Concurrency Control

 Concurrency Control 

•  Lock-Based Protocols 
•  Timestamp-Based Protocols 
•  Validation-Based Protocols 
•  Multiple Granularity 
•  Multiversion Schemes 
•  Deadlock Handling 
•  Insert and Delete Operations 
•  Concurrency in Index Structures

Lock-Based Protocols 

• A lock is a mechanism to control concurrent access to a data item 

• Data items can be locked in two modes : 

1. exclusive (X) mode. Data items can be both read as well as written. X-lock is requested using lock-X instruction. 

2. shared (S) mode. Data items can only be read. S-lock is requested using lock-S instruction. 

• Lock requests are made to concurrency-control manager. Transaction can proceed only after a             request is granted.

Lock-Based Protocols 

• Lock-compatibility matrix

• A transaction may be granted a lock on an item if the requested lock is compatible with locks already held on the item by other transactions 
• The matrix allows any number of transactions to hold shared locks on an item, but if any transaction holds an exclusive on the item no other transaction may hold any lock on the item. 
• If a lock cannot be granted, the requesting transaction is made to wait till all incompatible locks held by other transactions have been released. The lock is then granted.

Lock-Based Protocols 

• Example of a transaction performing locking:

•  Locking as above is not sufficient to guarantee serializability — if A and B get updated in-between the read of A and B, the displayed sum would be wrong. 
•  A locking protocol is a set of rules followed by all transactions while requesting and releasing locks. Locking protocols restrict the set of possible schedules.

Pitfalls of Lock-Based Protocols

• Consider the partial schedule

• Neither T3 nor T4 can make progress — executing lock-S(B) causes T4 to wait for T3 to release its lock on B, while executing lock-X(A) causes T3 to wait for T4 to release its lock on A. 
•  Such a situation is called a deadlock. To handle a deadlock one of T3 or T4 must be rolled back and its locks released. 

Pitfalls of Lock-Based Protocols 

•  The potential for deadlock exists in most locking protocols. Deadlocks are a necessary evil.
•  Starvation is also possible if a concurrency control manager is badly designed. For example: – A transaction may be waiting for an X-lock on an item, while a sequence of other transactions request and are granted an S-lock on the same item. – The same transaction is repeatedly rolled back due to deadlocks. 
•  Concurrency control manager can be designed to prevent starvation.

The Two-Phase Locking Protocol

•  This is a protocol which ensures conflict-serializable schedules. 
•  Phase 1: Growing Phase:

             – transaction may obtain locks
             – transaction may not release locks

•  Phase 2: Shrinking Phase:

                – transaction may release locks
                – transaction may not obtain locks

•  The protocol assures serializability. It can be proved that the transactions can be serialized in the order of their lock points (i.e. the point where a transaction acquired its final lock).

The Two-Phase Locking Protocol 

•  Two-phase locking does not ensure freedom from deadlocks 
•  Cascading roll-back is possible under two-phase locking. To avoid this, follow a modified protocol called strict two-phase locking. Here a transaction must hold all its exclusive locks till it commits/aborts. 
•  Rigorous two-phase locking is even stricter: here all locks are held till commit/abort. In this protocol, transactions can be serialized in the order in which they commit.
•  There can be conflict serializable schedules that cannot be obtained if two-phase locking is used. 
•  However, in the absence of extra information(e.g., ordering of access to data),two-phaselockingisneededforconflict serializability in the following sense:
• Givenatransaction Ti
• that does not follow two-phase locking,wecanfindatransaction Tj that uses two-phase locking, and a schedule for Ti and Tj thatisnotconflict serializable.

LockConversions

Two-phase locking with lock conversions:

– First Phase:

can acquire a lock-S on item

can acquire a lock-X on item

can convert a lock-S to a lock-X (upgrade)

– Second Phase:

can release a lock-S

can release a lock-X

can convert a lock-X to a lock-S (downgrade)

This protocol assures serializability. But still relies on the

programmer to insert the various locking instructions.

Automatic Acquisition of Locks

A transaction Ti issues the standard read/write instruction, without explicit locking calls.

