Thomas Yager-Madden tym-xqo

author	title	revision	version	description
tym-xqo	BenchPrep SQL Style Guide	2021-12-12	1.1.1	A guide to writing clean, clear, and consistent SQL.

BenchPrep SQL Style Guide [WIP]

(TL;DR: see "Recommendations" at the end)

OK, so. There are a few things going on here. The example query as originally written:

explain analyze
select count(*)
  from "burning_glass_jobs"

Nerium does not have a SQL query authoring interface, by design. "Write SQL in your favorite editor" is a feature, indeed one of the main selling points.
So, a public offering needs a way to get SQL to it. I'm thinking of something that handled this through cloud storage: user writes and saves queries to a local directory; Nerium-SaaS offers a mechanism like Netlify, to ingest that and upload it to the cloud, using some naming scheme to ID the tenant and an "upload event" or release.
also like Netlify, this could be handled via GitHub integration
user also needs to be able to provide a database url to their data source. this will necessarily include a password, so it will have to be done securely somehow — I.e. ideally the Nerium instance we launch for them in k8s as access to it, but we as the service provider do not. At a minimum, if we can't get around having to share the share the secret, it's at least protected from other tenants and outsiders. In general, I imagine th

If you have a local Postgres service running on port 5432, stop it first
Get Docker Desktop for Mac if you don't have it already
Pull Postgres 10 image from Docker Hub: docker pull postgres:10
Create a directory in a known location that will be mounted as a data volume where the container will store the database files: mkdir -p -m 0700 ${HOME}/Library/postgres-data
Run the image (note that POSTGRES_PASSWORD is required in the container environment, and will be the password for the postgres user in the container Postgres instance):
```
 docker run -d \
   --name=dev-postgres \
```

Definition: the systems engineering practice of handling changes systematically so that a system maintains its integrity over time.

In software, this generally means ensuring the consistency of the environment in which our applications run:

the operating system
versions of interpreters, libraries, packages, and other services on which our stuff depends

overall: as-it-happens discussion/conversation between ~tym and ~jmiller
maybe invite other guests sometimes?
broadly, subject matter of these conversations would focus on "what we think works in software projects" with the philosophy of "radical incrementalism" in the background — but not be limited to these
let's record 6 1-hour sessions
- it would be nice if we can get together in person for these somewhere, but we could always do over a call
following something like St. John's College seminar practice, each session begins with an Opening Question, which we take turns asking
once underway, we should let the conversation "follow the argument" — we don't need to stick to trying to answer the opening question directly; relevant tangents and even out-and-out digression is welcome and encouraged (although we should try to circle back and close open loops where we can). The Opening Question is a way to begin the discussion, not to limit its course
after we have 6 hours

(Maybe/Probably) Suspend boost reporting job
~~ut site in maintenance mode(?)~~
Manual run of boost etl job
Switch Production k8s endpoints to boost02
- external-reporting-compute-database
external-reporting-database

	#!/usr/local/bin/zsh

	TOKEN=$(python3 -c "import secrets; print(secrets.token_hex(24)[:7])")
	# echo $TOKEN
	POD=$(kubectl get pods \| grep tmp-$USER-dba \| awk '{print $1}')
	if [[ -z $POD ]]
	then
	POD="tmp-$USER-dba-$TOKEN"
	kubectl run $POD \
	--image=registry.gitlab.com/tym27/jackknife:latest \

	#!/bin/bash
	set -e
	env=${1-integration}
	chart=${2-apps}
	config=$(kubectl config get-contexts -o name \| grep "$env")
	for i in $config; do
	kubectl config use-context $i
	helm3 status $chart
	done

	#!/usr/bin/env python
	# -- coding: utf-8 --
	"""Use SQLAlchemy engine to fetch a dataset from a query
	"""
	import os

	from jinja2.sandbox import SandboxedEnvironment
	from sqlalchemy import create_engine