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Optimistic concurrency control transactions involve these phases: [2] Begin: Record a timestamp marking the transaction's beginning. Modify: Read database values, and tentatively write changes. Validate: Check whether other transactions have modified data that this transaction has used (read or written). This includes transactions that ...
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 ...
In Computer Science, in the field of databases, non-lock concurrency control is a concurrency control method used in relational databases without using locking. There are several non-lock concurrency control methods, which involve the use of timestamps on transaction to determine transaction priority: Optimistic concurrency control
Transactional memory provides optimistic concurrency control by allowing threads to run in parallel with minimal interference. [2] The goal of transactional memory systems is to transparently support regions of code marked as transactions by enforcing atomicity , consistency and isolation .
The objective is to provide more concurrency if extra resources are available. This approach is employed in a variety of areas, including branch prediction in pipelined processors, value prediction for exploiting value locality, prefetching memory and files, and optimistic concurrency control in database systems. [1] [2] [3]
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.
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They also provide global serializability without local concurrency control information distribution, can be combined with any relevant concurrency control, and allow optimistic (non-blocking) implementations. Both use additional information for relaxing CO constraints and achieving better concurrency and performance.