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Empty result when step is larger than 300s #705

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arkbriar opened this issue Jan 14, 2025 · 10 comments
Open

Empty result when step is larger than 300s #705

arkbriar opened this issue Jan 14, 2025 · 10 comments

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@arkbriar
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arkbriar commented Jan 14, 2025

Seems the commit is missing from the forked prometheus
prometheus/prometheus#9946. Therefore, there's a high chance no data can be popped when a step is larger than 300s (which is the default look back delta).

An example:

  • Query params: start=1736607436000, end=1736780236000, step=1800s
  • Two backends (both VM)
  • Result below (both same)
value="{} =>\n0.03333333333333333 @[1736762400]\n0 @[1736764200]\n0 @[1736766000]\n0 @[1736767800]\n0 @[1736769600]\n0.03333333333333333 @[1736771400]\n0 @[1736773200]\n0 @[1736775000]\n0 @[1736776800]\n0.03333333333333333 @[1736778600]"

The overall result from the query engine was empty. I traced through the code and found data was jumped because of this, where the delta is the default value 300000.

A workaround to this is to align the start and end to step, which Grafana does. And the fact that Grafana always works while my program doesn't confused me a long time until I captured the HTTP request :(

@rishabhkumar92
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rishabhkumar92 commented Feb 1, 2025

@arkbriar I am working on upgrading promxy to implement native histogram ([change],(#696) discussion) and this is based on latest prometheus (post nov 2024)

I am facing the same issue but with very high step functions (like 3h). do find any resolution around this?

@arkbriar
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arkbriar commented Feb 3, 2025

I am facing the same issue but with very high step functions (like 3h).

@rishabhkumar92 It was the same on my side. High steps are much easier for reproducing the issue, though I was able to reproduce with my tiny query with step of 500s.

do find any resolution around this?

Solution, no. I found only a workaround which I posted in the description.

A workaround to this is to align the start and end to step, which Grafana does. And the fact that Grafana always works while my program doesn't confused me a long time until I captured the HTTP request :(

@rishabhkumar92
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rishabhkumar92 commented Feb 3, 2025

Solution, no. I found only a workaround which I posted in #705 (comment).

@arkbriar There were 2 key things mentioned above:

did you find any workaround for the second case?

@arkbriar
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arkbriar commented Feb 3, 2025

Other is around the jump which is in the current master too but not sure if there is any bug in this logic.

This is the trigger of the exact issue here: the delta isn't set correctly. The code is included in the current promxy's Prometheus version as well. You could maybe debug it and see if the delta is set to step?

@rishabhkumar92
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@arkbriar i validated that delta was indeed set correctly but problem was due to max lookback limit.

@arkbriar
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arkbriar commented Feb 5, 2025

@arkbriar i validated that delta was indeed set correctly but problem was due to max lookback limit.

Sorry, I'm a bit confused. How the jump happens when delta is set correctly?

	t0 := t - b.delta

	if b.valueType != chunkenc.ValNone && t0 > b.lastTime {

@jacksontj
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I think I'm actually a bit lost on this error report. The subject seems to indicate that there are empty results with a large step (>300s); but I am able to get data with a 5000s step spread over the course of a day (equivalent upstream query Upstream 5000s
).

There is also some mention of time alignment with grafana; which I played around with the start/end times but seemingly can't get it to return an empty dataset either. Is it possible to create a repro case using some public datasource? If not, could we attach some trace log output (which would include the query and data)?

@arkbriar
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arkbriar commented Feb 7, 2025

I think I'm actually a bit lost on this error report. The subject seems to indicate that there are empty results with a large step (>300s); but I am able to get data with a 5000s step spread over the course of a day (equivalent upstream query Upstream 5000s ).

There is also some mention of time alignment with grafana; which I played around with the start/end times but seemingly can't get it to return an empty dataset either. Is it possible to create a repro case using some public datasource? If not, could we attach some trace log output (which would include the query and data)?

