yauri-io

#!/bin/sh
#
# NGINX Amplify Agent install script
#
# Copyright (C) Nginx, Inc.
#

# Edited using reference in https://github.com/nginxinc/nginx-amplify-agent/issues/181

packages_url="https://packages.amplify.nginx.com"

yauri-io

# custom IntelliJ IDEA properties

editor.zero.latency.typing=true
idea.max.intellisense.filesize=3500
idea.cycle.buffer.size=2048

yauri-io

-Xms1024m
-Xmx3072m
-Xss64m
-XX:ReservedCodeCacheSize=512m
-XX:+UseCompressedOops
-XX:NewRatio=2
-Dfile.encoding=UTF-8
-XX:+UseConcMarkSweepGC
-XX:SoftRefLRUPolicyMSPerMB=250
-XX:NewSize=512m

yauri-io

[
   {
      "districts":[
         {
            "zip":"100",
            "name":"中正區"
         },
         {
            "zip":"103",
            "name":"大同區"

yauri-io

Moved to git repository: https://github.com/denji/nginx-tuning

NGINX Tuning For Best Performance

For this configuration you can use web server you like, i decided, because i work mostly with it to use nginx.

Generally, properly configured nginx can handle up to 400K to 500K requests per second (clustered), most what i saw is 50K to 80K (non-clustered) requests per second and 30% CPU load, course, this was 2 x Intel Xeon with HyperThreading enabled, but it can work without problem on slower machines.

You must understand that this config is used in testing environment and not in production so you will need to find a way to implement most of those features best possible for your servers.

yauri-io

'use strict'

const Fs = require('fs')
const Path = require('path')
const filePath = process.env.filePath

if (!filePath) {
	throw Error ('Please set filePath!')
}

yauri-io

[
    {
        "timezones": [
            "America/Aruba"
        ], 
        "latlng": [
            12.5, 
            -69.96666666
        ], 
        "name": "Aruba", 

yauri-io

Movies Recommendation:

• MovieLens - Movie Recommendation Data Sets http://www.grouplens.org/node/73
• Yahoo! - Movie, Music, and Images Ratings Data Sets http://webscope.sandbox.yahoo.com/catalog.php?datatype=r
• Jester - Movie Ratings Data Sets (Collaborative Filtering Dataset) http://www.ieor.berkeley.edu/~goldberg/jester-data/
• Cornell University - Movie-review data for use in sentiment-analysis experiments http://www.cs.cornell.edu/people/pabo/movie-review-data/

Music Recommendation:

• Last.fm - Music Recommendation Data Sets http://www.dtic.upf.edu/~ocelma/MusicRecommendationDataset/index.html