Transactions

Outline

Transaction Concept Transaction State Concurrent Executions Serializability

Recoverability Implementation of Transaction Definition in Testing for
Isolation SQL Serializability.

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 to deal with:

• Failures of various kinds, such as hardware failures and system crashes

• Concurrent execution of multiple transactions

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

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.
 Consistency requirement in above example:

• The sum of A and B is unchanged by the execution of the transaction

In general, consistency requirements include

• Explicitly specified integrity constraints such as primary keys and foreign keys

• Implicit integrity constraints

e.g., sum of balances of all accounts, minus sum of loan amounts must equal

value of cash-in-hand

• A transaction must see a consistent database.

• During transaction execution the database may be temporarily inconsistent.

• When the transaction completes successfully the database must be consistent

Erroneous transaction logic can lead to inconsistency

Example of Fund Transfer

ACID Properties
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.

Transaction State

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

• That is, to control the interaction among the concurrent transactions in order to prevent them from destroying the
consistency of the database

Schedules

Schedule – a sequences 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 instructions 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

Schedule 1

Schedule 2

Schedule 3
Schedule 4

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

Simplified view of transactions

We ignore operations other than 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.

Conflicting Instructions

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

Conflict Serializability

Conflict Serializability

View Serializability
View Serializability

Other Notions of Serializability

Testing for Serializability

Test for Conflict Serializability

Test for View Serializability

The precedence graph test for conflict serializability cannot be used directly to test for view serializability.

• Extension to test for view serializability has cost exponential in the size of the precedence graph.

The problem of checking if a schedule is view serializable falls in the class of NP-complete problems.

• Thus. existence of an efficient algorithm is extremely unlikely.

However practical algorithms that just check some sufficient conditions for view serializability can still be used.

Recoverable Schedules
Cascading Rollbacks

Cascadeless Schedules

Concurrency Control

A database must provide a mechanism that will ensure that all possible schedules are

• either conflict or view serializable, and

• are recoverable 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

• Are serial schedules recoverable/cascadeless?

Testing a schedule for serializability after it has executed is a little too late!

Goal – to develop concurrency control protocols that will assure serializability.

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.

Concurrency Control vs. Serializability Tests

Concurrency-control protocols allow concurrent schedules, but ensure that the schedules are conflict/view
serializable, and are recoverable and cascadeless .

Concurrency control protocols (generally) do not examine the precedence graph as it is being created

• Instead a protocol imposes a discipline that avoids non-serializable schedules.

• We study such protocols in Chapter 16.

Different concurrency control protocols provide different tradeoffs between the amount of concurrency they allow
and the amount of overhead that they incur.

Tests for serializability help us understand why a concurrency control protocol is correct.

Weak Levels of Consistency

Some applications are willing to live with weak levels of consistency,allowing schedules that are not serializable

• E.g., a read-only transaction that wants to get an approximate total balance of all accounts

• E.g., database statistics computed for query optimization can be approximate (why?)

• Such transactions need not be serializable with respect to other transactions

Tradeoff accuracy for performance

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.

• Successive reads of record may return different (but committed) values.

Read uncommitted — even uncommitted records may be read.

Levels of Consistency

Lower degrees of consistency useful for gathering approximate information about the database

Warning: some database systems do not ensure serializable schedules by default

 E.g., Oracle (and PostgreSQL prior to version 9) by default support a level of consistency called snapshot isolation
(not part of the SQL standard)

Transaction Definition in SQL

Implementation of Isolation Levels

Overview

Locking

• Lock on whole database vs lock on items

• How long to hold lock?

• Shared vs exclusive locks

Timestamps

• Transaction timestamp assigned e.g. when a transaction begins

• Data items store two timestamps

Read timestamp

Write timestamp

• Timestamps are used to detect out of order accesses

Multiple versions of each data item

• Allow transactions to read from a “snapshot” of the database

Transactions as SQL Statements