Sorry for the confusion... I'm pretty sure I can reproduce it with my VM setup since I scripted the MRE. Let me have a try with the open data source.

@arkbriar
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arkbriar commented Feb 10, 2025

There is also some mention of time alignment with grafana; which I played around with the start/end times but seemingly can't get it to return an empty dataset either. Is it possible to create a repro case using some public datasource? If not, could we attach some trace log output (which would include the query and data)?

I found I couldn't reproduce with the open datasource simply because it's a Proemtheus, which returns a result of aligned timestamps starting from the query's start so it avoids the problem. The branch will be correctly skipped if refTime == t, where refTime is the timestamp that promxy uses to read values from the pulled time series, and t is the first point that is larger or equal to refTime. When query start and the timestamp of the first point aligns with the step, which I mean (t_query_start - t_first_point) % step == 0, the branch is always skipped and a result will be popped.

However, in the case I was and am able to reproduce, timestamps don't align. FYI, the following is the line from the trace log with all the values.

value="{} =>\n0.03333333333333333 @[1736762400]\n0 @[1736764200]\n0 @[1736766000]\n0 @[1736767800]\n0 @[1736769600]\n0.03333333333333333 @[1736771400]\n0 @[1736773200]\n0 @[1736775000]\n0 @[1736776800]\n0.03333333333333333 @[1736778600]"

The query start is 1736607436000 in milliseconds. Thus, (1736762400000 - 1736607436000) % 1800000 = 164000 means the branch will always be entered. And since the delta in the iterator is set to 300s, the PeekPrev always fails because the prevTime is always -Inf (code).

I think this is a VictoriaMetrics specific problem. Let me see if there's an open VM datasource.

@arkbriar
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Reproduced with the public VM playground.

promxy:
  server_groups:
    - static_configs:
        - targets: ["play.victoriametrics.com"]
      path_prefix: /select/0/prometheus
      scheme: https
      http_client:
        dial_timeout: 1s
        tls_config:
          insecure_skip_verify: true
  • query: rate(container_cpu_usage_seconds_total{container="alertmanager"}[30s])
  • query options:
    • start: 1w-ago (2025-02-04 05:46:38)
    • end: now (2025-02-11 05:46:38)
    • step: 1800s

Result from VM playground:

Image

Result from promxy: empty.

Image

Trace logs:

