程序代写代做代考 database SQL scheme algorithm concurrency Chapter 14: Transaction Processing

Chapter 14: Transaction Processing

Transactions
Transaction Concept
Concurrent Executions and Schedules
Serializability
Recoverable and Cascadeless Schedules

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Database System Concepts

Transaction Concept
A transaction is a unit of program execution that accesses and possibly updates various data items.
E.g. transaction to transfer $50 from account A to account B:
1. read(A)
2. A := A – 50
3. write(A)
4. read(B)
5. B := B + 50
6. write(B)
Two main issues that may result in the database becoming inconsistent during transaction execution:
Failures of various kinds, such as hardware failures and system crashes
Concurrent execution of multiple transactions  You will learn this very soon!

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Database System Concepts

Example of Fund Transfer
Transaction to transfer $50 from account A to account B:
1. read(A)
2. A := A – 50
3. write(A)
4. read(B)
5. B := B + 50
6. write(B)
Atomicity requirement
If the transaction fails after step 3 and before step 6, money will be “lost” leading to an inconsistent database state, i.e., the sum of A and B is no longer preserved.
Failure could be due to software or hardware
The system should ensure that updates of a partially executed transaction are not reflected in the database.
Durability requirement
Once the user has been notified that the transaction has completed (i.e., the transfer of the $50 has taken place), the updates to the database by the transaction must persist even if there are software or hardware failures.

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Database System Concepts

Example of Fund Transfer (Cont.)
Transaction to transfer $50 from account A to account B:
1. read(A)
2. A := A – 50
3. write(A)
4. read(B)
5. B := B + 50
6. write(B)
In general, consistency requirements include
Explicit integrity constraints such as primary keys and foreign keys
Implicit integrity constraints, e.g., sum of A and B be unchanged by the execution of the transaction
A transaction must see a consistent database.
If the database is consistent before an execution of the transaction, the database remains consistent after the execution of the transaction.
Erroneous transaction logic can lead to inconsistency
However, during transaction execution, the database may be temporarily inconsistent…..

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Database System Concepts

Example of Fund Transfer (Cont.)
Isolation requirement
If between steps 3 and 6, another transaction T2 is allowed to access the partially updated database, it will see an inconsistent database (the sum A + B will be less than it should be).
T1 T2
1. read(A)
2. A := A – 50
3. write(A)
read(A), read(B), print(A+B)
4. read(B)
5. B := B + 50
6. write(B
Isolation can be ensured trivially by running transactions serially
that is, one after the other.
However, executing multiple transactions concurrently has significant benefits, as we will see later.

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Database System Concepts

ACID Properties
 Atomicity. Either all operations of the transaction are properly reflected in the database or none are.
 Consistency. Execution of a transaction in isolation preserves the consistency of the database. Responsibility of application programmers!
 Isolation. Although multiple transactions may execute concurrently, each transaction must be unaware of other concurrently executing transactions. Intermediate transaction results must be hidden from other concurrently executed transactions. Responsibility of concurrency-control system!
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 has made to the database persist, even if there are system failures.
A transaction is a unit of program execution that accesses and possibly updates various data items. To preserve the integrity of data, the database system must ensure:

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Database System Concepts

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
can be done only if no internal logical error
kill the transaction
Committed – after successful completion.

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Database System Concepts

Transactions
Transaction Concept
Concurrent Executions and Schedules
Serializability
Recoverable and Cascadeless Schedules

©Silberschatz, Korth and Sudarshan
‹#›
Database System Concepts

Concurrent Executions
Multiple transactions are allowed to run concurrently in the system. Advantages are:
increased processor and disk utilization, leading to better transaction throughput
E.g. one transaction can be using the CPU while another is reading from or writing to the disk
reduced average response time for transactions: short transactions need not wait behind long ones.
Concurrency control schemes – mechanisms to achieve isolation
To control the interaction among the concurrent transactions in order to prevent them from destroying the consistency of the database
Will study after studying notion of correctness of concurrent executions.

