Concurrency Control

Alexandra Cristea and Steve Russ

1

Who needs ‘control’?

• large databases are usually shared – by many users, and resources

• it is efficient to allow concurrent access.

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Relevant Concepts for Concurrency Control

• integrity : consistency and correctness• security : ensuring users only do what they

are allowed• recovery : return after an error to a known

correct state

• ISSUE: Concurrent access endangers each of these !!!

3

Level of treatment

• Large and complex topic• Here: logical or conceptual level. • closely following:

– C.J. Date Introduction to Database Systems (8th ed.) Ch.16. The book by Date has an excellent annotated bibliography for each chapter.

– similar treatments in Silberschatz et al., and Connolly & Begg.

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Sources for Learning There are good chapters on each of the main topics associated with concurrency control in the Date book:

Integrity (Chapter 9)Recovery (Chapter 15)Concurrency (Chapter 16)Security (Chapter 17)

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More Sources

• There are similar chapters in the Silberschatz et al. recommended book (Ch.5, 15, 16, 17).

• There are some good sets of notes on the web on these topics – ‘Transaction processing’ or similar.

• Google ‘lost update problem database’ (in UK).

But: better to stick with one source in detail. 6

Integrity

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Database Integrity

• Domains• Constraints• Entity/referential integrity• Assertions

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Four Types of Integrity Rule• Domain Rules: Give legal values for domains.• Attribute Rules: Give legal values for attributes.• Relation Rules: Rules governing single relations (e.g.,

Primary keys must be unique and Non-NULL)• Database Rules: Rules governing interrelationships

between relations (e.g., Foreign Keys must be Primary keys - and therefore Non-NULL).

• SQL provides ways of defining these Rules or Constraints.

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Domains and Constraints• Defining constrains outside the CREATE TABLE data

definition: CREATE DOMAIN domain_name [AS] data_type

[DEFAULT default_option]

[CHECK (search_condition)]

CREATE DOMAIN sex_type AS CHAR

CHECK (VALUE IN (‘M’, ‘F’))

Names of types are reusable.10

Entity Integrity• Entity integrity enforced by naming PRIMARY KEY (i.e., attribute or

set of attributes which should be NOT NULL and UNIQUE). E.g.:CREATE TABLE staff(

staff# number (3),

name char(30),

PRIMARY KEY staff#);• For alternate keys can use NOT NULL and UNIQUE qualifiers after

column attribute name. E.g.:CREATE TABLE fruit(

name char(30) PRIMARY KEY,

supplier char(20) NOT NULL,

country char(20) NOT NULL,

UNIQUE (supplier, country)); 11

Referential Integrity

• defined by FOREIGN KEY or REFERENCES. • Referential action must allow cascading of updates from

parent to child table (+deletes, NULL value , DEFAULT). E.g.:

CREATE TABLE emps(

emp# number(2),

name char(30),

dept# number(2) REFERENCES dept

ON UPDATE CASCADE);

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Assertions

CREATE ASSERTION assertion_name

CHECK (search condition)

CREATE ASSERTION daycheck

CHECK ( (day>0) and (day<=

(select DM.day from

daysinmonth DM where DM.month=month))

Named rules like this are database/ enterprise wide.

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Oracle SQL Limitations

• Note that Oracle 10g 2 does not implement all ISO SQL Integrity Enhancement Features (IEF).– Domains cannot be defined outside CREATE TABLE.– Referential action restricted to ON DELETE CASCADE

or NO ACTION.– Table check constraints can only refer to attributes

within a table.– Named assertions cannot be defined.

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• Note: Integrity is not Security.

• Integrity ensures that the things the users are trying to do are correct.

• Security ensures that things users are doing are only what they are allowed to do.

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Security

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Security vs. Integrity

• Integrity: Ensuring what users are trying to do is correct.

• Security: Ensuring users are allowed to do things they are trying to do.

• Both require rules that users must not violate.

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Database Security Approaches

1. Discretionary Control: Named users, Privileges or access rights to data objects. Distributed control.

2. Mandatory Control: Users have Clearance, Objects have classification levels. Central control.

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Security Mechanisms

• Security sub-systems which checks IDs against security rules.

