| WITH btree_index_atts AS ( | |
| SELECT nspname, relname, reltuples, relpages, indrelid, relam, | |
| regexp_split_to_table(indkey::text, ' ')::smallint AS attnum, | |
| indexrelid as index_oid | |
| FROM pg_index | |
| JOIN pg_class ON pg_class.oid=pg_index.indexrelid | |
| JOIN pg_namespace ON pg_namespace.oid = pg_class.relnamespace | |
| JOIN pg_am ON pg_class.relam = pg_am.oid | |
| WHERE pg_am.amname = 'btree' | |
| ), |
| WITH table_scans as ( | |
| SELECT relid, | |
| tables.idx_scan + tables.seq_scan as all_scans, | |
| ( tables.n_tup_ins + tables.n_tup_upd + tables.n_tup_del ) as writes, | |
| pg_relation_size(relid) as table_size | |
| FROM pg_stat_user_tables as tables | |
| ), | |
| all_writes as ( | |
| SELECT sum(writes) as total_writes | |
| FROM table_scans |
| --- PSQL queries which also duplicated from https://github.com/anvk/AwesomePSQLList/blob/master/README.md | |
| --- some of them taken from https://www.slideshare.net/alexeylesovsky/deep-dive-into-postgresql-statistics-54594192 | |
| -- I'm not an expert in PSQL. Just a developer who is trying to accumulate useful stat queries which could potentially explain problems in your Postgres DB. | |
| ------------ | |
| -- Basics -- | |
| ------------ | |
| -- Get indexes of tables |
This is a very simple script, so don't expect something great.
You can change it, distribute, do whatever you like, I don't mind. But if you improve it, you could share it back ;)
To use, you have to export variables to use aws-cli, like AWS_PROFILE, AWS_DEFAULT_REGION, etc. Then just call the script using watch (or however you like) and giving the RDS instance name:
watch ./rds-top.sh <your instance name>
Requirements:
| # | |
| # This is the ultimate HAProxy 2.0 "Getting Started" config | |
| # It demonstrates many of the features available which are now available | |
| # While you may not need all of these things, this can serve | |
| # as a reference for your own configurations. | |
| # | |
| # Have questions? Check out our community Slack: | |
| # https://slack.haproxy.org/ | |
| # |
This is a living document. Everything in this document is made in good faith of being accurate, but like I just said; we don't yet know everything about what's going on.
Update: I've disabled comments as of 2025-01-26 to avoid everyone having notifications for something a year on if someone wants to suggest a correction. Folks are free to email to suggest corrections still, of course.
A pattern for building personal knowledge bases using LLMs.
This is an idea file, it is designed to be copy pasted to your own LLM Agent (e.g. OpenAI Codex, Claude Code, OpenCode / Pi, or etc.). Its goal is to communicate the high level idea, but your agent will build out the specifics in collaboration with you.
Most people's experience with LLMs and documents looks like RAG: you upload a collection of files, the LLM retrieves relevant chunks at query time, and generates an answer. This works, but the LLM is rediscovering knowledge from scratch on every question. There's no accumulation. Ask a subtle question that requires synthesizing five documents, and the LLM has to find and piece together the relevant fragments every time. Nothing is built up. NotebookLM, ChatGPT file uploads, and most RAG systems work this way.