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Performance issues when running unfurl_version_range_v2advisor (and others)

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評估

難度
5/5
預估耗時
一週以上
新手友好度
25/100
Issue 類型
缺陷
描述清晰度
需要釐清
活躍度
冷清
技術堆疊
postgresql, python
領域
backend, databases, performance

研究方向

報告指出了 unfurl_version_range_v2advisor improver 以及管理命令 import --all 和 improve --all；首先根據提供的 PostgreSQL 資料表大小和 pg_stat_user_tables 查詢，對這些進入點進行效能分析。一項貢獻需要明確且可重現的效能變更，以及可量測的完成標準，而目前的 issue 尚未指定這兩者中的任何一個。

由索引模型根據 Issue 內容生成。

描述

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?

主要語言
Python
星號
716
分支
347
平均合併
12 小時 15 分鐘
30 天內合併 PR
9

環境準備

  • 提供 Dockerfile 或 Docker Compose 檔案
  • 沒有 Pull Request 範本
  • 沒有貢獻指南

從這裡開始

  1. 先讀完整個 Issue，再讀專案的貢獻指南。
  2. 在 Issue 下留言說明你要接手 —— 這能避免兩個人做同樣的事。
  3. Fork 儲存庫，在一個分支上完成修改。
  4. 送出 Pull Request，並在描述裡引用這個 Issue 編號。

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