Prometheus promql
From wikinotes
PromQL is prometheus's query language.
It's syntax is inspired by golang.
You can query prometheus from
- HTTP API
- UI table/graph view
Documentation
official docs https://prometheus.io/docs/prometheus/latest/querying/basics/ official examples https://prometheus.io/docs/prometheus/latest/querying/examples/ re2 (regex engine) https://github.com/google/re2/wiki/Syntax
Comments
# a comment
Datatypes
Strings
# string "foo" `foo` # string-literal 'foo\nbar'Floats
23 -2.43 3.4e-9 0x8f -Inf NaN
Metric-Selectors
Basics
The most basic query you can use is
your_metric_name
which queries all samples for that metric.
These metric selectors can be composed and filtered.{__name__="your_metric_name"} # query all (you can match multiple metrics this way) your_metric_name # query all your_metric_name[5min] # lump data into 5min clumps your_metric_name{job="foo",group="bar"} # filter by metric-labelsOperators
label metrics support various matchers/operators
= # equal != # not-equal =~ # regex match !~ # not regex matchClustering Metrics
TODO:
are these aggregates averages? sums? greatest-value?
your_metric_name[5min] # lump data into 5min clumpsUnits
ms # milliseconds s # seconds m # minutes h # hours d # days w # weeks y # yearsQuery Time Ranges
your_metric_name offset 5min # query 5min-ago until present your_metric_name @ 1609746000 # query at exactly '2021-01-04T07:40:00+00:00'
Queries
Basics
A simple query is simply a metric-selector with an optional filter
your_metric_name{job="foo"}SubQueries
You can combine functions and metrics.
From official examples:rate(http_requests_total[5m])[30m:1m]Metric Operators
You can do simple math using metrics.
There is some type-trickiness here, see docs for details.metric_start - metric_endmath
+ # add - # subtract * # multiplication / # division % # modulo ^ # exponentmetric_1 and metric_2 # only elements of metric_1 with exactly matching label-sets in metric_2 metric_1 or metric_2 # all elements of metric_1, and elements of metric_2 with non-matching labels metric_1 unless metric_2 # only elements of metric_1, where there are no matching label-sets in metric_2Metric Matching
Aggregates
sum(your_metric_name) # aggregate function sum without (duration) (your_metric_name) # excludes 'duration' labels from sum sum by (job, duration) (your_metric_name) # group sums by label 'job' and 'duration'# simple sum # sum elements min # smallest of elements max # largest of elements avg # average of elements count # num of elements count_values # num elements with same value # complex group stddev stdvar bottomk topk quantileFunctions
There are several builtin functions.