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Database System Concepts

Schedules
Schedule – a sequence of instructions that specify 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.
A transaction that successfully completes its execution will have a commit instruction as the last statement
by default transaction assumed to execute commit instruction as its last step
A transaction that fails to successfully complete its execution will have an abort instruction as the last statement

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Database System Concepts

Schedule 1
Let T1 transfer $50 from A to B, and T2 transfer 10% of the balance from A to B.
A serial schedule in which T1 is followed by T2 :

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Database System Concepts

Schedule 2

A serial schedule where T2 is followed by T1:

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Database System Concepts

Schedule 3
Let T1 and T2 be the transactions defined previously. The following schedule is not a serial schedule, but it arrives at the same state as Schedule 1.

In Schedules 1, 2 and 3, the sum A + B is preserved.

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Database System Concepts

Schedule 4
The following concurrent schedule does not preserve the value of (A + B).

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Database System Concepts

Transactions
Transaction Concept
Concurrent Executions and Schedules
Serializability
Recoverable and Cascadeless Schedules

©Silberschatz, Korth and Sudarshan
‹#›
Database System Concepts

Serializability
Basic Assumption – Each transaction preserves database consistency.
Thus serial execution of a set of transactions preserves database consistency.
So, database consistency under concurrent execution can be ensured by making sure that any schedule has the same effect as a serial schedule.
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
 view serializability
Is not used in practice due to its high computational complexity.

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Database System Concepts

Simplified view of transactions
From a scheduling point of view, the only significant operations of a transaction are read and write instructions.
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.
A common notation:
Example:
T1: r1(A); w1(A); r1(B); w1(B);
T2: r2(A); w2(A); r2(B); w2(B);
S3: r1(A); w1(A); r2(A); w2(A); r1(B); w1(B); r2(B); w2(B);

Schedule 3

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Database System Concepts

Conflicting Instructions
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 conflict
4. 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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Database System Concepts

Conflict Serializability
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.

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Database System Concepts

Conflict Serializability (Cont.)
Schedule 3 can be transformed into Schedule 6, a serial schedule where T2 follows T1, by series of swaps of non-conflicting instructions. Therefore Schedule 3 is conflict serializable.
Schedule 3
Schedule 6

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Database System Concepts

Conflict Serializability (Cont.)

Example of a schedule that is not conflict serializable:

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

Testing for Serializability
A simple method for determining conflict serializability.
Consider a schedule of a set of transactions T1, T2, …, Tn.
Precedence graph — a directed graph where the vertices are the transactions (names).
We draw an arc from Ti to Tj if the two transactions conflict, and Ti accessed the data item on which the conflict arose earlier.
We may label the arc by the item that was accessed.

Precedence graph for Schedule 4

Schedule 4
S4: r1(A); r2(A); w2(A); r2(B); w1(A); r1(B); w1(B); w2(B);

Test for Conflict Serializability
A schedule is conflict serializable if and only if its precedence graph is acyclic.
Cycle-detection algorithms exist which take order n2 time, where n is the number of vertices in the graph.
(Better algorithms take order n + e where e is the number of edges.)
If precedence graph is acyclic, the serializability order can be obtained by a topological sorting of the graph.
This is a linear order consistent with the partial order of the graph.

Transactions
Transaction Concept
Concurrent Executions and Schedules
Serializability
Recoverable and Cascadeless Schedules

Recoverable Schedules
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 the user) an inconsistent database state (the value of A written by the aborted T8). We must abort T9 to ensure atomicity.
Hence, database must ensure that schedules are recoverable.
Recoverable schedule — if a transaction Tj reads a data item previously written by a transaction Ti , then the commit operation of Ti appears before the commit operation of Tj.

Need to address the effect of transaction failures on concurrently
running transactions.

Cascading Rollbacks
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

Cascadeless Schedules
Cascadeless 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, i.e., allow transaction to only read committed data.
Every cascadeless schedule is also recoverable
It is desirable to restrict the schedules to those that are cascadeless

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.
In almost all database systems, by default, every SQL statement also commits implicitly if it executes successfully

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