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Performance issues when running unfurl_version_range_v2advisor (and others)

Aperta
#2,333 3 commenti 1 reazione 0 assegnatari Vedi su GitHub

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Valutazione

Difficoltà
5/5
Tempo stimato
Più di una settimana
Idoneità per principianti
25/100
Tipo di issue
Bug
Chiarezza
Da chiarire
Stato di attività
Tranquilla
Stack tecnologico
postgresql, python

Direzione di ricerca

Il report indica unfurl_version_range_v2advisor improver e i comandi di gestione import --all e improve --all; inizia profilando questi punti di ingresso rispetto alle dimensioni delle tabelle PostgreSQL e alla query pg_stat_user_tables fornita. Un contributo richiederebbe una modifica delle prestazioni definita e riproducibile e un criterio di completamento misurabile, nessuno dei quali è attualmente specificato dall’issue.

Scritto dal modello di indicizzazione a partire dal testo della issue.

Descrizione

Hi Team,

first release: v34.0.0rc4 (or earlier)
current release: 38.1.0

Our database dates back 2+years and has grown a lot. I checked the sizes of some of the tables using this command:

SELECT
    schemaname AS schema,
    relname AS table_name,
    n_live_tup AS row_count
FROM
    pg_stat_user_tables
ORDER BY
    n_live_tup DESC;

Results were staggering:

"vulnerabilities_impactedpackageaffecting"	735403239 =735 mln (!!!)
"vulnerabilities_advisory"	54630236  = 54 mln
"vulnerabilities_advisoryrelatedalias"	54622255 = 54 mln
"vulnerabilities_packagechangelog"	34332358 =  34 mln
"vulnerabilities_vulnerability_severities"	32511124 =  32 mln
"vulnerabilities_vulnerabilityseverity"	32221132 =  32 mln
"vulnerabilities_impactedpackage"	        25634100 =  25 mln
"vulnerabilities_impactedpackagefixedby"	8558740 =  8mln

We are running VulnerableCode on OpenShift and decided that we wanted a regular updates of the importers and improvers, so we created CronJobs that would import/improve just one thing each (for example python manage.py import nvd_importer_v2). With the new version we have 137 pods running running at different times of day. While this was a lot but sort of manageable (at least we thought) we have starting noticing problems our database was under enormous load especially when improvers run. While I know that this is caused by parallel runs there is one specific improver that causes our nodes to crash and push the database beyond CPU limits - unfurl_version_range_v2advisor it was running usually for 4 days straight and using north of 44 GiB of RAM on OpenShift and 10-12 CPUs on PostgreSQL side.

With this we tried running importers and improvers as it says in documentation import --all and improve --all but those takes days or weeks to do.

Most recent importer --all run:

CommandError: 8 failed!: apache_kafka_importer_v2,mattermost_importer_v2,gitlab_importer,pypa_importer,npm_importer,nginx_importer,pysec_importer,vulnerabilities.importers.istio.IstioImporter

and it still took 26 hrs. and that is just importers on their own.

We haven't been able to do full run of the improve -all as of yet as I have seen some of those improvers can run for 3-4 days each.

So the question here arises, what to do with this as with this version it is unusable for our production instances.

what to do?

  1. Delete the whole thing and start over with new db
  2. Run importers once every 26 hrs, and then start improve --all which will take most likely weeks
  3. Skip most resource intensive improvers and just do the rest?

I would love to hear your suggestions on possible solutions, or how you run it?

Lingua principale
Python
Stelle
716
Fork
347
Merge medio
12h 15m
PR unite (30g)
9

Preparare l'ambiente

  • Include un Dockerfile o un file Docker Compose
  • Nessun modello di pull request
  • Nessuna guida per i contributori

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