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However the local techniques have their limitations and use multi-processes (or threads) supported by multi-processors (or multi-cores) to scale. This often turns transactions into distributed ones, if they themselves need to span multi-processes. In these cases most local concurrency control techniques do not scale well.
Without concurrency control, if someone is reading from a database at the same time as someone else is writing to it, it is possible that the reader will see a half-written or inconsistent piece of data. For instance, when making a wire transfer between two bank accounts if a reader reads the balance at the bank when the money has been ...
Optimistic concurrency control (OCC), also known as optimistic locking, is a non-locking concurrency control method applied to transactional systems such as relational database management systems and software transactional memory. OCC assumes that multiple transactions can frequently complete without interfering with each other.
[6] Parallelism vs concurrency; Multi-threading and multi-processing (shared system resources) Synchronization (coordinating access to shared resources) Coordination (managing interactions between concurrent tasks) Concurrency Control (ensuring data consistency and integrity) Inter-process Communication (IPC, facilitating information exchange)
Distributed concurrency control poses special challenges beyond centralized one, primarily due to communication and computer latency. It often requires special techniques, like distributed lock manager over fast computer networks with low latency, like switched fabric (e.g., InfiniBand ).
Commitment ordering (CO) is a class of interoperable serializability techniques in concurrency control of databases, transaction processing, and related applications. It allows optimistic (non-blocking) implementations.
Each object in the database is given two timestamp fields which are not used other than for concurrency control: R T ( O j ) {\displaystyle RT(O_{j})} is the timestamp of the last transaction that read the value of the object ( T S ( T r ) {\displaystyle TS(T_{r})} , where T r {\displaystyle T_{r}} is the last transaction that read the value of ...
A schedule in which tasks execute one at a time (serially, no parallelism), without interleaving (sequentially, no concurrency: no task begins until the prior task ends) is called a serial schedule. A set of tasks that can be scheduled serially is serializable, which simplifies concurrency control. [citation needed]