yoongkang0122

#Steps to install latest Laravel, LEMP on AWS Ubuntu 16.4 version. This tutorial is the improvised verision of this tutorial on Digitalocean based on my experience.

Install PHP 7 on Ubuntu

Run the following commands in sequence.

sudo apt-get install -y language-pack-en-base
sudo LC_ALL=en_US.UTF-8 add-apt-repository ppa:ondrej/php
sudo apt-get update
sudo apt-get install zip unzip

Installation

Installation instructions are basically notes that I took while installing openface on MacOSX El Capitan.

System packages

brew install bash coreutils curl findutils opencv
brew install python --framework --universal --with-brewed-openssl
brew install boost-python --universal

	:'Problem 1
	#Connect to the MySQL database on the itversity labs using sqoop and import all of the data from the orders table into HDFS
	Output Requirements
	#Place the customer files in the HDFS directory
	#/user/yourusername/problem1/solution/
	#Replace yourusername with your OS user name
	#Use a text format with comma as the columnar delimiter
	#Load every order record completely'

	sqoop import \

	"""
	A DAG docstring might be a good way to explain at a high level
	what problem space the DAG is looking at.
	Links to design documents, upstream dependencies etc
	are highly recommended.
	"""
	from datetime import datetime, timedelta
	from airflow.models import DAG # Import the DAG class
	from airflow.operators.sensors import NamedHivePartitionSensor
	from airflow.operators.hive_operator import HiveOperator

	# http://stackoverflow.com/questions/1388025/how-to-get-id-of-the-last-updated-row-in-mysql

	# single row update
	SET @update_id := 0;
	UPDATE some_table SET column_name = 'value', id = (SELECT @update_id := id)
	WHERE some_other_column = 'blah' LIMIT 1;
	SELECT @update_id;

	# Multiple rows updated
	SET @uids := null;

	import pandas as pd
	import pymysql
	from sqlalchemy import create_engine

	engine = create_engine("mysql+pymysql://USER:PASSWORD@HOST:PORT/DBNAME")

	df = pd.read_sql_query("SELECT * FROM table", engine)
	df.head()

	import tensorflow as tf
	import numpy as np
	import os

	import zconfig
	import utils


	class RBM(object):

	'''
	Extract Features from a pre-trained caffe CNN Layer
	based on https://github.com/karpathy/neuraltalk/blob/master/python_features/extract_features.py
	'''
	import sys
	import os.path
	import argparse

	import numpy as np
	from scipy.misc import imread, imresize

	/**
	*
	* In this example we create view with inplace and bulk editing.
	* Tools and plugins:
	* jQuery
	* xEditable jquery plugin
	* twitter bootstrap
	*
	*/

	#!/bin/bash

	USAGE="$0 [-u <user> -p <password> -h <host> -P <PORT> -d <database> -D <destination/directory/without/trailing/slash>]"
	DESTINATION=`pwd`
	USER=root
	PASS=root
	HOST=localhost
	PORT=3306

	# SPECIFY HOW LONG TO RETAIN BACKUPS