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SQL Syntax for Security RulesGRANT [privilege-commalist | ALL PRIVILEGES]ON object-nameTO [authorisation_id_list | PUBLIC][WITH GRANT OPTION]Each privilege is one of the following:SELECTDELETEINSERT [ (attribute-commalist)]UPDATE [ (attribute-commalist) ]REFERENCES [ (attribute-commalist) ]

The REFERENCES allows privileges to be granted on named table(s) inintegrity constraints of CREATE TABLE.The GRANT OPTION allows the named users to pass the privileges onto other users.

Audit TrailsWe can’t assume that security will be perfect, i.e. someone might gain unauthorised access.Audit Trails area logs which can track down the infiltrators.Audit trails will contain entries of the form: request (source text) location (physical e.g. terminal id)

user id

date/ time

relations affected (base, tuple, attribute)

old-values

new-values

Knowing that there is an audit trail may deter security hacks.

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Grant and RevokeIf a user A grants privileges to user B, then they can also revoke them e.g.

REVOKE ALL PRIVILEGES ON STATS FROM John;

SQL REVOKE syntaxREVOKE [GRANT OPTION FOR][privilege_list | ALL PRIVILEGES]ON object_nameFROM [authorisation_list|PUBLIC] [RESTRICT|CASCADE]

If RESTRICT option is given then the command is not executed if anydependent rules exist i.e. those created by other users through theWITH GRANT OPTION.CASCADE will force a REVOKE on any dependent rules.

Security Summary• A DBMS security-subsystem enforces security• Access is checked against security rules• Discretionary control rules have a users, privileges and

objects• Mandatory controls have clearance and classification

levels• Audit trails are used to record attempted security

breaches• GRANT/ REVOKE syntax in SQL• We have not dealt with data-encryption, which deals

with the storing and transmission of sensitive data.23

Recovery

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Recovery

• Restoring a database to a known correct state after some failure.

• Database recovery is based on redundancy at the physical level. – Any piece of information can be recovered from

some other stored information, somewhere else.

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Transactions

• A transaction is a logical unit of work, as well as unit of recovery.

• It is broken down into a sequence of atomic operations, which if any fail, the whole transaction is undone.

SELECT | INSERT | …

…

… work …

…

COMMIT | ROLLBACK 26

Transactions• series of database commands w clear semantics

– e.g. transfer of funds from one account to another

• Commit: If nothing fails commit point where the DB should be consistent. All updates are tentative until committed.• Rollback: If any command fails => whole series is undone.

• Any DBMS support these (and lang. e.g. SQL)27

Transaction ExampleBEGIN TRANSACTION UPDATE ACC123 {BALANCE := BALANCE - £100} IF any error occurred THEN GO TO UNDO; END IF; UPDATE ACC456 {BALANCE := BALANCE + £100} IF any error occurred THEN GO TO UNDO; END IF;COMMIT; GO TO FINISH; /*successful end*/UNDO:

ROLLBACK; /*unsuccessful end*/FINISH:

RETURN; 28

Transaction Properties• Atomicity: all or nothing (any error => Rollback, as if nothing happened)• Consistency: a consistent state always leads to another consistent

state• Isolation: a transaction’s updates are hidden until it Commits• Durability: after a Commit, updates persist

These are the ACID properties of transactions. 29

System Recovery

• How does the system recover after a system failure (e.g., power failure) or media failure (e.g., disk crash)?

• In the event of a crash …– Contents of main memory are lost.– Transaction log persists.– At failure, certain transactions will be complete

while others part complete.

• Note that updates are held in memory buffers and written out periodically.

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RecoveryTo recover the state of the database we can use:

• A log file recording every database operation.• Checkpoints recording the state of all active

transactions.– Then: develop an algorithm for transactions to UNDO,– and those that we need to REDO, to effect recovery.– at intervals, the system will:

• Flush its buffers• Write out a checkpoint record to log indicating which

transactions are in progress.

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Five Transaction categories

• The most recent check point record was taken at time tc.

Time tc tf

Transactions

T1

T2

T3

T4

T5System failure (time tf)

Checkpoint(time tc)

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Completed Un-Finished

Cached Written

T2 T1T4

T3 T5

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• CHECKPOINT RECORD: – T3, T5 : undone (rollback possible)– T2, T4 : re-done

• DBMS creates REDO/UNDO list from checkpoint record + system log.

