included in a group by.

Math

Input Stack:
expr: TimeSeriesExpr
Output Stack:
TimeSeriesExpr

Select the maximum value for corresponding times across the time series resulting from the input expression. This variant is typically used when you need to apply a different aggregation function for grouping first, then find the maximum across the groups.

Parameters

  • expr: A time series expression that may contain multiple series to find the maximum across

Examples

First group by cluster using sum aggregation, then find the maximum across all groups:

BeforeAfter
name,sps,:eq,
:sum,
(,nf.cluster,),:by
name,sps,:eq,
:sum,
(,nf.cluster,),:by,
:max
  • :min - Minimum aggregation function
  • :sum - Sum aggregation function
  • :avg - Average aggregation function
  • :count - Count aggregation function
  • :by - Group time series by tag values before aggregating