CIS 720 Concurrency Control

Locking Atomic statement Th1: …. < x = x + 1; y = z>;……. Can be used to perform two or more updates atomically Th1: …. < x = x + 1; y = z>;……. Th2:………….<m = m + 1;….>;…….

Transactions A database system is a set of shared data objects A transaction is a sequential program which accesses data objects in the database Each transaction is a sequence of read and write operations

The Transaction Model Examples of primitives for transactions. Description BEGIN_TRANSACTION Make the start of a transaction END_TRANSACTION Terminate the transaction and try to commit ABORT_TRANSACTION Kill the transaction and restore the old values READ Read data from a file, a table, or otherwise WRITE Write data to a file, a table, or otherwise

Transactions Each transaction is a sequence of read and write operations The read set of transaction T, denoted by rs(t), is a set of variables read by T. The write set ws(T) is defined similarly

Banking System } } Deposit(amount, account) Withdraw(amount, account) { x = db.account; x = x + amount; db.account = x; } Withdraw(amount, account) { y = db.account; if y > amount y = y - amount; db.account = y; }

Distributed Transactions BEGIN_TRANSACTION reserve MCI -> JFK; reserve JFK -> FRK; END_TRANSACTION

Distributed Transactions A nested transaction A distributed transaction

A database has an invariant I (integrity constraint). Each transaction is designed to preserve I If transactions are executed simultaneously, then they may interfere and invalidate I. The task of concurrency control is to preserve I.

Banking System } Transaction 1: Deposit $50 in Acc1 Possible interleavings T1.x = db.Acc1; T1.x = T1.x + 50 T2.x = db.Acc1; T2.x = T2.x + 70; db.Acc1 = T1.x db.Acc1 = T2.x Deposit(amount, account) { x = db.account; x = x + amount; db.account = x; }

Concurrency Control General organization of managers for handling transactions.

Concurrency Control General organization of managers for handling distributed transactions.

A schedule is any execution of a set of transaction operations Two schedules T1 and T2 are equivalent if - all read operations return the same value in both schedules - the final database state is the same in both schedules

T1: r1(x)0 w1(x)1 T2: r2(y)0 r2(x)1 w2(y)2 T1: r1(x)0 w1(x)1 T2: r2(y)0 r2(x)1 w2(y)2 T1: r1(x)0 w1(x)1 T2: r2(y)0 r2(x)1 w2(y)2

T1: r1(y)1 w1(x)1 T2: w2(y)1 r2(x)1 w2(y)2 T1: r1(y)0 w1(x)1 T2: w2(y)1 r2(x)1 w2(y)2 T1: r1(y)0 w1(x)1 T2: w2(y)1 r2(x)0 w2(y)2

A serial schedule is a schedule in which transactions execute one at a time. We know that a serial schedule preserves IC of the database A concurrency control algorithm can restricts the execution so that all schedules are serial.

A CC ensures that all schedules are equivalent to some serial schedule A schedule that is equivalent to a serial schedule is called serializable

Untyped Concurrency control Assumes that all transactions with intersecting read and write sets interfere with one another. How can we determine whether a schedule is serializable Let T1,…,Tn be a set of transactions Define a graph G with transactions as nodes There is an edge from Ti to Tj if - there exists a read rj(x) which reads from wi(x) - there exists a read ri(x) that occurs before wj(x) - there exists a write wi(x) that occurs before wj(x)

A graph is serializable if the graph is acyclic

Two-phase Locking Obtain a read or write lock before reading or writing a variable respectively. rl(x): read lock operation ul(x): unlock operation wl(x): write lock operation

Locking rules: - two read locks can be given at the same time; read and write lock must be exclusive * conflict table

Simple locking does not ensure serializability

T1: r1(y)1 w1(x)1 T2: w2(y)1 r2(x)1 w2(y)2 T1: r1(y)0 w1(x)1 T2: w2(y)1 r2(x)1 w2(y)2 T1: r1(y)0 w1(x)1 T2: w2(y)1 r2(x)0 w2(y)2

T1: L(y) r1(y)1 ul(y) L(x( w1(x)1 ul(x) T2: L(x)w2(y)1 UL(x) L(x) r2(x)1 ul(x) w2(y)2

Two phase locking rule Locking phase: acquire all locks Unlocking phase: release all locks Two-phase locking ensures serializability It is prone to deadlocks

Two-Phase Locking (1) Two-phase locking.

Two-Phase Locking (2) Strict two-phase locking.

Writeahead Log a) A transaction x = 0; y = 0; BEGIN_TRANSACTION; x = x + 1; y = y + 2 x = y * y; END_TRANSACTION; (a) Log [x = 0 / 1] (b) [y = 0/2] (c) [x = 1/4] (d) a) A transaction b) – d) The log before each statement is executed

Graph based protocols Impose a partial ordering  on data items If d1  d2, then any transaction accessing both d1 and d2 must first access d1 before d2.

Tree protocol Only exclusive locks are allowed First item to be locked can be any one Next, a data item can be locked only if the parent is already locked Data items can be unlocked at any time A data item cannot be relocked by a transaction.

Semantics-based concurrency control If transactions T1 and T2 do not interfere then they can be executed concurrently. Two operations op1 and op2 do not conflict if they commute (that is, op1; op2 is the same as op2; op1)

Predicate Locking Each transaction specifies a predicate as a lock. A new transaction can execute if it does not interfere with existing predicate locks