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Unit 4: Transaction Management By : Mrs. Suman Madan [email protected]
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Page 1: unit 4

Unit 4: Transaction Management

By :Mrs. Suman Madan

[email protected]

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Transaction Concept A transaction is a unit of program execution that accesses and

possibly updates various data items.

A transaction must see a consistent database.

During transaction execution the database may be inconsistent.

When the transaction is committed, the database must be consistent.

Two main issues to deal with:◦ Failures of various kinds, such as hardware failures and system crashes◦ Concurrent execution of multiple transactions

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ACID Properties

Atomicity - Either all operations of the transaction are properly reflectedin the database or none are.

Consistency - Execution of a transaction in isolation preserves theconsistency of the database.

Isolation - Although multiple transactions may execute concurrently,each transaction must be unaware of other concurrently executingtransactions. Intermediate transaction results must be hidden fromother concurrently executed transactions.◦ That is, for every pair of transactions Ti and Tj, it appears to Ti that either Tj,

finished execution before Ti started, or Tj started execution after Ti finished.

Durability - After a transaction completes successfully, the changes it hasmade to the database persist, even if there are system failures.

To preserve integrity of data, the database system must ensure:

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Example of Fund Transfer• Transaction to transfer $50 from account A to account B:

1.read(A)2.A := A – 503.write(A)4.read(B)5.B := B + 506.write(B)

• Consistency requirement – the sum of A and B is unchanged by theexecution of the transaction.

• Atomicity requirement — if the transaction fails after step 3 andbefore step 6, the system should ensure that its updates are notreflected in the database, else an inconsistency will result.

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Example of Fund Transfer• Durability requirement — once the user has been notified that

the transaction has completed (i.e., the transfer of the $50 hastaken place), the updates to the database by the transaction mustpersist despite failures.

• Isolation requirement — if between steps 3 and 6, anothertransaction is allowed to access the partially updated database, itwill see an inconsistent database(the sum A + B will be less than it should be).Can be ensured trivially by running transactions serially, that isone after the other. However, executing multiple transactionsconcurrently has significant benefits, as we will see.

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Transaction State• Active, the initial state; the transaction stays in this state while it is

executing

• Partially committed, after the final statement has been executed.

• Failed, after the discovery that normal execution can no longer proceed.

• Aborted, after the transaction has been rolled back and the database restored to its state prior to the start of the transaction. Two options after it has been aborted:

– restart the transaction – only if no internal logical error

– kill the transaction• Committed, after successful completion.

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Transaction State (cont…)

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Implementation of Atomicity and Durability

The recovery-management component of a databasesystem implements the support for atomicity and durability.

The shadow-database scheme:◦ assume that only one transaction is active at a time.◦ a pointer called db_pointer always points to the current

consistent copy of the database.◦ all updates are made on a shadow copy of the database, and

db_pointer is made to point to the updated shadow copy onlyafter the transaction reaches partial commit and all updatedpages have been flushed to disk.

◦ in case transaction fails, old consistent copy pointed to bydb_pointer can be used, and the shadow copy can be deleted.

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Implementation of Atomicity and Durability (Cont.)

• Assumes disks to not fail

• Useful for text editors, but extremely inefficient for large databases: executing a single transaction requires copying the entire database.

The shadow-database scheme:

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Concurrent Executions• Multiple transactions are allowed to run

concurrently in the system. Advantages are:– increased processor and disk utilization, leading to

better transaction throughput: one transaction canbe using the CPU while another is reading from orwriting to the disk

– reduced average response time for transactions:short transactions need not wait behind long ones.

• Concurrency control schemes – mechanisms toachieve isolation, i.e., to control the interactionamong the concurrent transactions in order toprevent them from destroying the consistency ofthe database.

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Schedules

• Schedules – sequences that indicate the chronological order in which instructions of concurrent transactions are executed

– a schedule for a set of transactions must consist of all instructions of those transactions

– must preserve the order in which the instructions appear in each individual transaction.

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Example Schedules• Let T1 transfer $50 from A to B, and T2 transfer 10%

of the balance from A to B. The following is a serial schedule (Schedule 1), in which T1 is followed by T2.

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Example Schedules• Let T1 and T2 be the transactions defined previously. The following schedule

(Schedule 3) is not a serial schedule, but it is equivalent to Schedule 1.

In both Schedule 1 and 3, the sum A + B is preserved.

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Example Schedules (Cont.)• The following concurrent schedule (Schedule 4 )

does not preserve the value of the sum A + B.

