From our previous experiences with implementing causality tracking and conflict resolution in CRDTs, we can now draw some implications for application design.
Imagine being a lead engineer for a global streaming giant like Netflix or YouTube. In such platforms, if a user in the US adds a new movie to their favorites list, this information should be reflected across all replicated databases worldwide. This update should also be reflected in real-time for another user who is accessing the same account from a different location - let's say, a family member on vacation in France! Equally, the design needs to account for two family members, in different locations, adding different movies to the favorite list at the same time. We wouldn't want one update to overwrite the other, causing a loss of data.
As such, the design of the application needs to allow for real-time data replication, conflict-free updates, and data consistency - a perfect scenario for CRDTs.
In the code we've included here, we have simulated a server node in a movie-streaming platform. The server node uses a CRDT to manage movie information and user actions. We replicate a movie addition across the system and apply a user update. In a real-world scenario, there would be many more server nodes and updates happening concurrently; however, this simplified example gives us an understanding of how CRDTs play a vital role in the application design of distributed systems.
xxxxxxxxxxif __name__ == '__main__': # This is a simplified simulation of a server node in our distributed system. # Let's assume for our example we'reA dealing with a global online movie streaming platform. server_node = CRDT() # Let's replicate a new movie addition across the system movie_info = {'title': 'Inception', 'director': 'Christopher Nolan', 'year': 2010} server_node.add_movie(movie_info) # Now let's assume a user update - a user adding this movie to their favorites user_action = ('add_to_favorites', 'Inception') server_node.apply_user_update(user_action) # Now let's print the state of the node to inspect how our operations affected it print(server_node.get_state())