Hi ,
I am trying to store most of the data from tmdb locally an to check for updates using 'latest' method periodically. May I know the exact capacity me db should have to accommodate tmdb data ?
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Reply by Dale
on July 22, 2013 at 6:02 AM
I only have about a 1/4 of the data in MySql server and my database is up to about 300MB, It might be the way I am storing it. When you are storing it locally you might not be storing the data the same way as it is stored in TMDB server. What kind of data are you planning on storing locally.
Below is the tables I store:
age_group
film_name
collection_group
list_ of_genres
film_posters
list_ of_keywords
film_ to_collection
film_id
people_name
film_overview
production_company
user_rating
film_release_dates
film_trailer
If you would like some more information from how I do it please let me know.
p.s Some of the _ underscores are not working.
Dale.
Reply by NancyJe
on July 22, 2013 at 8:53 AM
I am creating a kind of social networking app ( in every mobile platform) that shares preference in film. thousands of users will be accessing server simultaneously. Since there is API request count restriction in tmdb I am trying to store almost every movie's overview, cast, posters of couple of dimensions,etc. I prefer using NoSQL db to store JSON response I get from tmdb , where as I am using MySQL to store profile info of users. It will be of great help if you could tel me the way you store it. I am trying to achieve low latency.
Thanks in advance.
Reply by Dale
on July 22, 2013 at 10:23 AM
Well I store all the requests I make from JSON directly into MySQL database. This way I have all my users details and Movie data stored into the same location.
Movie = 6.4 MiB (Has movie ID, title and IMDB ID) overview = 45.1 MiB (Has Movie ID and Overview text) cast = 81.2 MiB (Has Person ID, Name of Person, Poster of Person, Job role, List order and Character name) posters = 8.1 MiB (Has Movie ID, Backdrop link and Poster link)
Examples of each of these below for Movie ID 3
Movie: '3' , 'Varjoja paratiisissa' , 'tt0092149'
Overview: '3' , 'An episode in the life of Nikander, a garbage man,...'
Cast: '3' , '5999' , 'Kati Outinen' , '/cjcuhAXRcg8C0VIDHtfz1BIVE3m.jpg' , 'actor' , '1' , 'Ilona Rajamäki'
Poster: '3' , '/6YjUX87VtIEuDzanBE6obVxE9V3.jpg' , '/lfaiYUVL7vPE57xgTscJN3kN5P1.jpg'
Hope this helps.
Dale.
Reply by Travis Bell
on July 22, 2013 at 10:33 AM
Hi NancyJe,
I won't delve into specifics but here at TMDb we use MongoDB. Our movies and person collections (from a mongodumped BSON collection) are 630MB and 531MB respectively. Our entire DB is over 3.5GB but not everything is necessarily available via the API.
That should give you an idea anyways.
Reply by Dale
on July 22, 2013 at 10:37 AM
Travis would you say only half of the 3.5GB is available from the API?
Dale.
Reply by Travis Bell
on July 22, 2013 at 11:05 AM
Hi Dale,
That is really hard, almost impossible for me to say with any truth.
Reply by Dale
on July 22, 2013 at 11:10 AM
I understand. I was just interested, as I pulled a lot of the data to my local server to run new recommendation algorithms against the data from TMDB. Sorry I have hijacked NancyJe Thread.
Dale.
Reply by NancyJe
on July 22, 2013 at 1:26 PM
Thanks a lot Dale & Travis. That is a great detail.
Reply by harishmukkapati
on July 4, 2024 at 8:45 AM
@NancyJe @crazydc1 , were either of you able to manage to store the entire database? If so, what was the process