Learn how to run powerful aggregations across your data to produce insights that are easy to understand and monitor.
count
count
visualization counts all matching events and produces a time series chart.
`count` overview
distinct
distinct
visualization counts each distinct occurrence of the distinct field inside the dataset and produce a time series chart.
field: any
is the field to aggregate.
`distinct` overview
avg
avg
visualization averages the values of the field inside the dataset and produces a time series chart.
field: number
is the number field to average.
`avg` overview
max
max
visualization finds the maximum value of the field inside the dataset and produces a time series chart.
field: number
is the number field where Axiom finds the maximum value.
max overview
min
min
visualization finds the minimum value of the field inside the dataset and produces a time series chart.
field: number
is the number field where Axiom finds the minimum value.
`min` overview
sum
sum
visualization adds all the values of the field inside the dataset and produces a time series chart.
field: number
is the number field where Axiom calculates the sum.
`sum` overview
percentiles
percentiles
visualization calculates the requested percentiles of the field in the dataset and produces a time series chart.
field: number
is the number field where Axiom calculates the percentiles.percentiles: number [, ...]
is a list of percentiles , each a float between 0 and 100. For example, percentiles(request_size, 95, 99, 99.9)
.`percentile` overview
histogram
histogram
visualization buckets the field into a distribution of N buckets, returning a time series heatmap chart.
field: number
is the number field where Axiom calculates the distribution.nBuckets
is the number of buckets to return. For example, histogram(request_size, 15)
.`histogram` overview
topk
topk
visualization calculates the top values for a field in a dataset.
field: number
is the number field where Axiom calculates the top values.nResults
is the number of top values to return. For example, topk(method, 10)
.`topk` overview
variance
variance
visualization calculates the variance of the field in the dataset and produces a time series chart.
The variance
aggregation returns the sample variance of the fields of the dataset.
field: number
is the number field where Axiom calculates the variance.
`variance` overview
stddev
stddev
visualization calculates the standard deviation of the field in the dataset and produces a time series chart.
The stddev
aggregation returns the sample standard deviation of the fields of the dataset.
field: number
is the number field where Axiom calculates the standard deviation.
`stddev` overview