El nucleo de la programacion asincrona son los objetos Task y Task<T>. Son compatibles con las palabras clave async y await.

Primero hay que reconocer si el codigo se usa para trabajos enlazados a I/O o si son CPU intensivos.

• Si el codigo espera algo como una BBDD o una response de un servidor, es codigo I/O. En este caso hay que usar async y await
• Si el codigo realiza un calculo costoso, es CPU intensivo. Use await para esperar una operacion que se ha comenzado en background con Task.run

Async / Await (Operaciones I/O)

La palabra clave importante aqui es await. Lo que hace es suspender la ejecucion del metodo actual y devolver el control hasta que está lista para seguir.

public async Task Main()
{
	string contenido = await LeerPaginaWebAsync("http://example.com");
}

private async Task<string> LeerPaginaWebAsync(string url)
{
	using (HttpClient client = new HttpClient())
	{
		return await client.GetStringAsync(url);
	}
}

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Config

Azure

log-in into a tenant

az login --tenant 7f2c3a6b-e849-4d6f-b65d-1c0ef8b0f41c

configure local kubectl .kube config file

az aks get-credentials --resource-group my-aks --name aksname --admin

(the –admin part is optional but useful)

Contexts & Namespaces

see all configured contexts

kubectl config get-contexts

configure a context with a default namespace

kubectl config set-context <context_here> --namespace=<namespace_here>
# example
kubectl config set-context my-aks-context --namespace=aks-dev

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Data generated and used by Docker containers does not persist after restarts. We use Docker volumes to manage data to solve this issue. We use it to persist data in a container or share data between containers.

Volumes are the preferred mechanism for persisting data generated and user by Docker containers. Volumes are easier to back up or migrate.

Volumes are often a better choice than persisting data in a container’s writable layer, because a volume does not increase the size of the containers using it. The volume’s contents exist outside the lifecycle of a given container.

We have 3 volume types:

Anonymous volumes

Helpful to persist data temporarily. If we restart our container data is still visible. It doesn’t persist when we remove the container. Not accessible by other containers. They’re created inside /var/lib/docker/volume.

Example file:

version: '3.8'  
services:  
  db:  
    image: mysql  
    restart: always  
    environment:  
      MYSQL_ROOT_PASSWORD: root  
      MYSQL_DATABASE: test_db  
    ports:  
      - "3306:3306"  
    volumes:  
      - /var/lib/mysql

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Steps to go from a docker-compose file, to build an Image out of the file, upload it to DockerHub, and run it with Kubernetes (minikube).

Set up

Install Kompose

# linux
curl -L https://github.com/kubernetes/kompose/releases/download/v1.22.0/kompose-linux-amd64 -o kompose
chmod +x kompose
sudo mv ./kompose /usr/local/bin/kompose

Clone App and Host It into DockerHub

Clone the files, go to the directory where your Dockerfile is and run:

# mariocodes is my DockerHub username
# kubernetes-custom-java-maven-app is the name of the repo I created at DockerHub
docker build -f Dockerfile -t mariocodes/kubernetes-custom-java-maven-app .

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(Oficial Doc)

Technology to quickly set up a Kubernetes cluster locally to learn how to use Kubernetes.

Installation

How to install on a fresh Ubuntu installation:

Install prerrequisites and kubectl

sudo apt-get update && sudo apt-get install -y apt-transport-https curl

curl -s https://packages.cloud.google.com/apt/doc/apt-key.gpg | sudo apt-key add -

echo "deb https://apt.kubernetes.io/ kubernetes-xenial main" | sudo tee -a /etc/apt/sources.list.d/kubernetes.list

sudo apt-get update
sudo apt-get install -y kubectl

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STATUS CrashLoopBackOff

CrashLoopBackOff and no log appears. This happens as the container has no command to run so it start up and then immediately exits.

Give your image a command.

more here

apiVersion: v1
kind: Pod
metadata:
  name: twocontainers
spec:
  containers:
  - name: container1
    image: python:3.6-alpine
	command: ['sh', '-c', 'echo cont1 > index.html && python -m http.server 8082']
  - name: container2
    image: python:3.6-alpine
	command: ['sh', '-c', 'echo cont1 > index.html && python -m http.server 8083']

Relational

SQL

SQL Cheat Sheet
SQL Triggers & Stored Procedures
SQL Views & Materialized views

PgSQL Functions

PgSQL Functions (Stored Procedure)

MySQL

MySQL Administration
MySQL User Privileges

No-relational

Mongo

MongoDB

ElasticSearch

ElasticSearch

i18n is just a nomenclature for Internationalization. i18n involves, among other things, the ability to display translated content. It prepares a digital product for localization by for example, separate the content into strings so they are ready to be translated and delivered.

The same goes for L10n. This is a nomenclature for Localization. L10n involves translating content, adapting graphics and finalizing the producto for each regional market.

Reference(s)

https://www.oneskyapp.com/blog/i18n-need-to-know-internationalization/

Indexes are a basic structure type that apply to one or multiple columns in order to improve performance and speed up queries that: filter, sort or join data for a table.

this may improve performance for a query that uses last_name in a WHERE clause or an ORDER BY

CREATE INDEX idx_last_name ON employees (last_name);

you can also create composite indexes

CREATE INDEX idx_composite ON employees (last_name, first_name)

and also composite index for only active employees

CREATE INDEX idx_active_employees ON employees (status) WHERE status = 'active';

When to use indexes

Frequent filters WHERE - if you usually filter by a specific column (last_name for example), an index should improve performance.

JOIN for big tables - when you use JOIN with big tables through PKs or FKs.

ORDER BY or GROUP BY - queries that search for / group by a specific column also benefit from indexes.

Best practices

Don’t create indexes in every column. This slows things down on insert, delete or update operations.

Index are best used for big domain fields such as ids, names, surnames. Don’t use them for male/female (or boolean) fields.

Keep indexes optimized: operations where you mass update or mass delete items in your tables may fragment your indexes. You may need to periodically check them and REINDEX them.

ALWAYS MEASURE PERFORMANCE TIME before and after the creation of that index. If your index doesn’t improve performance, remove it as it causes overhead.

Reference(s)

https://stackoverflow.com/questions/7744038/decision-when-to-create-index-on-table-column-in-database
https://stackoverflow.com/questions/52444912/how-to-find-out-fragmented-indexes-and-defragment-them-in-postgresql
https://chatgpt.com/

UNION

The union sentence is used to accumulate results for two SELECT sentences.

SELECT column1, column2 FROM table1
UNION
SELECT column1, column2 FROM table2

We have the following tables

company1

company2

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Find an exact match of a nested field (note that .keyword has to be added to string fields)

{
  "query": {
    "bool": {
      "must": [
        {
          "term": {
            "metadata.title.keyword": "File test.pdf"
          }
        }
      ]
    }
  },
  "size": 200
}

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