SignalFx Developers Guide

max()

Find the maximum value of the input stream.

Syntax

Aggregation

max([by=grp])

Table 1. Parameter definitions
Parameter Type Description

grp

string or list of strings. Default is None.

Optional: Names of properties to group by.

Transformation

max(over=duration [,cycle=type][,cycle_start=index][,shift_cycles=shift][,partial_values=partials_flag])

Table 2. Parameter definitions
Parameter Type Description

duration

Duration (number and duration units indicator)
Durations are specified as a number followed by a single character:

  • s: seconds

  • m: minutes

  • h: hours

  • d: days

The default is None.

Duration over which to get the maximum of the input stream. If you want a simple transformation, you need to use over=duration.

type

One of the following:

  • "quarter"

  • "month"

  • "week"

  • "day"

  • "hour"

Clock or calendar duration over which to get the maximum of the input stream.1

index

Optional: String or number, depending on the value of cycle. Default is None.

Index within cycle=type at which the transformation starts. The default is the first position within type. Format depends on the value of type.1
NOTE: You can’t specify cycle_start=index if you specify cycle="hour".

shift

Number. Default is 0.

Optional: Shifts the cycle window a number of cycles back from the current time and day. For example, cycle="hour" and shift_cycles=1 shifts the window to the previous hour.+ NOTE: If you specify shift_cycles=shift, partial_values must be False (the default).1

partials_flag

Boolean

Optional: If True, SignalFlow emits partial results during the time period of cycle; otherwise, SignalFlow only emits a result at the end of the cycle. Default is False.
NOTE: If you specify partial_values=True, you can’t use shift_cycles.1

1 To learn more about calendar window transformations, see Calendar window transformations.

All forms return a reference to the input stream object.

Examples

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#Aggregation - max by env
data('cpu.utilization').max(by='env')

#Aggregation - max by env and datacenter
data('cpu.utilization').max(by=['env', 'datacenter'])

#Transformation - 30 minute max
data('cpu.utilization').max(over='30m')

#Transformation - Max over last day, starting at 6:00 AM
#Emit values during the period
data('cpu.utilization').max(cycle="day", cycle_start="06h", partial_values=True)

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