{"id":16445286,"url":"https://github.com/dgapitts/pgday-munich-work_mem","last_synced_at":"2025-10-23T17:28:07.077Z","repository":{"id":232836503,"uuid":"781575033","full_name":"dgapitts/pgday-munich-work_mem","owner":"dgapitts","description":null,"archived":false,"fork":false,"pushed_at":"2024-04-13T17:11:11.000Z","size":3172,"stargazers_count":1,"open_issues_count":0,"forks_count":0,"subscribers_count":2,"default_branch":"main","last_synced_at":"2024-04-14T16:07:32.879Z","etag":null,"topics":[],"latest_commit_sha":null,"homepage":null,"language":"Shell","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":null,"license":null,"status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/dgapitts.png","metadata":{"files":{"readme":"README.md","changelog":null,"contributing":null,"funding":null,"license":null,"code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null,"roadmap":null,"authors":null,"dei":null,"publiccode":null,"codemeta":null}},"created_at":"2024-04-03T16:34:54.000Z","updated_at":"2024-04-14T16:07:32.879Z","dependencies_parsed_at":"2024-04-11T19:13:34.356Z","dependency_job_id":"f1d9d49d-cc17-4e29-9142-0154c5910162","html_url":"https://github.com/dgapitts/pgday-munich-work_mem","commit_stats":null,"previous_names":["dgapitts/pgday-munich-work_mem"],"tags_count":0,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dgapitts%2Fpgday-munich-work_mem","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dgapitts%2Fpgday-munich-work_mem/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dgapitts%2Fpgday-munich-work_mem/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/dgapitts%2Fpgday-munich-work_mem/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/dgapitts","download_url":"https://codeload.github.com/dgapitts/pgday-munich-work_mem/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":240831199,"owners_count":19864711,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":[],"created_at":"2024-10-11T09:43:54.535Z","updated_at":"2025-10-23T17:28:06.979Z","avatar_url":"https://github.com/dgapitts.png","language":"Shell","funding_links":[],"categories":[],"sub_categories":[],"readme":"# pg-day Munich - work_mem demos\n\n## Intro\nPostgres work_mem and private memory management is an important topic but not often discussed in depth at postgres events?\nI'm presenting at pgDay DE (Munich) 2024 on this topic in-depth and would like to focus on just\n\n(a) the recent hash_mem_multiplier changes affecting anyone upgrading to pg15 or pg16 and\n\n(b) some of the extra challenges DBaaS users have\n\n(c) tuning using heuristics (PGTune) vs ML (DBtune)\n\n\n\n## Demos \n* [Demo01 - Private Process Memory Management -  work_mem and hash_mem_multiplier woth HashAggregate operation - saves disc io](docs/Demo01-Private-Process-Memory-Management-work_mem-and-hash_mem_multiplier.md)\n* [Demo02 - Private-Process Memory Management work_mem and hash_mem_multiplier with Sort operations - no affect](docs/Demo02-Private-Process-Memory-Management-work_mem-and-hash_mem_multiplier-with-sorts.md)\n* [Demo03 - pgbench custom scripts for high concurrent HashAggregate operation - exhaust CPU and memory usage is not significantly impacted](docs/Demo03-pgbench-custom-scripts-for-high-concurrent-HashAggregate-operation.md)\n* [Demo04 - DBtune test results and jupyter based analysis](docs/Demo04-DBtune-test-results-and-jupyter-based-analysis.md)\n* [Demo05 - Edge Cases run away dynamic SQL](docs/Demo05-Edge-Cases-run-away-dynamic-SQL.md)\n\u003c\u003c\u003c\u003c\u003c\u003c\u003c HEAD\n=======\n\n\n## Q\u0026A\n\nSome nice feedback and Q\u0026A\n* I need to cover an edge where a long-running process can have a high memory footprint when idle ... going to try demo-ing this (todo list)\n* Regarding DB tune could we (a) add bounds and (b) should we add hash_mem_multiplier as a parameter ... good questions for DBtune team (@luigi)\n\n## Slides\n\n* [DB_Memory_Management-work_mem-pgDay_Munich_2024.pdf](docs/DB_Memory_Management-work_mem-pgDay_Munich_2024.pdf) (2.5Mb)\n\u003e\u003e\u003e\u003e\u003e\u003e\u003e b3b3003 (add-some-feedback-and-slides)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdgapitts%2Fpgday-munich-work_mem","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fdgapitts%2Fpgday-munich-work_mem","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fdgapitts%2Fpgday-munich-work_mem/lists"}