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Lost Update Problem

T1

read_item(X);

X:=X - N;

write_item(X);

read_item(Y);

Y:=Y + N;

write_item(Y);

T2

read_item(X);

X:=X+M;

write_item(X);

time

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Temporary Update (Dirty Read)

T1

read_item(X);

X:=X - N;

write_item(X);

read_item(Y);

T1 fails and aborts

T2

read_item(X);

X:=X+M;

write_item(X);

time

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Incorrect Summary Problem

T1

read_item(X);

X:=X-N;

write_item(X);

read_item(Y);

Y=Y+N

Write_item(Y)

T2

sum:=0;

read_item(A);

sum:=sum+A;

read_item(X);

sum:=sum+X;

read_item(Y);

sum:=sum+Y

time

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What Can Go Wrong?• System may crash before data is written back to disk

= Problem of atomicity

• Some transaction is modifying shared data while another transaction is ongoing (or vice versa)

= Problem of serialization and isolation

• System may not be able to obtain one or more of the data items

• System may not be able to write one or more of the data items

= Problems of atomicity

• DBMS has a Concurrency Control subsytem to assure database remains in consistent state despite concurrent execution of transactions

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Serializability• Basic Assumption – Each transaction preserves database consistency.

• Thus serial execution of a set of transactions preserves database consistency.

• A (possibly concurrent) schedule is serializable if it is equivalent to a serial schedule. Different forms of schedule equivalence give rise to the notions of:

1. conflict serializability

2. view serializability

• We ignore operations other than read and write instructions, and we assume that transactions may perform arbitrary computations on data in local buffers in between reads and writes. Our simplified schedules consist of only read and write instructions.

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Conflict Serializability• Instructions li and lj of transactions Ti and Tj respectively, conflict if

and only if there exists some item Q accessed by both li and lj, and at least one of these instructions wrote Q.

1. li = read(Q), lj = read(Q). li and lj don’t conflict.2. li = read(Q), lj = write(Q). They conflict.3. li = write(Q), lj = read(Q). They conflict4. li = write(Q), lj = write(Q). They conflict

• Intuitively, a conflict between li and lj forces a (logical) temporal order between them. If li and lj are consecutive in a schedule and they do not conflict, their results would remain the same even if they had been interchanged in the schedule.

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Conflict Serializability (Cont.)• If a schedule S can be transformed into a schedule S´ by a series of

swaps of non-conflicting instructions, we say that S and S´ are conflict equivalent.

• We say that a schedule S is conflict serializable if it is conflict equivalent to a serial schedule

• Example of a schedule that is not conflict serializable:

T3 T4

read(Q)write(Q)

write(Q)

We are unable to swap instructions in the above schedule to obtain either the serial schedule < T3, T4 >, or the serial schedule < T4, T3 >.

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Conflict Serializability (Cont.)

• Schedule 3 below can be transformed into Schedule 1, a serial schedule where T2 follows T1, by series of swaps of non-conflicting instructions. Therefore Schedule 3 is conflict serializable.

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View Serializability• Let S and S´ be two schedules with the same set of

transactions. S and S´ are view equivalent if the following three conditions are met:1.For each data item Q, if transaction Ti reads the initial

value of Q in schedule S, then transaction Ti must, in schedule S´, also read the initial value of Q.

2.For each data item Q if transaction Ti executes read(Q) in schedule S, and that value was produced by transaction Tj (if any), then transaction Ti must in schedule S´ also read the value of Q that was produced by transaction Tj .

3.For each data item Q, the transaction (if any) that performs the final write(Q) operation in schedule S must perform the final write(Q) operation in schedule S´.

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View Serializability (Cont.)• A schedule S is view serializable if it is view equivalent to a serial

schedule.

• Every conflict serializable schedule is also view serializable.

• Schedule 9 - a schedule which is view-serializable but not conflict serializable.

• Every view serializable schedule that is not conflictserializable has blind writes.

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Other Notions of Serializability• Schedule 8 given below produces same outcome as the serial

schedule < T1, T5 >, yet is not conflict equivalent or view equivalent to it.

• Determining such equivalence requires analysis of operations other than read and write.

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Recoverability

• Recoverable schedule — if a transaction Tj reads a data itemspreviously written by a transaction Ti , the commit operation of Ti

appears before the commit operation of Tj.

• The following schedule (Schedule 11) is not recoverable if T9

commits immediately after the read

• If T8 should abort, T9 would have read (and possibly shown to theuser) an inconsistent database state. Hence database must ensurethat schedules are recoverable.

Need to address the effect of transaction failures on concurrently

running transactions.

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Recoverability (Cont.)• Cascading rollback – a single transaction failure leads to a

series of transaction rollbacks. Consider the following schedule where none of the transactions has yet committed (so the schedule is recoverable)

• If T10 fails, T11 and T12 must also be rolled back.

