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[ENHANCEMENT] PromQL: use Kahan summation for sum() |
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test_test.go |
The PromQL test scripting language
This package contains two things:
- an implementation of a test scripting language for PromQL engines
- a predefined set of tests written in that scripting language
The predefined set of tests can be run against any PromQL engine implementation by calling promqltest.RunBuiltinTests()
.
Any other test script can be run with promqltest.RunTest()
.
The rest of this document explains the test scripting language.
Each test script is written in plain text.
Comments can be given by prefixing the comment with a #
, for example:
# This is a comment.
Each test file contains a series of commands. There are three kinds of commands:
load
clear
eval
Each command is executed in the order given in the file.
load
command
load
adds some data to the test environment.
The syntax is as follows:
load <interval>
<series> <points>
...
<series> <points>
<interval>
is the step between points (eg.1m
or30s
)<series>
is a Prometheus series name in the usualmetric{label="value"}
syntax<points>
is a specification of the points to add for that series, following the same expanding syntax as forpromtool unittest
documented here
For example:
load 1m
my_metric{env="prod"} 5 2+3x2 _ stale {{schema:1 sum:3 count:22 buckets:[5 10 7]}}
...will create a single series with labels my_metric{env="prod"}
, with the following points:
- t=0: value is 5
- t=1m: value is 2
- t=2m: value is 5
- t=3m: value is 7
- t=4m: no point
- t=5m: stale marker
- t=6m: native histogram with schema 1, sum -3, count 22 and bucket counts 5, 10 and 7
Each load
command is additive - it does not replace any data loaded in a previous load
command.
Use clear
to remove all loaded data.
clear
command
clear
removes all data previously loaded with load
commands.
eval
command
eval
runs a query against the test environment and asserts that the result is as expected.
Both instant and range queries are supported.
The syntax is as follows:
# Instant query
eval instant at <time> <query>
<series> <points>
...
<series> <points>
# Range query
eval range from <start> to <end> step <step> <query>
<series> <points>
...
<series> <points>
<time>
is the timestamp to evaluate the instant query at (eg.1m
)<start>
and<end>
specify the time range of the range query, and use the same syntax as<time>
<step>
is the step of the range query, and uses the same syntax as<time>
(eg.30s
)<series>
and<points>
specify the expected values, and follow the same syntax as forload
above
For example:
eval instant at 1m sum by (env) (my_metric)
{env="prod"} 5
{env="test"} 20
eval range from 0 to 3m step 1m sum by (env) (my_metric)
{env="prod"} 2 5 10 20
{env="test"} 10 20 30 45
Instant queries also support asserting that the series are returned in exactly the order specified: use eval_ordered instant ...
instead of eval instant ...
.
This is not supported for range queries.
It is also possible to test that queries fail: use eval_fail instant ...
or eval_fail range ...
.
eval_fail
optionally takes an expected error message string or regexp to assert that the error message is as expected.
For example:
# Assert that the query fails for any reason without asserting on the error message.
eval_fail instant at 1m ceil({__name__=~'testmetric1|testmetric2'})
# Assert that the query fails with exactly the provided error message string.
eval_fail instant at 1m ceil({__name__=~'testmetric1|testmetric2'})
expected_fail_message vector cannot contain metrics with the same labelset
# Assert that the query fails with an error message matching the regexp provided.
eval_fail instant at 1m ceil({__name__=~'testmetric1|testmetric2'})
expected_fail_regexp (vector cannot contain metrics .*|something else went wrong)