ICS 541 - 01 (072)Concurrency Control1 Transaction Processing and Concurrency Control Dr. Muhammad Shafique Chapter 18 17 March 2008

ICS 541 - 01 (072) Concurrency Control 1

Transaction Processing and

Concurrency Control

Dr. Muhammad Shafique

Chapter 18

17 March 2008


Outline

• Granularity of data items • Concurrency control techniques• Locking techniques • Timestamp ordering techniques • Multi-version concurrency control techniques • Optimistic concurrency control techniques• Advanced Concurrency control techniques • Summary


Concurrency Control Techniques

• Categories of concurrency techniques1. Locking techniques

2. Timestamp ordering techniques

3. Multi-version concurrency control techniques

4. Optimistic concurrency control techniques

5. Advanced concurrency control techniques


Granularity of Data Items• Size or granule of data for concurrency control is data

item granularity. It could be• An attribute value• A database record• A disk block• A whole file• The whole database

• Data item granularity and degree of concurrency• Fine granularity --- refers to small item sizes• Coarse granularity --- refers to large item sizes• Larger the data item size, lower the degree of concurrency

• Data item size depends on the types of transactions


Granularity of Data Items (Cont.)

• Multiple granularity levels and locking


Granularity of Data Items (Cont.)

• Multiple granularity levels and locking (cont.)

• Intension locks

In addition to shared (S) and Exclusive (X)

• Intention-Shared (IS)

• Intention-Exclusive (IX)

• Shared-Intention-Exclusive (SIX)

• Locking compatibility


Concurrency Control Through Locks

• Lock • A variable associated with a data item

• Describes status of the data item with respect to operations that can be performed on it

• Binary locks • Locked/unlocked

• Enforces mutual exclusion

• Multiple-mode locks: • Read lock or shared lock

• Write lock or exclusive lock

• Unlock

• Each data item can be in one of three lock states


Locking Rules1. T must issue read_lock(X) or write_lock(X) before any

read_item(X) operation is performed in T

2. T must issue write_lock(X) before any write_item(X) operation is performed in T

3. T must issue unlock(X) after all read_item(X) and write_item(X) operations are completed in T

4. T will not issue a read_lock(X) if it already holds a read lock or write lock on X (may be relaxed)

5. T will not issue a write_lock(X) if it already holds a read lock or write lock on X (may be relaxed)

6. T will not issue unlock (X) request unless it holds a read lock write lock on X


Two Transactions

T1read_lock(Y);

read_item(Y);

unlock(Y);

write_lock(X);

read_item(X);

X:=X+Y;

write_item(X);

unlock(X);

T2read_lock(X);

read_item(X);

unlock(X);

write_lock(Y);

read_item(Y);

Y:=X+Y;

write_item(Y);

unlock(Y);

Let’s assume serial schedule S1: T1,T2

Initial values: X=20, Y=30 Result: X=50, Y=80


Locks Alone Don’t Insure Serializability

T1read_lock(Y);read_item(Y);unlock(Y);

write_lock(X);read_item(X);X:=X+Y;write_item(X);unlock(X);

T2

read_lock(X);read_item(X);unlock(X);write_lock(Y);read_item(Y);Y:=X+Y;write_item(Y);unlock(Y);

Non-serializable!

Result: X=50, Y=50

unlocked too early!

Let’s run T1 and T2 in interleaved fashion

Schedule S


Two-Phase Locking (2PL) Protocol

• Transaction is said to follow the two-phase-locking protocol if all locking operations precede the first unlock operation • Expanding (growing) phase

• Shrinking phase

• During the shrinking phase no new locks can be acquired• Downgrading ok

• Upgrading is not

• Example


2PL ExampleT1’

read_lock(Y);

read_item(Y);

write_lock(X);

unlock(Y);

read_item(X);

X:=X+Y;

write_item(X);

unlock(X);

T2’read_lock(X);

read_item(X);

write_lock(Y);

unlock(X);

read_item(Y);

Y:=X+Y;

write_item(Y);

unlock(Y);

• Both T1’ and T2’ follow the 2PL protocol

• Any schedule including T1’ and T2’ is guaranteed to be serializable

• Limits the amount of concurrency


Locking Techniques for Concurrency Control

• Quick review of ideas discussed so far• Locks and system lock tables

• Lock table and lock manager

• Binary locks --- lock & unlock operations (critical sections)

• Shared/exclusive locks --- read-lock, write-lock, and unlock

• Conversion of locks• Upgrade the lock

• Downgrade the lock

• Concurrency control subsystem generates read-lock and write-lock requests on behalf of the transactions

• Using locks in transactions does not guarantee serializability of schedules on its own


Using Locks for Concurrency Control in Indexes

• Two phase locking can be applied to indexes. Here the nodes of an index correspond to disk pages.

