#TINYURL SYSTEM DESIGN JAVA UPDATE#
#TINYURL SYSTEM DESIGN JAVA CODE#

There exist possibilities of data inconsistencies here because there are different machines for handling different requests which might result in data being out of sync.Īs there is only one machine, there is no issue of data inconsistency.

Vertical scaling makes use of inter-process communication within the machine which makes it quite fast. Since there are multiple machines being involved, it is very much necessary to have network communication. This is more prone to failure as there is only one machine and failure of this results in failure of the entire application. This is more resistant to application failure because if one server fails, traffic is routed to other servers. Since there is just one single machine, the load balancer is not required. Requires load balancing for distributing request traffic across multiple machines. This has been demonstrated in the image below:

#TINYURL SYSTEM DESIGN JAVA CODE#

The capability of the server can be enhanced without the need for code manipulation. Vertical scaling refers to the concept of upgrading the resource capacity such as increasing RAM, adding efficient processors etc of a single machine or switching to a new machine with more capacity.

In simple words, more instances of servers are added to the existing pool and the traffic load is distributed across these devices in an efficient manner.

Horizontal scaling refers to the addition of more computing machines to the network that shares the processing and memory workload across a distributed network of devices.How is Horizontal scaling different from Vertical scaling? Cassandra, CouchDB guarantees Availability and Partition Tolerance. Redis, MongoDB, Hbase databases guarantee Consistency and Partition Tolerance. We see that RDBMS databases guarantee consistency and Availability simultaneously. The following image represents what databases guarantee what aspects of the CAP Theorem simultaneously. Partition Tolerance: The database system should be functioning despite the communication becoming unstable.Availability: The databases cannot have downtime and should be available and responsive always.For example, post database updation, all queries should retrieve the same result. Consistency: This states that the data has to remain consistent after the execution of an operation in the database.Let us understand this with the help of a distributed database system. It can at max provide any 2 of the 3 guarantees. What is CAP theorem?ĬAP(Consistency-Availability-Partition Tolerance) theorem says that a distributed system cannot guarantee C, A and P simultaneously. System Design Interview Questions for Freshers 1. Design Uber, Ola or Lyft type of systems. Design a type-ahead search engine service. How do you design global file storage and file sharing services like Google Drive, Dropbox etc? Design an API Rate Limiter system for GitHub or Firebase sites. How do you design a recommendation system? Design a forum-like systems like Quora, Reddit or HackerNews. How do you design a URL shortening service like TinyURL or bit.ly? Design a global chat service like Whatsapp or a facebook messenger. System Design Interview Questions for Experienced What are some of the design issues in distributed systems? How do you answer system design interview questions? What do you understand by Leader Election? What do you understand by Content delivery network? What are the various Consistency patterns available in system design?

#TINYURL SYSTEM DESIGN JAVA UPDATE#

What is Caching? What are the various cache update strategies available in caching? How is performance and scalability related to each other? How is sharding different from partitioning? How is NoSQL database different from SQL databases? What do you understand by Latency, throughput, and availability of a system?

What do you understand by load balancing? Why is it important in system design? System Design Interview Questions for Freshers

Tinyurl system design java