In this project, a large database with over a million rows is explored by building complex SQL queries to draw business conclusions for the data.

Install Vagrant And VirtualBox Clone this repository

Launch Vagrant VM by running vagrant up, you can the log in with vagrant ssh To load the data, use the command psql -d news -f newsdata.sql to connect a database and run the necessary SQL statements. To execute the program, run python3 newsdata.py from the command line.

CREATE VIEW dailyErrors AS SELECT daily_log.date, round(daily_error.error_request * 100.0 / daily_log.total_request, 2) AS error_log FROM ( select time::date AS date, count(*) AS total_request FROM log GROUP BY date ) AS daily_log join ( select time::date as date, count(*) as error_request from log where status != '200 OK' group by date ) as daily_error on daily_log.date = daily_error.date;

Resources/help have been used in this project including Udacity FSND Nanodegree Program and also the Udacity FSND Program's Forum.