• Tree structure of the index can be taken advantage of• A conservative approach for insertions can be to lock

the root node in exclusive mode.• Index locking using B-link tree rather than B+ tree

• In B-link tree, sibling nodes at the same level are linked together at every level


Locking Techniques for Concurrency Control (Cont.)

• Two-phase locking protocol (2PL)All lock operations precede the first unlock operation• Expanding phase and shrinking phase

• Upgrading of locks must be done in expanding phase and downgrading of locks must be done in shrinking phase

• If every transaction in a schedule follows 2PL protocol then the schedules is guaranteed to be serializable.

• Variants of 2PLBasic, conservative, strict, and rigorous


Locking Techniques for Concurrency Control (Cont.)

1. Basic 2PLAll lock operations before the first unlock operation

2. Conservative 2PL or static 2PL Lock all the items it accesses before the transaction begins execution.

1. Deadlock free protocol2. Read-set and write-set of the transaction should be known

3. Strict 2PL No exclusive lock will be unlocked until the transaction commits or aborts

• Strict 2PL guarantees strict schedules4. Rigorous 2PL

No lock will be unlocked until the transaction commits or aborts


Dealing with Deadlocks and Starvation in 2PL

• 2PL can produce deadlocks• Deadlock and starvation in 2PL

Deadlock occurs when each transaction T in a set of two or more transactions is waiting for some item that is locked by some other transaction T’ in the set.

• Example (next slide)


Dealing with Deadlocks and Starvation in 2PL


Dealing with Deadlocks and Starvation in 2PL• Deadlock prevention protocols

• Conservative 2PL, lock all needed items in advance

• Ordering all items in the database

• Possible actions if a transaction is involved in a possible deadlock situation• Block and wait

• Abort and restart

• Preempt and abort another transaction


Dealing with Deadlocks and Starvation in 2PL• Two schemes that prevent deadlock (Timestamp based)

• Wait-die

An older transaction is allowed to wait on a younger transaction whereas a younger transaction requesting an item from held by an older transaction is aborted and restarted with the same timestamp

• Wound-wait

A younger transaction is allowed to wait on an older transaction whereas an older transaction requesting an item from held by a younger transaction preempts the younger transaction by aborting it.


Dealing with Deadlocks and Starvation in 2PL• Two schemes that prevent deadlock and do not

require timestamps• No waiting

Abort immediately and restart after a certain time delay

• Cautious waiting

• If a transaction holding the lock is not waiting for another item to be locked then allow T to wait otherwise abort and restart T


Dealing with Deadlocks and Starvation in 2PL• Deadlock detection and timeouts

• Construct and maintain a wait-for graph• Victim selection

• Timeouts

• StarvationA transaction cannot proceed for an infinite period of time while other transactions in the system continue normally• Unfair waiting scheme

• Victim selection


Concurrency Control Based on Timestamp Ordering• Timestamp --- a unique identifier created by the

DBMS to identify a transaction• read-TS(X)

• The largest timestamp among all the timestamps of transactions that have successfully read item X

• write-TS(X)• The largest timestamp among all the timestamps of transactions

that have successfully written item X

• Timestamp Ordering (TO) algorithms• Basic timestamp ordering• Strict timestamp ordering• Thomas’s write rule


Concurrency Control Based on Timestamp Ordering (Cont.)

• Basic timestamp ordering algorithmOrder transactions based on their timestamps1. T issues a write(X)

1. If read-TS(X) > TS(T) or if write-TS(X) > TS(T) the abort and rollback T and reject the operation.

2. If condition above does not occur then execute the operation and set write-TS(X) = TS(T)

2. T issues a read(X)1. If write-TS(X) > TS(T) then abort and rollback T and reject the

operation.2. If write-TS(X) TS(T) then execute the operation and set

read-TS(X) = max ( read-TS(X), TS(T) )

• The schedules produced by basic TO are guaranteed to be conflict serializable

• No deadlocks but cyclic restart are possible (hence starvation)



• Strict Timestamp Ordering (strict TO)• A transaction T that issues a read-item(X) or write-item(X)

such that TS(T) > write-TS(X) has its read or write operation delayed until the transaction T’ that wrote the value of X (hence TS(T’ ) = write-TS(X)) has committed or aborted.

