vingao

_/﹋\_
(҂`_´)
<,︻╦╤─ ҉ - - Y O U   G O T   H A C K E D
_/﹋\_

vingao

{
    "public_identifier": "eden-marco",
    "profile_pic_url": "https://s3.us-west-000.backblazeb2.com/proxycurl/person/eden-marco/profile?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=0004d7f56a0400b0000000001%2F20240609%2Fus-west-000%2Fs3%2Faws4_request&X-Amz-Date=20240609T145729Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=2773956fb88e429ba25214cd60a8fd40c0b6c26e3dc606a2b61dc4aea384b8b5",
    "background_cover_image_url": "https://s3.us-west-000.backblazeb2.com/proxycurl/person/eden-marco/cover?X-Amz-Algorithm=AWS4-HMAC-SHA256&X-Amz-Credential=0004d7f56a0400b0000000001%2F20240609%2Fus-west-000%2Fs3%2Faws4_request&X-Amz-Date=20240609T145729Z&X-Amz-Expires=3600&X-Amz-SignedHeaders=host&X-Amz-Signature=cc9166ff7356a3805f758246a1b989a0229c7eddd9d207a9d573a7c686fc8427",
    "first_name": "Eden",
    "last_name": "Marco",
    "full_name": "Eden Marco",
    "follower_count": 4414,
    "occupation": "LLM Specialist, Customer Engineering - Google Cloud at Google",
    "headline": "LLMs @ Google

vingao

import redis
import sys

host = sys.argv[1]
room = sys.argv[2]
print "-- connect to redis"
client = redis.Redis(host=host)
pubsub = client.pubsub()
pubsub.subscribe(room)
print "-- listen to {}".format(room)

vingao

Ruby on Rails Cheatsheet

Architecture

Create a new application

Install the Rails gem if you haven't done so before

vingao

GOTO 2017 • The Many Meanings of Event-Driven Architecture - Martin Fowler

(the video is here, the original talk notes are here)

At least one of those four patterns are in play when you talk about "event-driven" architectures:

1. Event Notification: components communicating via events
2. Event-carried State Transfer: allowing components to access data without calling the source
3. Event Sourcing: using an event log as the primary record for a system
4. CQRS: having a separate component for updating a store from any readers of the store

vingao

from __future__ import absolute_import, division, print_function, unicode_literals
from tensorflow.keras import layers

try:
  # %tensorflow_version only exists in Colab.
  %tensorflow_version 2.x
except Exception:
  pass
import tensorflow as tf

vingao

Configure Git to use a proxy

In Brief

You may need to configure a proxy server if you're having trouble cloning or fetching from a remote repository or getting an error like unable to access '...' Couldn't resolve host '...'.

Consider something like:

vingao

-- show running queries (pre 9.2)
SELECT procpid, age(clock_timestamp(), query_start), usename, current_query 
FROM pg_stat_activity 
WHERE current_query != '<IDLE>' AND current_query NOT ILIKE '%pg_stat_activity%' 
ORDER BY query_start desc;

-- show running queries (9.2)
SELECT pid, age(clock_timestamp(), query_start), usename, query 
FROM pg_stat_activity 
WHERE query != '<IDLE>' AND query NOT ILIKE '%pg_stat_activity%' 

vingao

$ s3cmd get s3://us-east-1.elasticmapreduce/libs/s3distcp/1.latest/s3distcp.jar
$ hadoop jar ./s3distcp.jar --src s3a://<bucket>/input/ --dest=s3a://<bucket>/output

vingao

import base64
import os
import time

"""
Writing from Spark to S3 is ridiculously slow. This is because S3 is an object
store and not a file system. Because of consistency model of S3, when writing
Parquet (or ORC) files from Spark. Data will be stored to a temporary destination
then renamed when the job is successful. As S3 is an object store, renaming files
is very expensive (complete rewrite). The Spark job will only terminate when all