Recovery & Concurrency Control

What is a Transaction? A transaction is a logical unit of work that

must be either entirely completed or aborted. A database request is the equivalent of a

single SQL statement in an application program or transaction.

A transaction that changes the contents of the database must alter the database from one consistent database state to another.

To ensure consistency of the database, every transaction must begin with the database in a known consistent state.

Example of Transaction

X = 100

X = 50

X = X - 50

Amount in stock = X

Initial State <Consistent State>

Final State <Consistent State>

Transaction A <Modifies database>

Transaction ACID Properties

AtomicAll operations of a transaction be completed; if not, the

transaction is aborted.Transaction cannot be subdivided

ConsistentConstraints don’t change from before transaction to after

transaction Isolated

Data used during the execution of a transaction cannot be used by a second transaction until the first one is completed.

Database changes not revealed to users until after transaction has completed

DurableDatabase changes are permanentThe permanence of the database’s consistent state.

Transaction Management with SQL

Transaction support is provided by 2 SQL statements: COMMIT ROLLBACK.

When a transaction sequence is initiated, it must continue through all succeeding SQL statements until one of the following four events occurs:A COMMIT statement is reached.A ROLLBACK statement is reached.The end of a program is successfully reached

(COMMIT).The program is abnormally terminated (ROLLBACK).

Transaction Management with SQL

Example:UPDATE PRODUCTSET PROD_QOH = PROD_QOH - 200WHERE PROD_CODE = ‘QS123XY’;

UPDATE ACCT_RECEIVABLESET ACCT_BALANCE = ACCT_BALANCE + 10000WHERE ACCT_NUM = ‘12345678’;

COMMIT;

Concurrency Control Problem–in a multi-user environment,

simultaneous access to data can result in interference and data loss

Solution–Concurrency ControlConcurrency ControlThe process of managing simultaneous

operations against a database so that data integrity is maintained and the operations do not interfere with each other in a multi-user environment

Concurrency Control The objective of concurrency control is to

ensure the serializability of transactions in a multi-user database environment.

Simultaneous execution of transactions over a shared database can create several data integrity and consistency problems:Lost Updates.Uncommitted Data.Inconsistent retrievals.

Lost Updates

Lost Updates Using Product Table: Product’s quantity on Hand

(PROD_QOH) Two concurrent transactions update PROD_QOH:

See Table 1 for the serial execution under normal circumstances.

See Table 2 for the lost update problems resulting from the execution of the second transaction before the first transaction is committed.

Lost Updates

Uncommitted Data Data are not committed when two transactions T1

and T2 are executed concurrently and the first transaction is rolled back after the second transaction has already accessed the uncommitted data - thus violating the isolation property of the transaction.

Uncommitted Data

Correct Execution Of Two Transactions

An Uncommitted Data Problem

Inconsistent Retrieval Inconsistent retrievals occur when a transaction

calculates some summary (aggregate) functions over a set of data while other transactions are updating the data.

Example:T1 calculates the total quantity on hand of the

products stored in the PRODUCT table.At the same time, T2 updates the quantity on hand

(PROD_QOH) for two of the PRODUCT table’s products.

Inconsistent Retrieval

Inconsistent Retrieval

Inconsistent Retrieval

Concurrency Control Techniques

Serializability Finish one transaction before starting another

Locking Mechanisms The most common way of achieving

serializationData that is retrieved for the purpose of

updating is locked for the updaterNo other user can perform update until

unlocked

Updates with locking (concurrency control)

Locking Mechanisms Locking level:

Database–used during database updatesTable–used for bulk updatesBlock or page–very commonly usedRecord–only requested row; fairly commonly usedField–requires significant overhead; impractical

Database Lock

Table Lock

Block or Page Lock

Record Lock

Locking Mechanisms Types of locks:

Shared lock (S locks/read locks)○ Allows other transactions to read but not update Allows other transactions to read but not update

a record or other resourcesa record or other resources○ Read but no update permitted. Used when just

reading to prevent another user from placing an exclusive lock on the record

Exclusive lock (X locks/write locks)○ Prevents another transactions from reading and Prevents another transactions from reading and

therefore updating a record until it is locked.therefore updating a record until it is locked.○ No access permitted. Used when preparing to

update

Deadlock

Managing Deadlock Deadlock prevention:

Lock all records required at the beginning of a transaction

Two-phase locking protocol○ Growing phase○ Shrinking phase

May be difficult to determine all needed resources in advance

Deadlock prevention Two-phase locking protocol

Growing phase○ A transaction acquires all the required locks without

unlocking any data○ Once all locks have been acquired, the transaction is in its

locked pointShrinking phase

○ A transaction releases all locks and cannot obtain any new lock

Two-phase locking protocol

Managing Deadlock Deadlock Resolution:

Allow deadlocks to occur nut build mechanisms into the DBMS for detecting and breaking the deadlocks.

The DBMS maintains a matrix of resource usage.○ Indicates what subjects (users) are using what

objects (resources)○ Scanning this matrix: the computer can detect

deadlock if occur○ DBMS resolve deadlock: One of the transactions is

aborted: changes made by the transaction up to the time of deadlock are removed & transaction is restarted when the required resources become available.

Versioning

Optimistic approach to concurrency control Instead of locking Assumption is that simultaneous updates will

be infrequent Each transaction can attempt an update as it

wishes The system will reject an update when it

senses a conflict Use of rollback and commit for this

Figure 13-15 The use of versioning

Better performance than locking

Data Dictionaries and Repositories

Data dictionaryDocuments data elements of a databaseStore metadata/information about the databaseActive: managed by DBMSPassive: managed by the user(s)Part of system catalogSystem catalog

○ System-created database that describes all database objects

○ Table-related data (table names), table creators/owners, column names, data types, etc

Data Dictionaries and Repositories

Information RepositoryStores metadata that describe an organization’s

data and data processing resources, manages the total information processing environment and combines information about an organization's business information and its application portfolio

Information Repository Dictionary System (IRDS)Software tool that is used to manage and control

access to the information repository 3 components of repository system

architecture:Information ModelRepository EngineRepository Database

Figure 13-16 Three components of the repository system architecture

A schema of the repository information

Software that manages the repository objects

Where repository objects are stored

Source: adapted from Bernstein, 1996.

Data Availability Downtime is expensive

Lost business during the outageCost of catching up when service is restoredLegal costsPermanent loss of customer loyalty

How to ensure availabilityHardware failures–provide standby componentsLoss of data–database mirroringHuman Error – SOP, training, documentationMaintenance downtime–automated and non-disruptive

maintenance utilitiesNetwork problems–careful traffic monitoring, firewalls, and

routers

Information in this slides were taken from Modern Database Management Information in this slides were taken from Modern Database Management System, Ninth edition by Jeffrey A.Hoffer, Mary B.Prescott & Heikki Topi. System, Ninth edition by Jeffrey A.Hoffer, Mary B.Prescott & Heikki Topi. AND Database Systems, Design, Implementation & Management by Peter AND Database Systems, Design, Implementation & Management by Peter Rob & Carlos CoronelRob & Carlos Coronel