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Distributed deadlocks can be detected either by constructing a global wait-for graph, from local wait-for graphs at a deadlock detector or by a distributed algorithm like edge chasing. Phantom deadlocks are deadlocks that are detected in a distributed system due to system internal delays but no longer actually exist at the time of detection.
In a SQL database, a record is typically called a "row". The introduction of granular (subset) locks creates the possibility for a situation called deadlock. Deadlock is possible when incremental locking (locking one entity, then locking one or more additional entities) is used. To illustrate, if two bank customers asked two clerks to obtain ...
An alternate to locking for database synchronicity while avoiding deadlocks involves the use of totally ordered global timestamps. There are mechanisms employed to manage the actions of multiple concurrent users on a database—the purpose is to prevent lost updates and dirty reads.
Detecting a deadlock that has already occurred is easily possible since the resources that each process has locked and/or currently requested are known to the resource scheduler of the operating system. [13] After a deadlock is detected, it can be corrected by using one of the following methods: [citation needed]
Banker's algorithm is a resource allocation and deadlock avoidance algorithm developed by Edsger Dijkstra that tests for safety by simulating the allocation of predetermined maximum possible amounts of all resources, and then makes an "s-state" check to test for possible deadlock conditions for all other pending activities, before deciding whether allocation should be allowed to continue.
A wait-for graph in computer science is a directed graph used for deadlock detection in operating systems and relational database systems.. In computer science, a system that allows concurrent operation of multiple processes and locking of resources and which does not provide mechanisms to avoid or prevent deadlock must support a mechanism to detect deadlocks and an algorithm for recovering ...
In databases and transaction processing, two-phase locking (2PL) is a pessimistic concurrency control method that guarantees conflict-serializability. [1] [2] It is also the name of the resulting set of database transaction schedules (histories).
This, in turn, leads to the possibility of conflicting inserts into those files, leading to an inconsistent database state. To prevent this, some ISAM implementations [5] [6] provide whole-file or individual record locking functionality. Locking multiple records runs the risk of deadlock unless a deadlock prevention scheme is