• Can lead to the undoing of a significant amount of work

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Recoverability (Cont.)

• Cascade-less schedules — cascading rollbacks cannot occur; for each pair of transactions Ti

and Tj such that Tj reads a data item previously written by Ti, the commit operation of Ti appears before the read operation of Tj.

• Every cascade-less schedule is also recoverable

• It is desirable to restrict the schedules to those that are cascade-less

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Implementation of Isolation• Schedules must be conflict or view serializable, and recoverable,

for the sake of database consistency, and preferably cascadeless.

• A policy in which only one transaction can execute at a time generates serial schedules, but provides a poor degree of concurrency..

• Concurrency-control schemes tradeoff between the amount of concurrency they allow and the amount of overhead that they incur.

• Some schemes allow only conflict-serializable schedules to be generated, while others allow view-serializable schedules that are not conflict-serializable.

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Transaction Definition in SQL• Data manipulation language must include a construct for specifying

the set of actions that comprise a transaction.

• In SQL, a transaction begins implicitly.

• A transaction in SQL ends by:

– Commit work commits current transaction and begins a new one.

– Rollback work causes current transaction to abort.

• Levels of consistency specified by SQL-92:

– Serializable — default

– Repeatable read

– Read committed

– Read uncommitted

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Levels of Consistency in SQL-92

• Serializable — default

• Repeatable read — only committed records to be read, repeated reads of same record must return same value. However, a transaction may not be serializable – it may find some records inserted by a transaction but not find others.

• Read committed — only committed records can be read, but successive reads of record may return different (but committed) values.

• Read uncommitted — even uncommitted records may be read.

Lower degrees of consistency useful for gathering approximate

information about the database, e.g., statistics for query optimizer.

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Testing for Serializability• Consider some schedule of a set of transactions

T1, T2, ..., Tn

• Precedence graph — a direct graph where the vertices are the transactions (names).

• We draw an arc from Ti to Tj if the two transaction conflict, and Ti accessed the data item on which the conflict arose earlier.

• We may label the arc by the item that was accessed.

• Example 1

x

y

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T1

Read(N)

T2

Read(N)

N=N-1

N= N-1

Write(N)

Write(N)

Example : Precedence graph

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Precedence graph

T1

Read(N)

T2

Read(N)

N=N-1

N= N-1

Write(N)

Write(N) T1

T2N

N

Cycle -> not serializable

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Examples (Precedence Graph)

Assume we have these three transactions:• T1: r1(x);w1(x);r1(y);w1(y)

• T2: r2(z);r2(y);w2(y);r2(x);w2(x)

• T3: r3(y);r3(z);w3(y);w3(z)

Assume we have these schedule:

• S1: r2(z);r2(y);w2(y); r3(y);r3(z); r1(x);w1(x); w3(y);w3(z);r2(x); r1(y);w1(y); w2(x)

No equivalent serial schedule

(cycle x(T1T2),y(T2T1))

(cycle x(T1T2),yz(T2T3),y(T3T1))

y

x

y y,z

T1 T2

T3

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Examples (Precedence Graph)

Assume we have another schedule for the same transactions:

• S2: r3(y);r3(z);r1(x); w1(x);w3(y);w3(z);r2(z); r1(y);w1(y);r2(y); w2(y);r2(x);w2(x)

Equivalent serial schedule

T3T1T2

x,y

y y,z

T1 T2

T3

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Recoverability• Serializability maintains the consistency of the database,

assuming that no transactions fail, but…

• If a transaction fails:

– Atomicity requires the effects of the transaction to be undone

– Durability states that the effects of a committing transaction cannot be undone

– Some schedules are therefore unrecoverable

• For a schedule to be recoverable

– For a pair of transactions Ti and Tj, if Tj reads a data item previously written by Ti, then the read by Tj must be after the commit of Ti

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Concurrency Techniques

• Two basic concurrency control approaches

– Conservative (Pessimistic)

• Locking

• Time stamping

– Optimistic (Conflict is rare)

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Conservative Technique• Also known as Pessimistic

– locking

• most widely used approach, best known is Two-phase locking.

• It works by delaying operations within transactions in case they conflict with other transactions.

• 2PL works by having two types of locks –

– read locks (there can be an infinite number of read operations and they will always return the same result),

– exclusive (write) locks - there can be no other locks for an exclusive lock.

– The problem with 2PL is that deadlock can occur and should be resolved.

– Time-stamping

• ordering transactions such that older transactions get priority in the event of a conflict.

• Timestamping is one approach to resolving situations such as deadlock.

