LOG ANALYSIS

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Description of the project

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This project a part of Udacity Fullstack developer Nano Degree. This project is designed to provide a great SQL skills practice expereince by building a SQL reporting tool interacting with a database with over a million rows, both from the command line and from the code itself. Python programming language (python3) and postgresql are used for this particular project.

Prerequisites

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You must be familiar with the following before starting the project:

• Python
• PostgreSQL
• Vagagrant
• VirtualBox

How to start setting up the Project

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1. Install Python3
2. Install and Configure Vagrant and VirtualBox
3. Download or Clone the project from the github: https://github.com/udacity/fullstack-nanodegree-vm
4. Download and install newsdata.sql in our vagrant directory

How to run the project

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1. Change the directory to vagrant
2. Launch the virtual machine by following command $ vagrant up
3. Log into vitural machine by this command $ vagrant ssh
4. Change the directory to /vagrant
5. run the following command to load the data in local database psql -d news -f newsdata.sql
6. Use this command to see the database-> psql -d news
7. Database contains 3 tables (authors, articles, and log) and to explore each one, use the following commands: \dt (note: that will display a list of tables that the database contains) \d table(note: replace table with actual table name)
8. Use the below command to run the program python logs.py

Creating the view

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A view, a virtual table based on the result-set of a postgre sql statement, is created for this project. Create the view as follows.

Create view popular_articles_view as select title, author, count(*) as views from articles join log on log.path=CONCAT('/article/',articles.slug) group by articles.author, articles.title order by views DESC;