Concurrency Control on Relational Databases

CONCURRENCY CONTROL ON RELATIONAL DATABASESSeminar: Transaction Processing (Bachelor)SS 2009

Dennis Stratmann

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Concurrency Control on Relational Databases

OUTLINE

Goal and Overview Examine Three Approaches to CC on RD:

1. Predicate-Oriented Concurrency Control 2. Relational Update Transactions

Syntax and Semantics Histories and Final State Serializability Conflict Serializability Extended Conflict Serializability

3. Exploiting Transaction Program Knowledge Transaction Chopping Applicability of Chopping

Summary Questions & Answers


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GOAL AND OVERVIEW

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GOAL AND OVERVIEW

Semantic approach to Concurrency Control Possible to exploit semantic knowledge at

higher abstraction level

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GOAL AND OVERVIEW

Three Approaches to CC on RD: Predicate-Oriented Concurrency Control Relational Update Transactions Exploiting Transaction Program Knowledge


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THREE APPROACHES TO CC ON RD:

1. Predicate-Oriented Concurrency Control

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1. PREDICATE-ORIENTED CC ON RD

Relational Database

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Lock entire Relation

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Lock individual Tuples


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Phantom Problem: Transaction 1:

Transaction 2:

Emp Name Department

Position Salary

Jones Service Clerk 20 000Meier Service Clerk 22 000Paulus Service Manager 42 000Smyth Toys Cashier 25 000Brown Sales Clerk 28 000Albert Sales Manager 38 000

DELETE FROM Emp WHERE Department = ‘Service’ AND Position = ‘Manager’

INSERT INTO Emp VALUES (‘Smith’, ‘Service’, ‘Manager’, 40000)

SELECT Name, Position, SalaryFROM EmpWHERE Department = ‘Service’

UPDATE EmpSET Department = ‘Sales’WHERE Department = ‘Service’AND Position <> ‘Manager’

INSERT INTO EmpVALUES (‘Sone’, ‘Serivce’, ‘Clerk’, 13000)

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Predicate Locking

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Transaction 1: Ca: Department = ‘Service‘ Position =

‘Manager‘

Cb: Name = ‘Smith‘ Department = ‘Service‘ Position = ‘Manager‘ Salary = ‘40000‘

Cc1: Department = ‘Service‘ Position ‘Manager‘

Cc2: Department = ‘Sales‘ Position ‘Manager‘

Cd: Name = ‘Stone‘ Department = ‘Service‘ Position = ‘Clerk‘ Salary = ‘13000‘

DELETE FROM Emp WHERE Department = ‘Service’ AND Position = ‘Manager’

INSERT INTO Emp VALUES (‘Smith’, ‘Service’, ‘Manager’, 40000)

UPDATE EmpSET Department = ‘Sales’WHERE Department = ‘Service’AND Position <> ‘Manager’

INSERT INTO EmpVALUES (‘Sone’, ‘Serivce’, ‘Clerk’, 13000)

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Transaction 2:

Cq: Department = ‘Service‘

Transaction 3:

Cp: Department = ‘Sales‘

Example: H(Ca) H(Cq) ∅ H(Cb) H(Cq) ∅ H(Cc1) H(Cq) ∅ H(Cc2) H(Cq) = ∅ H(Cd) H(Cq) ∅

SELECT Name, Position, SalaryFROM EmpWHERE Department = ‘Service’

SELECT Name, Position, SalaryFROM EmpWHERE Department = ‘Sales’

H(Ca) H(Cp) = ∅ H(Cb) H(Cp) = ∅ H(Cc1) H(Cp) = ∅ H(Cc2) H(Cp) ∅ H(Cd) H(Cp) = ∅

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Scheduler


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2. Relational Update Transactions


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2. RELATIONAL UPDATE TRANSACTIONSSYNTAX AND SEMANTICS

IDM Transaction Model Insertion: iR(C) Deletion: dR(C) Modify:

mR(C1;C2) Semantics is called

effect

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2. RELATIONAL UPDATE TRANSACTIONSSYNTAX AND SEMANTICS

Transaction Equivalence Two IDM Transactions t and t’ are equivalent,

if eff(t) = eff(t’) Written: t t’

Commutativity Rules Simplification Rules

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2. RELATIONAL UPDATE TRANSACTIONSHISTORIES AND FINAL STATE SERIALIZABILITY

A history s is serial, if all Transactions appear strictly one after the other

A history s is Final State Serializable if s s’ for some history s’

FSRIDM denotes class of all Final State Serializable histories

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Example:

t1 = d(3)m(1;2)m(3;4)

t2 = d(3)m(2;3)

s = d2(3)d1(3)m1(1;2)m2(2;3)m1(3;4)

s’

= d(3)m(1;4)m(2;4)m(3;4)

eff(s) = eff(s’

) s s’

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s = d2(3)d1(3)m1(1;2)m2(2;3)m1(3;4)

s / t1t2 or s / t2t1 s FSRIDM

t1 t1‘ = d(3)m(1;2)

s‘

= d2(3)d1(3)m1(1;2)m2(2;3) t1t2

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2. RELATIONAL UPDATE TRANSACTIONSCONFLICT SERIALIZABILITY

A history s for a set T of n transactions is conflict serializable, if s tp(1)...tp(n) using only the Commutativity Rules

