Josh Goldsmith j0shua

##Neo4j GraphGist - Enterprise Architectures: Real-time Graph Updates using Kafka Messaging

Neo4j Use Case: Low Latency Graph Analytics & OLTP - Update 1M Nodes in 90 secs with Kafka and Neo4j Bolt

Introduction

A recent Neo4j whitepaper describes how Monsanto is performing real-time updates on a 600M node Neo4j graph using Kafka to consume data extracted from a large Oracle Exadata instance.

This modern data architecture combines a fast, scalable messaging platform (Kafka) for low latency data provisioning and an enterprise graph database (Neo4j) for high performance, in-memory analytics & OLTP - creating new and powerful real-time graph analytics capabilities for your enterprise applications.

Kubectl output options

Let's look at some basic kubectl output options.

Our intention is to list nodes (with their AWS InstanceId) and Pods (sorted by node).

We can start with:

kubectl get no

	"""
	# MIT License (c) Luke Stanley 2024
	AIOHTTP server to save webpage text changes with timestamps.
	Prints changes to the console and saves them to 'changes.jsonl' in the background.

	Dependencies: aiohttp, asyncio

	Install: pip install aiohttp
	Run: python3 logging_server_aio.py

	#!/bin/bash
	# In honor of the remarkable Windson
	#/bin/bash
	namespace=$1

	if [[ -z "$namespace" ]]; then
	echo "Use "$(basename "$0")" NAMESPACE";
	exit 1;
	fi

	#!/usr/bin/env bash

	find_files() {
	ag "$1" \| cut -d: -f1 \| sort \| uniq
	}

	do_replace() {
	echo "Finding files matching orignial string $1"
	for f in $(find_files "$1"); do
	echo " -> Replacing string in file $f"

	from slacker import Slacker
	import json
	import argparse
	import os
	import shutil
	import copy
	import requests
	import urllib3
	#from io import open
	from datetime import datetime

	VPN Notes, Scripts

	Victoria Stuart: Apr 12, 2017
	[gmail: Victorias.Linux@ ...]

	File: /mnt/Vancouver/Reference/VPN/vpn notes, scripts.txt

	Saved 2017-Apr-12 as public Gist:
	https://gist.github.com/victoriastuart/19acf4944c9c95af461d62b27d0c19ec

	/*
	This snippet is an example of backpressure implementation in Go.
	It doesn't run in Go Playground, because it starts an HTTP Server.

	The example starts an HTTP server and sends multiple requests to it. The server starts denying
	requests by replying an "X" (i.e. a 502) when its buffered channel reaches capacity.

	This is not the same as rate-limiting; you might be interested in https://github.com/juju/ratelimit
	or https://godoc.org/golang.org/x/time/rate.

	FROM nginx
	HEALTHCHECK --interval=3s --retries=20 CMD curl -fs http://localhost:${HTTP_PORT:-8000}

	# coding: utf-8

	# FILE:
	# -----
	# /mnt/Vancouver/apps/Webcam-Face-Detect/webcam_cv3_v2_fps_v3.py

	# FUNCTIONALITY:
	# --------------
	# * outputs webcam to screen and finds faces, eyes
	# * writes webcam video to *.avi file (MJPG codec) via OpenCV/FourCC