The operation read(D) is processed as:

           if Ti has a lock on D

                    then

                       read(D)

                             else

                           begin

                        if necessary wait until no other

               transaction has a lock-X on D

               grant Ti a lock-S on D;

                  read(D)

                   end;

Automatic Acquisition of Locks 

write(D) is processed as:

        if Ti has a lock-X on D

           then

             write(D)

          else

            begin

               if necessary wait until no other trans. has any lock on D,

                if Ti has a lock-S on D

              then

            upgrade lock on D to lock-X

             else

               grant Ti a lock-X on D

             write(D)

           end;

All locks are released after commit or abort

Graph-Based Protocols

Is an alternative to two-phase locking

Impose a partial ordering ! on the set D = fd1, d2, ..., dhg

     of all data items.

– If di !dj , then any transaction accessing both di and dj

       must access di before accessing dj .

– Implies that the set D may now be viewed as a directed

       acyclic graph, called a database graph.

tree-protocol is a simple kind of graph protocol.

Tree Protocol

Only exclusive locks are allowed.

The first lock by Ti may be on any data item. Subsequently, a

      data item Q can be locked by Ti only if the parent of Q is currently locked by Ti .

Data items may be unlocked at any time.

A data item that has been locked and unlocked by Ti cannot

       subsequently, be re-locked by Ti .

Graph-Based Protocols 

The tree protocol ensures conflict serializability as well as

freedom from deadlock.

Unlocking may occur earlier in the tree-locking protocol than in

the two-phase locking protocol.

– shorter waiting times, and increase in concurrency

– protocol is deadlock-free

However,in the tree-locking protocol, a transaction may have to

lock data items that it does not access.

– increased locking overhead, and additional waiting time

– potential decrease in concurrency

schedules not possible under two-phase locking are possible

under tree protocol, and vice versa.

Timestamp-Based Protocols

Each transaction is issued a timestamp when it enters the

    system. If an old transaction Ti has time-stamp TS(Ti), a new

    transaction Tj is assigned time-stamp TS(Tj ) such that

    TS(Ti ) <TS(Tj ).

The protocol manages concurrent execution such that the

    time-stamps determine the serializability order.

In order to assure such behavior, the protocol maintains for

   each data item Q two timestamp values:

– W-timestamp(Q) is the largest time-stamp of any

transaction that executed write(Q) successfully.

– R-timestamp(Q) is the largest time-stamp of any

transaction that executed read(Q) successfully.

Timestamp-Based Protocols 

The timestamp ordering protocol ensures that any conflicting

read and write operations are executed in timestamp order.

Suppose a transaction Ti issues a read(Q)

1. If TS(Ti ) < W-timestamp(Q), then Ti needs to read a value

   of Q that was already overwritten. Hence, the read

   operation is rejected, and Ti is rolled back.

2. If TS(Ti ) W-timestamp(Q), then the read operation is

    executed, and R-timestamp(Q) is set to the maximum of

    R-timestamp(Q) and TS(Ti ).

Correctness of Timestamp-Ordering Protocol

The timestamp-ordering protocol guarantees serializability

since all the arcs in the precedence graph are of the form:

First:-transaction

with smaller

Second:-transaction

with larger

timestamp timestamp

Thus, there will be no cycles in the precedence graph

Timestamp protocol ensures freedom from deadlock as no

transaction ever waits.

But the schedule may not be cascade-free, and may not even

be recoverable.

Recoverability and Cascade Freedom

Problem with timestamp-ordering protocol:

– Suppose Ti aborts, but Tj has read a data item written by Ti

– Then Tj must abort; if Tj had been allowed to commit

earlier, the schedule is not recoverable.

– Further, any transaction that has read a data item written by

Tj must abort

– This can lead to cascading rollback — that is, a chain of

rollbacks

Solution:

– A transaction is structured such that its writers are all

performed at the end of its processing

– All writes of a transaction form an atomic action; no

transaction may execute while a transaction is being written

– A transaction that aborts is restarted with a new timestamp