prometheus/promql/testdata/at_modifier.test

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load 10s
metric{job="1"} 0+1x1000
metric{job="2"} 0+2x1000
load 1ms
metric_ms 0+1x10000
# Instant vector selectors.
eval instant at 10s metric @ 100
metric{job="1"} 10
metric{job="2"} 20
eval instant at 10s metric @ 100 offset 50s
metric{job="1"} 5
metric{job="2"} 10
eval instant at 10s metric offset 50s @ 100
metric{job="1"} 5
metric{job="2"} 10
eval instant at 10s -metric @ 100
{job="1"} -10
{job="2"} -20
eval instant at 10s ---metric @ 100
{job="1"} -10
{job="2"} -20
# Millisecond precision.
eval instant at 100s metric_ms @ 1.234
metric_ms 1234
# Range vector selectors.
eval instant at 25s sum_over_time(metric{job="1"}[100s] @ 100)
{job="1"} 55
eval instant at 25s sum_over_time(metric{job="1"}[100s] @ 100 offset 50s)
{job="1"} 15
eval instant at 25s sum_over_time(metric{job="1"}[100s] offset 50s @ 100)
{job="1"} 15
# Different timestamps.
eval instant at 25s metric{job="1"} @ 50 + metric{job="1"} @ 100
{job="1"} 15
eval instant at 25s rate(metric{job="1"}[100s] @ 100) + label_replace(rate(metric{job="2"}[123s] @ 200), "job", "1", "", "")
{job="1"} 0.3
eval instant at 25s sum_over_time(metric{job="1"}[100s] @ 100) + label_replace(sum_over_time(metric{job="2"}[100s] @ 100), "job", "1", "", "")
{job="1"} 165
# Subqueries.
# 10*(1+2+...+9) + 10.
eval instant at 25s sum_over_time(metric{job="1"}[100s:1s] @ 100)
{job="1"} 460
# 10*(1+2+...+7) + 8.
eval instant at 25s sum_over_time(metric{job="1"}[100s:1s] @ 100 offset 20s)
{job="1"} 288
# 10*(1+2+...+7) + 8.
eval instant at 25s sum_over_time(metric{job="1"}[100s:1s] offset 20s @ 100)
{job="1"} 288
# Subquery with different timestamps.
# Since vector selector has timestamp, the result value does not depend on the timestamp of subqueries.
# Inner most sum=1+2+...+10=55.
# With [100s:25s] subquery, it's 55*5.
eval instant at 100s sum_over_time(sum_over_time(metric{job="1"}[100s] @ 100)[100s:25s] @ 50)
{job="1"} 275
# Nested subqueries with different timestamps on both.
# Since vector selector has timestamp, the result value does not depend on the timestamp of subqueries.
# Sum of innermost subquery is 275 as above. The outer subquery repeats it 4 times.
eval instant at 0s sum_over_time(sum_over_time(sum_over_time(metric{job="1"}[100s] @ 100)[100s:25s] @ 50)[3s:1s] @ 3000)
{job="1"} 1100
# Testing the inner subquery timestamp since vector selector does not have @.
# Inner sum for subquery [100s:25s] @ 50 are
# at -50 nothing, at -25 nothing, at 0=0, at 25=2, at 50=4+5=9.
# This sum of 11 is repeated 4 times by outer subquery.
eval instant at 0s sum_over_time(sum_over_time(sum_over_time(metric{job="1"}[10s])[100s:25s] @ 50)[3s:1s] @ 200)
{job="1"} 44
# Inner sum for subquery [100s:25s] @ 200 are
# at 100=9+10, at 125=12, at 150=14+15, at 175=17, at 200=19+20.
# This sum of 116 is repeated 4 times by outer subquery.
eval instant at 0s sum_over_time(sum_over_time(sum_over_time(metric{job="1"}[10s])[100s:25s] @ 200)[3s:1s] @ 50)
{job="1"} 464
# Nested subqueries with timestamp only on outer subquery.
# Outer most subquery:
# at 900=783
# inner subquery: at 870=87+86+85, at 880=88+87+86, at 890=89+88+87
# at 925=537
# inner subquery: at 895=89+88, at 905=90+89, at 915=90+91
# at 950=828
# inner subquery: at 920=92+91+90, at 930=93+92+91, at 940=94+93+92
# at 975=567
# inner subquery: at 945=94+93, at 955=95+94, at 965=96+95
# at 1000=873
# inner subquery: at 970=97+96+95, at 980=98+97+96, at 990=99+98+97
eval instant at 0s sum_over_time(sum_over_time(sum_over_time(metric{job="1"}[20s])[20s:10s] offset 10s)[100s:25s] @ 1000)
{job="1"} 3588
# minute is counted on the value of the sample.
eval instant at 10s minute(metric @ 1500)
{job="1"} 2
{job="2"} 5
# timestamp() takes the time of the sample and not the evaluation time.
eval instant at 10m timestamp(metric{job="1"} @ 10)
{job="1"} 10
# The result of inner timestamp() will have the timestamp as the
# eval time, hence entire expression is not step invariant and depends on eval time.
eval instant at 10m timestamp(timestamp(metric{job="1"} @ 10))
{job="1"} 600
eval instant at 15m timestamp(timestamp(metric{job="1"} @ 10))
{job="1"} 900
# Time functions inside a subquery.
# minute is counted on the value of the sample.
eval instant at 0s sum_over_time(minute(metric @ 1500)[100s:10s])
{job="1"} 22
{job="2"} 55
# If nothing passed, minute() takes eval time.
# Here the eval time is determined by the subquery.
# [50m:1m] at 6000, i.e. 100m, is 50m to 100m.
# sum=50+51+52+...+59+0+1+2+...+40.
eval instant at 0s sum_over_time(minute()[50m:1m] @ 6000)
{} 1365
# sum=45+46+47+...+59+0+1+2+...+35.
eval instant at 0s sum_over_time(minute()[50m:1m] @ 6000 offset 5m)
{} 1410
# time() is the eval time which is determined by subquery here.
# 2900+2901+...+3000 = (3000*3001 - 2899*2900)/2.
eval instant at 0s sum_over_time(vector(time())[100s:1s] @ 3000)
{} 297950
# 2300+2301+...+2400 = (2400*2401 - 2299*2300)/2.
eval instant at 0s sum_over_time(vector(time())[100s:1s] @ 3000 offset 600s)
{} 237350
# timestamp() takes the time of the sample and not the evaluation time.
eval instant at 0s sum_over_time(timestamp(metric{job="1"} @ 10)[100s:10s] @ 3000)
{job="1"} 110
# The result of inner timestamp() will have the timestamp as the
# eval time, hence entire expression is not step invariant and depends on eval time.
# Here eval time is determined by the subquery.
eval instant at 0s sum_over_time(timestamp(timestamp(metric{job="1"} @ 999))[10s:1s] @ 10)
{job="1"} 55
clear