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quantize Metrics Operator

You can use the quantize operator to control the Sumo’s quantization behavior, which is described in detail in Metric Quantization. You can specify:

  • The size of the time buckets across which Sumo aggregates your metrics. If you do not specify a quantization interval, Sumo determines an optimum size for time buckets, as described in Automatic quantization at query time.  
  • The rollup type that Sumo uses to aggregate the individual data points in a time bucket, which can be one of avg, min, max, sum, or count. If you do not specify a rollup type in the quantize clause of your query, for each time bucket, Sumo presents the average of the data points in that bucket.  

quantize syntax

note

The quantize operator must appear immediatdly after your query selector, before any other operators.

metrics query | quantize to INTERVAL [using ROLLUP] [drop last]

where:

  • INTERVAL is the duration over which you want to quantize the metrics, in seconds (s) , minutes (m), hours (h), or days (d).
  • ROLLUP is  avg, min, max, sum, or count.
  • drop last causes the last time bucket to be dropped, if the end of that bucket is after the end of the query time range.
note

In the Metrics Explorer, you must switch to Advanced Mode to enter the drop last option.

quantize examples 

Set time bucket size

The quantize clause in this metric query sets the time bucket size to 5 minutes. Sumo will aggregate the metrics in each time bucket using the default rollup type, avg

_sourceCategory=hostmetrics | quantize to 5m

Set time bucket size and rollup type

The quantize clause in this metric query sets the time bucket size to 10 minutes, and specifies the sum rollup type. Sumo will sum the metric values in each 10 minute time bucket and return that value.

metric=CPU_User cluster=kafka | quantize to 10m using sum

Set time bucket size, rollup type, and drop last 

The quantize clause in this metric query sets the time bucket size to 10 minutes, and specifies the sum rollup type. Sumo will sum the metric values in each 10 minute time bucket and return that value. If the last time bucket ends after the end of the query time range, that bucket is dropped.

metric=CPU_User cluster=kafka | quantize to 10m using sum drop last
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