Table of contents [ hide ] Basic theory CAP States that any distributed data store can provide only two of the following three guarantees. Consistency Every read receives the most recent write or an error. Availability Every request receives a (non-error) response, without the guarantee that it contains the most recent write. Partition tolerance The system continues to operate despite an arbitrary number of messages being dropped (or delayed) by the network between nodes. Typical architecture of distributed systems When a network partition failure happens, it must be decided whether to do one of the following: CP: cancel the operation and thus decrease the availability but ensure consistency AP: proceed with the operation and thus provide availability but risk inconsistency. BASE Basically-available, soft-state, eventual consistency. Base theory is the practical application of CAP theory, that is, under the premise of the existence of partitions and copies, through certain syste
Table of contents [ hide ] Glossary Synchronous: When you start a program, you must wait until it finishes before moving on to the next step. Asynchronous: When you start a program, it returns immediately and runs the program in the background, and you can move on to the next step. Concurrency: Concurrency is the ability of different parts or units of a program, algorithm, or problem to be executed out-of-order or in the partial order, without affecting the final outcome Parallelism: Parallel computing is a type of computation in which many calculations or processes are carried out simultaneously. Blocking: A process that is blocked is one that is waiting for some event, such as a resource becoming available or the completion of an I/O operation Non-blocking: An algorithm is called non-blocking if the failure or suspension of any thread cannot cause the failure or suspension of another thread Concurrency level Blocking: A thread is blocked and it cannot execute until other threa