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Optimistic

– Conflict is rare

– Allow transactions to proceed unsynchronized

– Check for conflicts at end when transaction commits

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Why Recovery Is Needed

• There several possible reasons for a transaction to fail– A computer failure : A hardware, software, or network error

occurs in the computer system during transaction execution.

– A transaction or system error : Some operations in the transaction may cause it to fail.

– Local errors or exception conditions detected by the transaction.

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Why Recovery Is Needed (continued)

– Concurrency control enforcement : The concurrency control method may decide to abort the transaction.

– Disk failure : all disk or some disk blocks may lose their data

– Physical problems : Disasters, theft, fire, etc.

• The system must keep sufficient information to recover from the failure.

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The System Log

• The system maintains a log to keep track of all transaction operations that affect the values of database items.

• This log may be needed to recover from failures.

• Types of log records :– [start_transaction,T] : indicates that transaction T has started

execution.

– [write_item,T,X,old_value,new_value] : indicates that transaction T has changed the value of database item X from old_value to new_value.

(new_value may not be recorded)

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The System Log (continued)

– [read_item,T,X]: indicates that transaction T has read the value of database item X.

(read_item may not be recorded)

– [commit,T]: transaction T has recorded permanently .

– [abort,T]: indicates that transaction T has been aborted.

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Database Recovery• Restoring a database to a correct state in the event of a failure is called

recovery.

• Transactions are the basic unit of recovery

– transaction manager has to ensure that either all affects of a transaction are permanently recorded, or none i.e. atomicity and durability. Therefore the transaction manager uses the commit protocol.

• If transaction fails then use

– Roll forward (redo logs) - redo logs will allow the results of transactions to be repeated, e.g. if the failure occurs between writing data to the buffer and flushing the buggers, ensuring durability.

– rollback (undo logs) - Undo logs will allow to abort a transaction (or rollback) to guarantee atomicity, e.g. if the transaction has not committed at the time of failure then the database will be rolled back to the previous state.

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Recovery Facilities• Facilities which a DBMS will provide

– Backup -to periodically back up data (and log files).

– Journal - the DBMS creates log files of transactions performed on the DBMS. Obviously this is important because the backup may not always be the most up to date copy of the database

– Checkpoint - the commit protocol signifies the point at which all parts of a transaction have been completed, and the database is at the next consistent state. Thus each commit point has a checkpoint written into the log, so that the recovery manager knows how far back to go in, e.g. rollback.

– Recovery Manager - there must be a recovery manager which will allow the DBMS to recover from various problems.

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Recovery Techniques• Deferred update - no updates are written to the permanent database

until the commit point. Therefore, if there is an abort then no undo’s are necessary. This technique requires redo/after logs.

• Immediate update - updates are permanently recorded before the commit. Also known as write ahead logging. Removes need for after images, but still needs undo/before images.

• Shadow paging - 2 page tables are kept during the lifetime of a transaction – a current and shadow page table. The shadow never changes, and the current is updated. When the transaction commits, the shadow page is replaced by the current page. The advantage is that the overhead of the logs is eliminated, giving faster recovery (as there is no undo/redo process) but can be susceptible to data fragmentation and needs garbage collection.

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Recoverability

• A schedule S is said to be recoverable if no transaction T in S commits until all transactions T’ that have written an item that T reads have committed

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Characterizing Schedules based on Recoverability

• Type of schedules :

– recoverable scheduls : once a transaction T is commited , it should never rollbacked.

• i.e. If no transaction T in S commits until all transactions T’ that have written an item that T reads have committed.

• It is possible for Cascading rollback to occur when an uncommited transaction has to be rolled back.

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Examples

• 1- Sa: r1(x);r2(x);w1(x);r1(y);w2(x);c2;w1(y);c1;

Recoverable schedule, even it suffers from the lost update problem [w1(x);w2(x)]

• 2- Sc: r1(x); w1(x); r2(x); r1(y);w2(x);c2;a1;

Non-recoverable schedule. Why?

T2 reads x from T1, and then T2 commits before T1 commits. If T1 aborts, then T2 must be aborted after had been committed.

a- abort operation, c : commit operation

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Examples

• 3- To make Sc recoverable, c2 of Sc must be postponed until after T1 commits as follows:

Sd: r1(x); w1(x); r2(x); r1(y);w2(x); w1(y);c1; c2;

• If T1 aborts, then T2 should also abort as follows:

Se: r1(x); w1(x); r2(x); r1(y);w2(x); w1(y);a1; a2;

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Characterizing Schedules based on Recoverability (continued)

– Cascade less schedule : if every transaction in the schedule reads only items that were written by committed transactions.

– Strict Schedule : transactions can neither read nor write an item X until the last transaction that wrote X has committed or aborted.