In computer science, a consistency model specifies a contract between the programmer and a system, wherein the system guarantees that if the programmer follows the rules for operations on memory, memory will be consistent and the results of reading, writing, or updating memory will be predictable. Consistency models are used in distributed systems like distributed shared memory systems or distributed data stores (such as s, databases, optimistic replication systems or web caching). Consistency is different from coherence, which occurs in systems that are cached or cache-less, and is consistency of data with respect to all processors. Coherence deals with maintaining a global order in which writes to a single location or single variable are seen by all processors. Consistency deals with the ordering of operations to multiple locations with respect to all processors.
High level languages, such as C++ and Java, maintain the consistency contract by translating memory operations into low-level operations in a way that preserves memory semantics, reordering some memory instructions, and encapsulating required synchronization with library calls such as pthread_mutex_lock().
Assume that the following case occurs:
The row X is replicated on nodes M and N
The client A writes row X to node M
After a period of time t, client B reads row X from node N
The consistency model determines whether client B will definitely see the write performed by client A, will definitely not, or cannot depend on seeing the write.
Consistency models define rules for the apparent order and visibility of updates, and are on a continuum with tradeoffs. There are two methods to define and categorize consistency models; issue and view.
Issue Issue method describes the restrictions that define how a process can issue operations.
View View method which defines the order of operations visible to processes.
For example, a consistency model can define that a process is not allowed to issue an operation until all previously issued operations are completed.
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