Jowanza Joseph josep2

Quick Tips for Fast Code on the JVM

I was talking to a coworker recently about general techniques that almost always form the core of any effort to write very fast, down-to-the-metal hot path code on the JVM, and they pointed out that there really isn't a particularly good place to go for this information. It occurred to me that, really, I had more or less picked up all of it by word of mouth and experience, and there just aren't any good reference sources on the topic. So… here's my word of mouth.

This is by no means a comprehensive gist. It's also important to understand that the techniques that I outline in here are not 100% absolute either. Performance on the JVM is an incredibly complicated subject, and while there are rules that almost always hold true, the "almost" remains very salient. Also, for many or even most applications, there will be other techniques that I'm not mentioning which will have a greater impact. JMH, Java Flight Recorder, and a good profiler are your very best friend! Mea

./bin/drill-embedded                                                                                           
OpenJDK 64-Bit Server VM warning: ignoring option MaxPermSize=512M; support was removed in 8.0
Apr 19, 2017 4:53:50 PM org.glassfish.jersey.server.ApplicationHandler initialize
INFO: Initiating Jersey application, version Jersey: 2.8 2014-04-29 01:25:26...
apache drill 1.10.0 
"drill baby drill"

Now visit link http://localhost:8047 to open up Apache Drill explorer and configure S3 storage plugin refer

Shiny app to highlight on a Leaflet map by brushing a Plotly chart. Run for yourself with (provided all of the packages are installed):

shiny::runGist('da941dac84f730adcdde')

To get this to work on another dataset, you're going to need to have a sequential ID variable that matches the pointNumber column in the data frame generated by Plotly's event_data. See the setup.R script for how this was derived.

	This module contains operations for working with radix trees. A radix tree
	is a data structure for efficient storage and lookup of values that often
	share prefixes, typically used with strings.

	A common question when I show this to people is: how do I add to the tree?
	delete? update? For these, grab the Range of the tree, use set logic to
	add/remove any elements, and construct a new tree with RadixTree.

	For educational purposes, I've heavily commented all the operations. I
	recommend using the constant expression evaluator to try the building blocks

	package org.deeplearning4j.examples.dataExamples;

	import org.datavec.api.io.labels.ParentPathLabelGenerator;
	import org.datavec.api.records.listener.impl.LogRecordListener;
	import org.datavec.api.split.FileSplit;
	import org.datavec.image.loader.NativeImageLoader;
	import org.datavec.image.recordreader.ImageRecordReader;
	import org.deeplearning4j.datasets.datavec.RecordReaderDataSetIterator;
	import org.deeplearning4j.eval.Evaluation;
	import org.deeplearning4j.nn.api.OptimizationAlgorithm;

	library(idbr)
	library(dplyr)
	library(ggplot2)
	library(tidyr)
	library(countrycode)
	library(gganimate)
	library(tweenr)

	ctrys <- countrycode(c('South Africa', 'Botswana', 'Lesotho', 'Namibia', 'Zimbabwe', 'Swaziland'),
	'country.name', 'fips104')

	apt-get -y update
	apt-get -y upgrade
	apt-get -y --force-yes install make unzip g++ libssl-dev git xvfb x11-xkb-utils xfonts-100dpi xfonts-75dpi xfonts-scalable xfonts-cyrillic x11-apps clang libdbus-1-dev libgtk2.0-dev libnotify-dev libgnome-keyring-dev libgconf2-dev libasound2-dev libcap-dev libcups2-dev libxtst-dev libxss1 libnss3-dev gcc-multilib g++-multilib

	npm -f init
	npm i -S nightmare

	xvfb-run nodejs index.js

	APOLLO 11 GUIDANCE COMPUTER: VERB AND NOUN LIST
	https://en.wikipedia.org/wiki/Apollo_Guidance_Computer#/media/File:Agc_verb-noun-list.jpg

	VERB LIST
	50 PLEASE PERFORM
	51 PLEASE MARK
	53 PLEASE MARK ALT LOG
	54 REND COAS MARK
	56 TERMINATE P20
	58 STICKFLAG (R) V50N18 FLAG(S)

	var request = require("require"); //request npm module
	var Scraper = function() {
	};

	Scraper.prototype.scrape = function(url, callback) {
	request(url, function responseCallback(error, response, html) {
	if(error) {
	callback(error);
	} else {
	console.log(html);