mburakergenc / twitter-analysis

Part I

1. The sql query below retreives the current user information

   SELECT t1.user_id, t1.name, t1.email
   
   from user_changes AS t1
   
   LEFT  OUTER  JOIN user_changes AS t2
   
   ON t1.user_id = t2.user_id
   
   AND(t1.created < t2.created
   
   OR (t1.created = t2.created AND t1.user_id < t2.user_id))
   
   WHERE t2.email is  NULL
   

2. Find the median time between the second and third profile edit.

   with edit_diff as
   (
     select timestampdiff(hour, min(created), max(created)) difference
     from
     (
       select *,
         row_number() over (partition by user_id order by created) rn
       from users_changes
     ) T
     where rn in(2,3)
     group by user_id
   )
   
   select round(avg(difference), 2) median
   from
   (
     select difference,
            row_number() over (order by difference) diffOrder,
           count(*) over () cn
     from edit_diff
   ) T
   where diffOrder between floor((cn + 1) / 2) and ceil((cn + 1) / 2);
   

Part II

How to run the application

• Have Docker installed on your system
• If you don't have docker installed, you can run the src/assignment/handler.py file after filling the src/assignment/credentials.py file with your credentials.
• Run the command below to pull the docker image;
  • docker pull mburakergenc/kahootassignment
• Run the command below to run the container;
  • docker run -ti mburakergenc/kahootassignment
• Enter a search term when requested by the application such as "Donald"
• Please try to select a high volume keyword to see all the details analysis. You'll get warnings printed when the keyword doesn't have any tweets within the last 1, 5, 60 minutes.
• Results are limited to 500 tweets for performance reasons. It should take a few seconds for 500 tweets to be loaded from Twitter.

How to run the tests

• cd into the project directory
  • cd twitter-analysis
• py.test