rollup

Type of operation: Aggregate, Metrics

Description

Rollup raw metrics into aligned metrics

Usage

rollup [ options ], metric ...

Argument

Type

Required

Multiple

options

options

Optional

Only one

metric

expression

Required

Can be multiple

Options

Option

Type

Meaning

resolution

duration

How large each rolled-up bucket is (e g 5m)

buckets

int64

Approximately how many buckets to divide the query window into (not accelerable)

empty_bins

bool

deprecated

Accelerable

rollup is sometimes accelerable, depending on options used. A dataset that only uses accelerable verbs, can be accelerated, making queries on the dataset respond faster.

Examples

rollup options(resolution:300s), requests:metric("requests_total")

Generates a column named “requests” holding “requests_total” metric and align them with 300s time bins.

rollup options(buckets:2000), failed_requests:metric("requests_total")

Generates a column named “failed_requests” holding “requests_total” metric and align them with 2000 uniform time bins in the query window.

rollup options(resolution:300s), failed_requests:metric("requests_total", filter:status_code >= 400 and status_code <= 599)

Generates a column named “failed_requests” holding “requests_total” metric where status_code is in [400, 599], and align them with 300s time bins.

rollup options(resolution:300s), failed_requests:metric("requests_total", type:cumulativeCounter, rollup:avg, aggregate:sum)

Generates a column named “failed_requests” holding “requests_total” metric and align them with 300s time bins with the provided method.