Ganeshan Venkataraman ganeshan

SSL Certificate Generation

Keystore & mkcert

PKCS12 is the industry standard, however, java has a proprietary format specific for Java called JKS, we will stick with PKC12 for our keystore.
Managing the generation of certs and trust store system wide, mkcert is an incredibly useful tool

Install mkcert

brew install mkcert

Migration to ASP.NET Core in .NET 6

WebApplication and WebApplicationBuilder
Differences in the hosting model
Building libraries for ASP.NET Core
FAQ
Cheatsheet

WebApplication and WebApplicationBuilder

OSRM North America route server on EC2

Overview

OSRM route server is an extremely useful tool for getting the driving distance/time through multiple locations. The route server requires data that has to be downloaded and processsed before it can be used to serve routes from.

Processing OSRM data for large region like North America can be a real challenge due to memory and disk size requirements. It's also really time consuming. If you cut and try from scratch, you will repeatedly run into some constraints and fail after hours of running.

The following are summary notes from trying this with eventual success.

Spatial SQL and PostGIS

This set of instructions goes with this presentation deck.

Installing PostGIS

PGDG Yum Repository

https://yum.postgresql.org/

yum install postgis24_10

Where :

FIRST_ROWS(N) tells the optimizer, "Hey, I'm interested in getting the first rows, and I'll get N of them as fast as possible."
:MAX_ROW_TO_FETCH is set to the last row of the result set to fetch—if you wanted rows 50 to 60 of the result set, you would set this to 60.
:MIN_ROW_TO_FETCH is set to the first row of the result set to fetch, so to get rows 50 to 60, you would set this to 50.

Source https://blogs.oracle.com/oraclemagazine/on-rownum-and-limiting-results

	import pandas as pd
	import numpy as np

	def get_dataset(size):
	# Create Fake Dataset
	df = pd.DataFrame()
	df['size'] = np.random.choice(['big','medium','small'], size)
	df['age'] = np.random.randint(1, 50, size)
	df['team'] = np.random.choice(['red','blue','yellow','green'], size)
	df['win'] = np.random.choice(['yes','no'], size)

	/**
	* Autowire Quartz Jobs with Spring context dependencies
	* @see http://stackoverflow.com/questions/6990767/inject-bean-reference-into-a-quartz-job-in-spring/15211030#15211030
	*/
	public final class AutowiringSpringBeanJobFactory extends SpringBeanJobFactory implements ApplicationContextAware {
	private transient AutowireCapableBeanFactory beanFactory;

	public void setApplicationContext(final ApplicationContext context) {
	beanFactory = context.getAutowireCapableBeanFactory();
	}

	import com.jcraft.jsch.SftpProgressMonitor;
	import lombok.Getter;
	import lombok.RequiredArgsConstructor;
	import lombok.Setter;

	@RequiredArgsConstructor
	public class CustomSftpProgressMonitor implements SftpProgressMonitor {

	private final long totalbytes;

	def optimised_pagination(query, per_page, page):
	'''A more efficient pagination for SQLAlchemy
	Fetch one item before offset (to know if there's a previous page)
	Fetch one item after limit (to know if there's a next page)
	The trade-off is that the total items are not available, but if you don't need them
	there's no need for an extra COUNT query
	'''
	offset_start = (page - 1) * per_page

	query_offset = max(offset_start - 1, 0)

	-- ¡¡¡¡Resumenes con ejemplos de cada tema!!!!
	http://www.morganslibrary.org/library.html

	https://lalitkumarb.wordpress.com/2014/05/31/oracle-explain-plan/

	-- EXPLAIN PLAN FOR
	-- per consultar resultat:
	set linesize 132;
	SELECT * FROM TABLE(dbms_xplan.display);