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Web application for recommending optimal places to put solar panels using gamification

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ISAC-Tokyo/WhereToPutSolarPanels

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WhereToPutSolarPanels

Members

  • Wataru Ohira (Lead)
  • Ryota Ayaki
  • Hiroki Matsue
  • Takashi Nishibayashi (github:haginon3000)
  • Eric Platon
  • Hajime Sasaki
  • Shun Shiramatsu (github:siramatu)
  • TAKANO Mitsuhiro a.k.a. takano32 (Lead Engineer / Big Data Administrator)

Deployment

Assuming Ubuntu 12_04

See also web_client/README.md for more detail on the client code

Package requirements

# As root
apt-get install build-essential libcurl4-openssl-dev apache2-prefork-dev apache2 nodejs git <必須なパケージを追加してください!>
\curl -L https://get.rvm.io | bash -s stable --ruby=1.9.3

If you want to install latest nodejs, see here: https://github.com/joyent/node/wiki/Installing-Node.js-via-package-manager#ubuntu-mint

Get the code the first time

cd /srv && \
git clone git://github.com/International-Space-Apps-Challenge-Tokyo/WhereToPutSolarPanels.git
# As needed
cd /srv/WhereToPutSolarPanels/web_server
BUNDLE_PATH=vendor/bundle bundle install && \
BUNDLE_PATH=vendor/bundle bundle exec passenger-install-apache2-module -a
cd /srv/WhereToPutSolarPanels/web_client
bower install

Get code updates (very primitive, but the way to date!)

cd /srv/WhereToPutSolarPanels
git checkout master && git pull
cd /srv/WhereToPutSolarPanels/web_server && BUNDLE_PATH=vendor/bundle bundle install
cd /srv/WhereToPutSolarPanels/web_client && bower install

Install virtual hosts

# As root
ln -s /srv/WhereToPutSolarPanels/etc/apache2/sites-available/wtps-api /etc/apache2/sites-available/wtps-api
ln -s /srv/WhereToPutSolarPanels/etc/apache2/sites-available/wtps-web /etc/apache2/sites-available/wtps-web
a2ensite wtps-web
a2ensite wtps-api

Start/Restart Apache

sudo apache2ctl start || sudo apache2ctl graceful

Softwares and Libraries

Servers

CommonSpec

  • Ubuntu 12.04 LTS 64bit
  • Disk 215GB (/ : 15GB, /mnt/work : 200GB)
  • Memory 8GB
  • CPU 1.7GHz * 2
  • SSH Port 22, Key Authentication only

SSH keys are shared in the private Facebook group.

Getting to the main server:

ssh root@210.129.195.213 -i ~/.ssh/id_rsa_wtps

Public Server (HTTP front end and Web API)

  • Global IP address: 210.129.195.213
  • Hostname: i-1603-29752-VM

Backend server "dai2"

  • Private IP address: 10.1.1.82
  • Hostname: i-1603-29759-VM

Backend server "dai3"

  • Private IP address: 10.1.2.94
  • Hostname: i-1603-29760-VM

SSH Config

SSH_CONFIG.rst

SetUp Workers

# apt-get update
# apt-get upgrade
# apt-get dist-upgrade
# fdisk /dev/sdb
# mkfs.ext4 /dev/sdb1
# blkid /dev/sdb1
# vi /etc/fstab
# reboot

at 210.129.195.213, foreach new worker's hostname.

# scp -i ~/.ssh/id_rsa_wtps{,} hostname:~/.ssh
# apt-get install git
# cd /mnt/work
# git clone https://github.com/International-Space-Apps-Challenge-Tokyo/WhereToPutSolarPanels.git

return to worker.

# apt-get install python-h5py python-pymongo

let's get started to insert data!

Data Management

Convert HDF4 to HDF5

install hdf5-tools

apt-get install hdf5-tools

use h4toh5.

Insert Data from HDF5

insert_cloud_mask.py using h5py and pymongo.

$ sudo apt-get install python-h5py python-pymongo

usage

$ insert_cloud_mask.py [shard_index] [shard_num] [HDF5 File Name]

multiple file insert.

ex. from 2000-01-01 to 2000-12-31 data.