• No deadlocks, since T waits for T’ only if TS(T) > TS(T’)

• Strict TO ensures that the schedules are both strict (for easy recoverability) and (conflict) serializable



• Thomas’s write rule• It rejects fewer write operations, by modifying the basic TO

checks for the write-item(X) operation as follows: 1. If read-TS(X) > TS(T), then abort and roll back T and reject the

operation.

2. If write-TS(X) > TS(T), then do not execute the write operation but continue processing. [This is because some transaction with timestamp greater than TS(T)—and hence after T in the timestamp ordering—has already written the value of X. Hence, we must ignore the write_item(X) operation of T because it is already outdated and obsolete.

Notice that any conflict arising from this situation would be detected by case (1).]

3. If neither the condition in part (1) nor the condition in part (2) occurs, then execute the write-item(X) operation of T and set write-TS(X) to TS(T).

• Thomas’ write rule does not enforce conflict serializability


Multi-version Concurrency Control Techniques

• Several versions X1, X2, ..., Xk of each data item X are maintained

• Multi-version Technique based on timestamp ordering• To ensure serializability, the following two rules are used

1. If transaction T issues a write(X) operation, and version i of x has the highest write-TS(Xi) of all versions of X that is also less than or equal to TS(T), and read-TS(Xi) > TS(T), then abort and rollback T; otherwise create a new version Xj of x with read-TS(Xj) = write-TS(Xj) =TS(T)

2. If transaction T issues a read(X) operation, find version i of x that has the highest write-TS(Xi) of all versions of X that is also less than or equal to TS(T), then return the value of Xj to transaction T, and set the value of read-TS(Xj) to the larger of TS(T) and the current read-TS(Xj)


Multi-version Concurrency Control Techniques• Multi-version 2PL using certify locks

• Three locking modes: read, write, and certify

• Two versions of each item X; one version must have been written by some committed transaction and the second version is created when a transaction acquires a write lock on X

• A transaction must acquire a certify lock on all items that it currently holds write locks on before it can commit

• The scheme avoids cascading aborts


Optimistic Concurrency Control Techniques

• Optimistic concurrency control techniques also known as validation concurrency control techniques or certification concurrency control techniques

• No checking is done while the transaction is executing • Updates in the transaction are not applied directly to the

database until the transaction reaches its end• There are three phases

1. Read phase --- a transaction can read values of committed data items from the database. Updates are applied only to the local copies of the data items

2. Validation phase --- Checking is performed to ensure that serializability will not be violated if the transaction updates are applied to the database.

3. Write phase --- if the validation phase is successful, the transaction updates are applied to the data base otherwise the updates are discarded and the transaction restarted.


Optimistic Concurrency Control Techniques• Validation phase

• Timestamp• Read-set and write-set of a transaction• Start and end time for each of the three phases of a transaction• Mutual exclusiveness

For transaction Ti the protocol checks that Ti does not interfere with any committed transaction or with a transaction in validation phase, i.e.,

1. Tj completes its write phase before Ti starts its read phase

2. Ti starts its write phase after Tj completes its write phase and intersection

of read-set of Ti and write-sets of Tj is empty

3. Both the read-set and write set of Ti have no items in common with the

write-set of Tj and Tj completes its read phase before Ti completes its

read phase.


Other Concurrency Control Issues• Insertion, deletion, and phantom records

• Insertion operation• New data item inserted in the database

• Deletion operation

• Phantom record• Use index locking

• Interactive transactions• No rollback

• Delay output of transactions until they have committed

• Latches• Locks held for a short duration are called latches

• Latches are used to , for example, write a buffer to a page


Summary

• Granularity of data items • Concurrency control techniques

• Locking techniques • Timestamp ordering techniques • Multi-version concurrency control techniques • Optimistic concurrency control techniques

• Other concurrency control issues

Thank you

Documents

ICS 541 - 01 (072)Concurrency Control1 Transaction Processing and Concurrency Control Dr. Muhammad Shafique Chapter 18 17 March 2008