time="2025-02-11T13:48:53+08:00" level=debug msg="call rate(container_cpu_usage_seconds_total{container=\"alertmanager\"}[30s]) vector"
time="2025-02-11T13:48:53+08:00" level=debug msg="https://play.victoriametrics.com/select/0/prometheus" api=QueryRange query="rate(container_cpu_usage_seconds_total{container=\"alertmanager\"}[30s])" r="{2025-02-04 05:46:38 +0000 UTC 2025-02-11 05:46:38 +0000 UTC 30m0s}"
time="2025-02-11T13:48:53+08:00" level=trace msg="https://play.victoriametrics.com/select/0/prometheus" api=QueryRange error="<nil>" query="rate(container_cpu_usage_seconds_total{container=\"alertmanager\"}[30s])" r="{2025-02-04 05:46:38 +0000 UTC 2025-02-11 05:46:38 +0000 UTC 30m0s}" took=262.854375ms value="{cluster=\"sandbox\", container=\"alertmanager\", cpu=\"total\", id=\"/kubepods.slice/kubepods-besteffort.slice/kubepods-besteffort-pod1a637df7_1189_4db0_b1ea_68ba064c3e6d.slice/cri-containerd-6abb2902881645f6761eacbbd596e7e769bfcef6a9be4bbab801b3ad97df976e.scope\", image=\"docker.io/prom/alertmanager:v0.24.0\", instance=\"gke-sandbox-e2-standard-4-20250202084-5e775834-b6rz\", job=\"kubelet\", metrics_path=\"/metrics/cadvisor\", name=\"6abb2902881645f6761eacbbd596e7e769bfcef6a9be4bbab801b3ad97df976e\", namespace=\"prometheus-benchmark\", node=\"gke-sandbox-e2-standard-4-20250202084-5e775834-b6rz\", pod=\"prometheus-benchmark-prometheus-benchmark-vmalert-stable-5l2h5t\", prometheus=\"monitoring/monitoring-vmagent\"} =>\n0.032679016666666644 @[1739187000]\n0.02555798333333333 @[1739188800]\n0.025182733333333356 @[1739190600]\n0.021065550000000145 @[1739192400]\n0.020392950000000097 @[1739194200]\n0.027317916666666994 @[1739196000]\n0.019990966666666547 @[1739197800]\n0.022974849999999946 @[1739199600]\n0.022974183333333068 @[1739201400]\n0.02111256666666653 @[1739203200]\n0.02158591666666704 @[1739205000]\n0.022505533333333005 @[1739206800]\n0.022857716666665813 @[1739208600]\n0.026286433333333057 @[1739210400]\n0.02156463333333439 @[1739212200]\n0.023501683333332343 @[1739214000]\n0.023267716666667108 @[1739215800]\n0.01975614999999872 @[1739217600]\n0.023563983333332317 @[1739219400]\n0.023464083333332535 @[1739221200]\n0.02340859999999907 @[1739223000]\n0.026782049999998964 @[1739224800]\n0.02216576666666583 @[1739226600]\n0.01913684999999911 @[1739228400]\n0.023757316666664488 @[1739230200]\n0.02829146666666702 @[1739232000]\n0.02004301666666682 @[1739233800]\n0.020785300000000007 @[1739235600]\n0.02167980000000019 @[1739237400]\n0.023134699999999005 @[1739239200]\n0.02061428333333121 @[1739241000]\n0.018396533333331414 @[1739242800]\n0.025664516666665804 @[1739244600]\n0.02051421666666329 @[1739246400]\n0.023264433333330694 @[1739248200]\n0.01754038333333483 @[1739250000]\n0.015764933333328675 @[1739251800]\n{cluster=\"sandbox\", container=\"alertmanager\", cpu=\"total\", id=\"/kubepods.slice/kubepods-besteffort.slice/kubepods-besteffort-pod1c68cd26_9762_4465_bb5e_aa862f1d240c.slice/cri-containerd-472f381014c2a5aca6a29c9171d20ec8fbf5f6d32857420e45dd2d12e3c9772a.scope\", image=\"docker.io/prom/alertmanager:v0.24.0\", instance=\"gke-sandbox-e2-standard-4-20250202084-5e775834-d56q\", job=\"kubelet\", metrics_path=\"/metrics/cadvisor\", name=\"472f381014c2a5aca6a29c9171d20ec8fbf5f6d32857420e45dd2d12e3c9772a\", namespace=\"prometheus-benchmark\", node=\"gke-sandbox-e2-standard-4-20250202084-5e775834-d56q\", pod=\"prometheus-benchmark-prometheus-benchmark-vmalert-stable-679tsw\", prometheus=\"monitoring/monitoring-vmagent\"} =>\n0.020917516666668235 @[1738647000]\n0.021485083333330598 @[1738648800]\n0.01812568333333123 @[1738650600]\n0.01895326666666885 @[1738652400]\n0.020437199999999697 @[1738654200]\n0.018737349999999726 @[1738656000]\n0.019980933333332965 @[1738657800]\n0.013724149999999706 @[1738659600]\n0.016114216666665016 @[1738661400]\n0.020132166666667218 @[1738663200]\n0.020694649999995818 @[1738665000]\n0.01994368333332659 @[1738666800]\n0.0207525333333327 @[1738668600]\n0.01822701666666641 @[1738670400]\n0.020424566666664153 @[1738672200]\n0.018822716666666867 @[1738674000]\n0.020839316666668613 @[1738675800]\n0.025253383333332144 @[1738677600]\n0.026610583333331307 @[1738679400]\n0.02745311666666718 @[1738681200]\n0.02240231666666356 @[1738683000]\n0.021877483333332746 @[1738684800]\n0.022235616666671378 @[1738686600]\n0.02573980000000423 @[1738688400]\n0.02410701666666076 @[1738690200]\n0.02289696666666714 @[1738692000]\n0.024988216666664207 @[1738693800]\n0.018542300000005223 @[1738695600]\n0.021138616666667075 @[1738697400]\n0.024287999999993797 @[1738699200]\n0.016450449999986936 @[1738701000]\n0.017589916666671947 @[1738702800]\n0.014069500000005064 @[1738704600]\n0.017460283333336216 @[1738706400]\n0.019971433333330423 @[1738708200]\n0.019479616666664392 @[1738710000]\n0.019928333333336923 @[1738711800]\n0.025698333333336147 @[1738713600]\n0.024092866666660485 @[1738715400]\n0.016929433333340665 @[1738717200]\n0.019066533333337552 @[1738719000]\n0.01632683333333868 @[1738720800]\n0.019600900000007946 @[1738722600]\n0.01900656666666691 @[1738724400]\n0.017512366666672583 @[1738726200]\n0.013668983333324529 @[1738728000]\n0.01706414999998742 @[1738729800]\n0.022597333333336186 @[1738731600]\n0.020003883333326183 @[1738733400]\n0.026289983333329776 @[1738735200]\n0.02011720000000423 @[1738737000]\n0.020528466666655733 @[1738738800]\n0.017551783333328786 @[1738740600]\n0.023303616666665524 @[1738742400]\n0.03169876666665914 @[1738744200]\n0.03000130000000354 @[1738746000]\n0.030305650000006304 @[1738747800]\n0.024123200000000605 @[1738749600]\n0.016859450000007808 @[1738751400]\n0.02158039999999346 @[1738753200]\n0.022668250000000018 @[1738755000]\n0.01969823333332291 @[1738756800]\n0.02543635000000298 @[1738758600]\n0.020945566666644783 @[1738760400]\n0.026114266666672846 @[1738762200]\n{cluster=\"sandbox\", container=\"alertmanager\", cpu=\"total\", id=\"/kubepods.slice/kubepods-besteffort.slice/kubepods-besteffort-pod1ca23e10_46c1_43aa_9de4_4392cfa2eb4d.slice/cri-containerd-892e1ed07282affb8400f20a509b7f0042334ff3e5614e7358fe90e9fadd50a3.scope\", image=\"docker.io/prom/alertmanager:v0.24.0\", instance=\"gke-sandbox-e2-standard-4-20250202084-5e775834-pk4l\", job=\"kubelet\", metrics_path=\"/metrics/cadvisor\", name=\"892e1ed07282affb8400f20a509b7f0042334ff3e5614e7358fe90e9fadd50a3\", namespace=\"prometheus-benchmark\", node=\"gke-sandbox-e2-standard-4-20250202084-5e775834-pk4l\", pod=\"prometheus-benchmark-prometheus-benchmark-vmalert-lts-74fd9zsgv\", prometheus=\"monitoring/monitoring-vmagent\"} =>\n0.022579900000005183 @[1738647000]\n0.012792566666666972 @[1738648800]\n0.01565369999999954 @[1738650600]\n0.018829583333331356 @[1738652400]\n0.016695916666662924 @[1738654200]\n0.018517750000000888 @[1738656000]\n0.016090266666666745 @[1738657800]\n0.021576616666667783 @[1738659600]\n0.020383066666666613 @[1738661400]\n0.020014199999999014 @[1738663200]\n0.020113516666666935 @[1738665000]\n0.020139016666666974 @[1738666800]\n0.022817300000004554 @[1738668600]\n0.026407866666666755 @[1738670400]\n0.02094406666666752 @[1738672200]\n0.02389858333332692 @[1738674000]\n0.02392320000000533 @[1738675800]\n0.027415033333333363 @[1738677600]\n0.027713350000006663 @[1738679400]\n0.023856099999996636 @[1738681200]\n0.02418405000000045 @[1738683000]\n0.018232800000002197 @[1738684800]\n0.018894616666663446 @[1738686600]\n0.024239699999998265 @[1738688400]\n0.023878400000012335 @[1738690200]\n0.025865549999995588 @[1738692000]\n0.01437783333334058 @[1738693800]\n0.01847023333333103 @[1738695600]\n0.018981050000002143 @[1738697400]\n0.02573850000000372 @[1738699200]\n0.02427714999998898 @[1738701000]\n0.023488033333327014 @[1738702800]\n0.0221835833333292 @[1738704600]\n0.021186350000001162 @[1738706400]\n0.021644149999989773 @[1738708200]\n0.014894350000001092 @[1738710000]\n0.02058006666666188 @[1738711800]\n0.022788599999997435 @[1738713600]\n0.022787233333338007 @[1738715400]\n0.027227800000006634 @[1738717200]\n0.023487599999998564 @[1738719000]\n0.026769666666662792 @[1738720800]\n0.025153649999977764 @[1738722600]\n0.01732266666667783 @[1738724400]\n0.016600866666673635 @[1738726200]\n0.019061066666669527 @[1738728000]\n0.02014761666666042 @[1738729800]\n0.01877315000000029 @[1738731600]\n0.023290750000008607 @[1738733400]\n0.01693399999999201 @[1738735200]\n0.021256883333338313 @[1738737000]\n0.023866349999995387 @[1738738800]\n0.020127300000012838 @[1738740600]\n0.02085175000000466 @[1738742400]\n0.02136873333333824 @[1738744200]\n0.021882066666663983 @[1738746000]\n0.026603833333335086 @[1738747800]\n0.02142983333333177 @[1738749600]\n0.016146816666666078 @[1738751400]\n0.025512016666668084 @[1738753200]\n0.020112733333326104 @[1738755000]\n0.023248083333328395 @[1738756800]\n0.020968516666668317 @[1738758600]\n0.01953971666666803 @[1738760400]\n0.017602883333317245 @[1738762200]\n{cluster=\"sandbox\", container=\"alertmanager\", cpu=\"total\", id=\"/kubepods.slice/kubepods-besteffort.slice/kubepods-besteffort-pod2112da82_41a2_43fa_b0a5_402b060b77a4.slice/cri-containerd-0e5d5cbd239fd84a29616957557597ec3ea14535c83f77abbab6c87029c1e35c.scope\", image=\"docker.io/prom/alertmanager:v0.24.0\", instance=\"gke-sandbox-e2-standard-4-20250202084-5e775834-yui5\", job=\"kubelet\", metrics_path=\"/metrics/cadvisor\", name=\"0e5d5cbd239fd84a29616957557597ec3ea14535c83f77abbab6c87029c1e35c\", namespace=\"prometheus-benchmark\", node=\"gke-sandbox-e2-standard-4-20250202084-5e775834-yui5\", pod=\"prometheus-benchmark-prometheus-benchmark-vmalert-lts-74fdcmcjp\", prometheus=\"monitoring/monitoring-vmagent\"} =>\n0.04016348333333332 @[1738764000]\n0.01767145000000004 @[1738765800]\n0.01933393333333318 @[1738767600]\n0.020531950000000167 @[1738769400]\n0.019258616666666246 @[1738771200]\n0.021003666666666733 @[1738773000]\n0.017399183333333214 @[1738774800]\n0.0174815833333336 @[1738776600]\n0.01902750000000045 @[1738778400]\n0.015750849999999636 @[1738780200]\n0.01951358333333341 @[1738782000]\n0.015492900000000039 @[1738783800]\n0.017244033333333655 @[1738785600]\n0.016220750000000332 @[1738787400]\n0.015617949999998852 @[1738789200]\n0.020186950000000554 @[1738791000]\n0.021303216666666458 @[1738792800]\n0.0242124833333321 @[1738794600]\n0.021351333333332907 @[1738796400]\n0.022885866666666744 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