In this course you will learn:
- Our system is decoupled as much as possible. We try to maintain accept and reject information on the client. On swiping left or right, the client can note the action and avoid showing the same user again, perhaps using bloom filters.
- The server has a validation engine called the matcher micro service, which notes matches and allows or disallows chat between two users.
- The final requirement of recommendations needs city wise partitioning on the user data. This is acheived using NoSQL databases like Cassandra or Amazon Dynamo. The other option is to use relational databases with horizontal partitioning. The concept is now refered to as sharding.