$ echo MOD35_L2.A200[0]*.h5 | xargs -n1 insert_cloud_mask.py [shard_index] [shard_num]

ex. from 2001-01-01 to 2012-12-31 data w/ concurrency 4.

$ echo MOD35_L2.A200[12]/*.h5 | xargs -P4 -n1 ./WhereToPutSolarPanels/insert_cloud_mask.py 0 12
$ echo MOD35_L2.A200[34]/*.h5 | xargs -P4 -n1 ./WhereToPutSolarPanels/insert_cloud_mask.py 0 12
$ echo MOD35_L2.A200[56]/*.h5 | xargs -P4 -n1 ./WhereToPutSolarPanels/insert_cloud_mask.py 0 12
$ echo MOD35_L2.A200[78]/*.h5 | xargs -P4 -n1 ./WhereToPutSolarPanels/insert_cloud_mask.py 0 12
$ echo MOD35_L2.A20[01][09]/*.h5 | xargs -P4 -n1 ./WhereToPutSolarPanels/insert_cloud_mask.py 0 12
$ echo MOD35_L2.A201[12]/*.h5 | xargs -P4 -n1 ./WhereToPutSolarPanels/insert_cloud_mask.py 0 12

ex. and batch insert.

$  i in `seq 0 11`; do echo MOD35_L2.A200[12]/*.h5 | xargs -P4 -n1 ./WhereToPutSolarPanels/insert_cloud_mask.py $i 12; done
$  i in `seq 0 11`; do echo MOD35_L2.A200[34]/*.h5 | xargs -P4 -n1 ./WhereToPutSolarPanels/insert_cloud_mask.py $i 12; done
$  i in `seq 0 11`; do echo MOD35_L2.A200[56]/*.h5 | xargs -P4 -n1 ./WhereToPutSolarPanels/insert_cloud_mask.py $i 12; done
$  i in `seq 0 11`; do echo MOD35_L2.A200[78]/*.h5 | xargs -P4 -n1 ./WhereToPutSolarPanels/insert_cloud_mask.py $i 12; done
$  i in `seq 0 11`; do echo MOD35_L2.A200[01][09]/*.h5 | xargs -P4 -n1 ./WhereToPutSolarPanels/insert_cloud_mask.py $i 12; done
$  i in `seq 0 11`; do echo MOD35_L2.A201[12]/*.h5 | xargs -P4 -n1 ./WhereToPutSolarPanels/insert_cloud_mask.py $i 12; done

Mongo DB

Create Geo Index

> db.cloud_mask.ensureIndex({loc: '2d'})

Count

> db.cloud_mask.count({query: {
    lat: {$gt: 35, $lt: 35.001},
    lon: {$gt: 134, $lt: 134.001}
    }})

Map Reduce

> var _m = function() {
  emit(this._id, {score: this.score});
};
> var _r = function(key, values) {
  var result = {count: 0, score: 0};
  values.forEach(function(value){
    result.count++;
    result.score += value.score;
  });
  return result;
};
> db.cloud_mask.mapReduce(_m, _r,
  {out: {inline: 1},
    query: {
      lat: {$gt: 35, $lt: 35.01},
      lon: {$gt: 134, $lt: 134.01}
      }})

Server API

  • GET /api/v1/rank
  • Request Parameters
    • lat: latitude
    • lan: longitude
  • Response
    • Content-Type:application/json
{
  rank: 5,
  total_score: 3600, // Total over 10 years
  series: {
    from: "2000-01",
    to: "2010-12",
    data: [100, 105, 100, 30] // Number of sunny days each month over 10 years.
  }
}
  • Example
http://xxxxx.com/api/v1/rank?lat=35.666666&lan=135.333333333
  • GET /api/v1/rank/range
  • Request Parameters
    • type1
      • lat_s: latitude start of range
      • lat_e: latitude end of range
      • lon_s: longitude start of range
      • lon_e: longitude end of range
    • type2
      • lat_r: latitude range
      • lon_r: longitude range
  • Response: Array of 400 data points (lat, lon, rank), where the rank is the number of sunny days on average at that position.
-------
|1|2|3|
-------
|4|5|6|
-------
  • Content-Type:application/json
[
  {
  "lat": 32.123,
  "lon": 139.123,
  "weight": 123
  },
  ...
  {
  "lat": 38.123,
  "lon": 142.123,
  "weight": 321
  },
]

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