TRANSACTIONS AND CONCURRENCY CONTROL Sadhna Kumari

OUTLINE ACID Properties 2-Phase Commit Protocol TPS Serializability Concurrency Control Protocols Current Research Future References

ACID PROPERTIES Atomicity: A transaction is either performed entirely or not at all. Consistency: After execution of a transaction, the database must be in correct state. Isolation: Partial results of an incomplete transaction are not visible to others. Durability: The results of a committed transaction must be made permanent.

2-PHASE COMMIT PROTOCOL Participant - receives pre-commit message - if ready then pre-commits and replies YES else aborts transaction and replies NO - receives decision - if commit then COMMIT, if abort then ABORT - send response Coordinator - pre-commit the transaction - sends request to all participants - collects all replies - if all replies are YES then commit and send COMMIT else abort and send ABORT - receives response

DISTRIBUTED TRANSACTION PROCESSING SYSTEM

DISTRIBUTED TRANSACTION PROCESSING SYSTEM ( CONTD )

SERIALIZABILITY Serial Schedule: serial execution of actions of set of transactions Serializable schedule: Execution result is equivalent to that of serial schedule Conflicts: write-write, read-write or write-read Serializability ensures consistency

SERIALIZABILITY ( EXAMPLE ) Serial schedule : {t1,t2}, {t2,t1} t0 COMMITED Possible results {C,D} : {80,120}, {120,80} Operation pairs {1,3} & {2,4} – write-write conflict

INTERLEAVING SCHEDULES

TWO PHASE LOCKING Expanding phase: new locks on items can be acquired but none can be released Shrinking phase: existing locks can be released but no new ones can be acquired Problems:  Deadlock  Rolling aborts  Commit dependence Strict two phase locking: only release locks either at commit or at abort

TIMESTAMP ORDERING Each transaction has a Timestamp(TS) associated with it. TS is not necessarily real time, can be a logical counter TS is unique for a transaction New transaction has larger TS than older transaction Larger TS transactions wait for smaller TS transactions and smaller TS transactions die and restart when confronting larger TS transactions No deadlock

OPTIMISTIC CONCURRENCY CONTROL Allows entire transaction to complete and then validate the transaction before making its effect permanent Execution Phase: Starts with begin transaction and ends with end transaction Validation Phase: Coordinator TM with participant TMs validate the consistency using two-phase validation protocol Update Phase: Update must be committed for validated transaction

COMPARISON 2PL is the most popular choice because it is simple 2PL is a pessimistic protocol because it achieves serializability by restricting the operation in a transaction Timestamp ordering is less pessimistic, allows operations to execute freely Optimistic concurrency control ignores conflicts during execution, but requires very elaborate validation

C URRENT RESEARCH

DISTRIBUTED LOCK MANAGER [3]

DISTRIBUTED LOCK MANAGER (GFS) Locking responsibility is distributed Partitioning the lock space (can be done by using hash function ) Faster processing than centralized approach Avoid single point failure Deadlock detection is complicated

CONCURRENCY CONTROL IN REAL - TIME [4] Each transaction is associated with a priority, high priority transaction has earlier deadline Higher priority transaction obtains the lock first. Lower priority transaction has to sacrifice the lock. If transaction confronts the same priority transaction, then lock is obtained by timestamp ordering

F UTURE

Currently concurrency control mechanism are mostly at OS/Kernel level. With increasing parallel computing, user level locking mechanism should be made available Small locking object is ideal for concurrency control. It is always better to lock attribute than whole file Need for a standardized concurrency control protocol for distributed/parallel environment

REFERENCES [1] Distributed Operating Systems & Algorithms, Andy Chow & Theodore Johnson,1997 [2] [3] Sungchune Choi ; Minseuk Choi ; Chunkyeong Lee ; Hee Yong Youn ; “Distributed Lock Manager for Distributed File System in Shared-Disk Environment” Sep 2010Sungchune ChoiMinseuk ChoiChunkyeong Lee Hee Yong Youn [4] Qiansheng Zheng ; Xiaoming Bi ; “An improved concurrency control algorithm for distributed real-time database” Aug 2010Qiansheng ZhengXiaoming Bi [5]

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