CSRIDM denotes class of all Conflict Serializable histories

Conflict Graph G(s) = (T,E) History s CSRIDM, if G(s) is acyclic

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2. RELATIONAL UPDATE TRANSACTIONSCONFLICT SERIALIZABILITY

Consider s = m2(1;2) m1(2;3) m2(3;2)

G(s) is cyclic, so s is not in CSRIDM On the other hand,

s m1(2;3) m2(1;2) m2(3;2) t1 t2

s is in FSRIDM CSRIDM FSRIDM

t1

t2

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2. RELATIONAL UPDATE TRANSACTIONSEXTENDED CONFLICT SERIALIZABILITY

Sometimes, the context in which a conflict occurs can make a difference:Example: Let

s = d1(0) m1(0;1) m2(1;2) m1(2;3) G(s) is cyclic, but s m2(1;2) d1(0) m1(0;1) m1(2;3) t2 t1

Intuitively the conflict involving m1(0;1) does not exist (due to d1(0) ) !

A history s for a set T of n transactions is extended conflict serializable, if Extended Conflict Graph EG(s) = (T,E) is acyclic

ECSRIDM denotes class of all Extended Conflict Serializable histories

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2. RELATIONAL UPDATE TRANSACTIONSEXTENDED CONFLICT SERIALIZABILITY

CSRIDM ECSRIDM FSRIDM

FSRIDM

CSRIDM


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3. Exploiting Transaction Program Knowledge

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3. EXPLOITING TRANSACTION PROGRAM KNOWLEDGE

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TRANSACTION CHOPPING

Transaction Chopping Short Transactions need less locks Short Transactions cause potentially less lock contention

Chopping depends on concurrent Transactions

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Definition of Transaction Chopping Every database operation invoked by the

chopped transactions is contained in exactly one piece, and the order of operation invocations is preserved

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Deadlock / Rollback situation

Atomicity of original Transaction needs to be preserved


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Three types of Transactions:

1. A Transaction updating a single Customer’s Account as well as the corresponding Branch

2. A Transaction reading a Customer’s Account Balance

3. A Transaction comparing the grand Total of all Account Balances with the Sum of the Branch Balances

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t1 = r1(A1)w1(A1)r1(B1)w1(B1)t2 = r2(A3)w2(A3)r2(B1)w2(B1)t3 = r3(A4)w3(A4)r3(B2)w3(B2)t4 = r4(A2)t5 = r5(A4)t6 = r6(A1)r6(A2)r6(A3)r6(B1)r6(A4)r6(A5)r6(B2)

SELECT Balance INTO :oldbalance FROM Accounts WHERE AccountNo = A1;UPDATE Accounts SET Balance = :newbalance WHERE AccountNo = A1;SELECT Total INTO :oldtotal FROM Branches WHERE BranchNo = B1;UPDATE Branches SET TOTAL = :newtotal WHERE Branches = B1;

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TRANSACTION CHOPPING Test if a given chopping is correct with a Chopping Graph Example

t6 = r6(A1)r6(A2)r6(A3)r6(B1)r6(A4)r6(A5)r6(B2) Chop into two pieces:

t61 = r61(A1)r61(A2)r61(A3)r61(B1)t62 = r62(A4)r62(A5)r62(B2)

Corresponding Chopping Graph:

s: siblingc: conflict

A chopping is correct if the associated graph does not contain an sc cycle.

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Further in the example:t1 = r1(A1)w1(A1)r1(B1)w1(B1)

Chop into two pieces:t11 = r1(A1)w1(A1)t12 = r1(B1)w1(B1)

Corresponding Chopping Graph:

Making chopping finer can introduce sc cycles

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APPLICABILITY OF CHOPPING

Applicability of Chopping To apply chopping algorithm, semantic knowledge is necessary Semantic knowledge derived form predicates

Real World Example:

High Level conflict Record-Level conflict

SELECT AccountNo, Balance FROM AccountsWHERE City = ‘Konstanz’

UPDATE Accounts SET Balance = Balance * 1.05WHERE City = ‘Stuttgart’

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Gain chopping relevant information from parameterized SQL statements:

The chopping method is in limited settings ready for practical use, if No control-flow branching is used No loops are used No If-then-else constructs are used

SELECT AccountNo, Balance FROM AccountsWHERE AccountType = ‘savings’ AND City = :x

UPDATE Accounts SET Balance = Balance * 1.05WHERE AccountType = ‘checking’ AND City = :y

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Rewrite SQL statement to a parameter-less statementSELECT AccountNo, Balance FROM AccountsWHERE AccountType = ‘savings’ AND City = :x;

If not found thenSELECT AccountNo, Balance FROM AccountsWHERE AccountTyoe = ‘checking’ AND City = :x;fi;

SELECT AccountNo, Balance FROM AccountsWHERE AccountType = ‘savings’;SELECT AccountNo, Balance FROM AccountsWHERE AccountTyoe = ‘checking’;


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SUMMARY

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SUMMARY

Predicate-Oriented Concurrency Control•Trade-off between locking entire relation and locking individual tuples•NP complete to test Satisfiability

Relational Update Transactions•Commutativity based Serializability (FSRIDM)•Conflict Serializability ([E]CSRIDM)

Exploiting Transaction Program Knowledge •Decomposition of Transactions into small pieces•Only in limited settings ready for practical use

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THANKS FOR LISTENING

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QUESTIONS & ANSWERS

Concurrency Control on Relational Databases

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