• isolation => – order of recovery not crucial, – only DB should be consistent near tf.

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Concurrency

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Concurrency• Many transactions - at the same time. • Databases shared!

• So: Transactions must be isolated => need of concurrency control to ensure no interference.

• We will look at:– 3 classic problems on concurrent access– Locking mechanism– Deadlock resolution 36

Three classic problemsPB: two (more) transactions read / write on the

same part of the db. Although transactions execute correctly, results

may interleave in diff ways => 3 classic problems.

• Lost Update• Uncommitted Dependency• Inconsistent Analysis

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Lost Update problemTime User 1 (Trans A) User2 (Trans B)

1 Retrieve t2 Retrieve t3 Update t4 Update t567

t : tuple in a table. Trans A loses an update at t4. The update at t3 is lost (overwritten) at t4 by B. 38

Uncommitted DependencyTime User 1 (Trans A) User 2 (Trans B)

1 Update t2 Retrieve t3 Rollback456 Update t7 Update t8 Rollback

2 PBs (T1-3 ; T6-8). One trans is allowed to retrieve/update) a tuple updated by another, but not yet committed.Trans A is dependent at time t2 on an uncommitted change made by Trans B, which is lost on Rollback. 39

Inconsistent AnalysisTime User 1 (Trans A) User 2 (Trans B)

1 Retrieve Acc 1 :Sum = 40

2 Retrieve Acc2 :Sum = 90

3 Retrieve Acc3 :

4 Update Acc3:30 → 20

5 Retrieve Acc1:

6 Update Acc1:40 → 50

7 commit

8 Retrieve Acc3:Sum = 110 (not 120)

Initially: Acc 1 = 40; Acc2 = 50; Acc3 = 30;

Trans A sees inconsistent DB state after B updated Accumulator

=> performs inconsistent analysis.

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Why these problems?• Retrieve : ‘read’ (R) • Update : ‘write’ (W). • interleaving two transactions => 3 PBS: RR – no problem

WW – lost update WR – uncommitted dependency RW – inconsistent analysis

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How to prevent such problems?• locking protocol

– Other approaches : serializability, time-stamping, and shadow-paging. See books.

• IF risk of interference = low => two-phase locking ~ common

approach – although it requires deadlock avoidance!!

• Lock applies to a tuple :– exclusive (write; X) or – shared(read; S).

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Lost Update ‘solved’Time User 1 (Trans A) User2 (Trans B)

1 Retrieve t (get S-lock on t)

2 Retrieve t (get S-lock on t)

3 Update t (request X-lock on t)

4 wait Update t (request X-lock on t)

5 wait wait

6 wait wait

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No update lost but => deadlock

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Uncommitted Dependency solved

Time User 1 (Trans A) User 2 (Trans B)

1 Update t (get X-lock on t)2 Retrieve t (request S-lock on t) -3 wait -4 wait -5 wait Commit / Rollback

(releases X-lock on t)6 Resume: Retrieve t

(get S-lock on t)7 -8

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Inconsistent Analysis ‘solved’Time User 1 (Trans A) User 2 (Trans B)

1 Retrieve Acc1 : (get S-lock)Sum = 40

2 Retrieve Acc2 : (get S-lock)Sum = 90

3 Retrieve Acc3: (get S-lock)

4 Update Acc3: (get X-lock)30 → 20

5 Retrieve Acc1: (get S-lock)6 Update Acc1: (request X-lock)

wait7 Retrieve Acc3:

(request S-lock)wait

waitwaitwait 45

Deadlock

• Deadlock occurs when 2 or more transaction are in a simultaneous wait state.

• It is desirable to conceal deadlocks from the user.

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Deadlock Resolution

• The system must detect and break deadlocks by:

1.Choosing one trans as a victim and rolling it back.2.Timing out the trans and returning an error.3.automatically restarting the transaction hoping not

to get deadlock again.4.Return an error code back to the victim and leaving

it up to program to handle situation..

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Topics covered:• Integrity

– Domains, Constraints, Entity/referential integrity, assertions

• Security– Discretionary, mandatory, audit trails

• Recovery– Transactions, ACID properties

• Concurrency Control– Lost update, uncommitted dependency,

inconsistent analysis, deadlock48

Questions?

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