1 Transaction-Oriented Computing COP 6730. 2 The Temporary Update Problem Problem: T2 reads the invalid “temporary” value. X=80 Y=60 Transfer $5 Deposit

1

Transaction-Oriented Computing

COP 6730

2

The Temporary Update Problem

T1 (Transfer) T2 (Deposit) X Y M N80 60 4 5

Read(X);X := X - N;Write(X); 75 60 4 5

Read(X);T1 failsRecover(X); 80 60 4 5

X := X + M;Write(X); 79 60 4 5

Read(X);X := X - N;Write(X); 74 60 4 5Read(Y);Y := Y + N;Write(Y); 74 65 4 5Correct Answer 79 65 4 5

Problem: T2 reads the invalid “temporary” value.

X=80

Y=60

Transfer $5

Deposit $4

Balance should be: $80 - $5 + $4 = $79

3

The Lost Update Problem

This update is lost

Balance should be: $80 - $5 + $4 = $79.

X=80

Y=60

Transfer $5

Deposit $4

4

The Incorrect Summary Problem

T1 (Transfer) T2 (Sum) Sum W X Y N70 80 60 5

Sum = 0;Read(W);Sum = Sum + W; 70 70 80 60 5

Read(X);X = X - N;Write(X); 70 70 75 60 5

Read(X);Sum = Sum + X;Read(Y);Sum = Sum + Y; 205 70 75 60 5

Read(Y);Y = Y + N;Write(Y); 205 70 75 65 5Correct Answer: 210 70 75 65 5

205 70 + 80 + 60

Inconsistent !

Transactions can be processed concurrently for efficiency. However, they must have the same results as in serial execution

W X Y

5

Outline

• Atomic Action and Flat Transactions.

• Sphere of Control.

• Notations

• Transaction Models

6

ACID Properties

•Atomicity: A transaction’s changes to the state are atomic – either all happen or non happen.

•Consistency: A transaction is a correct transformation of the state.

•Isolation: Even though transaction execute concurrently, it appears to each transaction, T, that other executed either before or after T, but not both.

•Durability: Once a transaction completes successfully, its changes to the state survive failures (transaction’s effects are durable).

A transaction is a collection of actions with the following ACID properties:

Transaction: Atomicity Property

• A transaction is an atomic sequence of actions (e.g., read/write database).

• Each transaction, executed completely, must leave the DB in a consistent state if DB is consistent when the transaction begins.

– Users can specify some simple integrity constraints on the data, and the DBMS will enforce these constraints.

– Beyond this, the DBMS does not really understand the semantics of the data. (e.g., it does not understand how the interest on a bank account is computed).

– Thus, ensuring that a transaction (run alone) preserves consistency is ultimately the user’s responsibility!

8

Disk Writes as Atomic Actions (1)

1. Single disk write:Problem: If there is a power loss in the middle of the

operation, it might happen that the first part of the block is written, the the rest is not.

2. Read-after-Write: First issues a single disk write, then reads the block from disk to verify the correctness of the data.

Problem: There is no provision to return to the initial state.

Atomicity of a disk write operation would mean that either the entire block is correctly transferred to the specified slot, or the slot remains unchanged.

9

3. Duplexed write: Each data block is written to two places on disk

4. Logged write: • The old contents of the block are first read and then

written to a different place.

• Then the block is modified, and eventually written to the old location


511

5

RAM

Observation:

•Even simple operations cannot simply be declared atomic; rather,

•atomicity is a property for which the operations have to be designed and implemented.

10


11

Action Types• Unprotected Actions: They lack all of the ACID

properties except for consistency.– Example: A single disk write.

• Protected Actions: They have the ACID properties.– They do not externalize their result before they are

completely done (i.e., Isolation).– They can roll back if anything goes wrong before the

normal end (i.e., Atomicity and Consistency).– Once they have reached their normal end, what has

happened remains (i.e., Durability).

• Real Actions: These actions affect the real, physical world in a way that is hard or impossible to reverse.– Example: Firing a missile, dispensing money from an

ATM

12

Higher-Level Protected Actions (Transactions)

Since unprotected actions can be undone, they can be included in a higher-level operation (i.e., transaction), which as a whole has the ACID properties.

unproted action

unproted action

unproted action

unproted action

Transaction (protected)

Begin Work

Commit Work

13

Handling Real ActionsThe higher-level operation must make sure that the real actions are executed only if all enclosing protected actions have reached a state in which they will not decide to roll back

BEGIN_WORK

SELECT … /*unprotected action*/

UPDATE … /*unprotected action*/

DRILL_HOLE …

INSERT …

SELECT …

IF (Condition) COMMIT_WORK;

ELSE ROLLBACK_WORK;

Defer execution of real action

Now do it

Don’t do it at all

Note: The ACID properties hold for everything executed between BEGIN_WORK and COMMIT_WORK.

Concurrency Control• Concurrent execution of user programs is essential for

good DBMS performance.

– Since disk accesses are frequent and relatively slow, it is important to keep the cpu humming by working on several user programs concurrently.

• Interleaving actions of different user programs can lead to inconsistency: e.g., check is cleared while account balance is being computed.

• Transaction processing ensures such problems do not arise: users can pretend they are using a single-user system.

Scheduling Concurrent TransactionsDBMS ensures that execution of {T1, ... , Tn} is equivalent to some serial execution T1, ... Tn.

– Before reading/writing an object, a transaction requests a lock on the object, and waits till the DBMS gives it the lock.

– All locks are released at the end of the transaction. (Strict 2-Phase locking protocol)

X T1T2 RW

I have the lockI wait

X T1T2 W

I am done

I can lock now

2PL Locking ProtocolN

umbe

r of l

ocks

acq

uire

d

Time

What if I need the lock again

before commit ?

Strict 2PL2PL

• 2PL offers more concurrency; but it is difficult to implement

Deadlock

X

T1T2

R2W3

I have the lock on X

I wait for X

A solution: T1 or T2 is aborted and restartedA solution: T1 or T2 is aborted and restarted

YW4W1I have the lock on

YI wait for Y

Ensuring Atomicity• DBMS ensures atomicity (all-or-nothing

property) even if system crashes in the middle of a transaction.

• Idea: Keep a log (history) of all actions carried out by the DBMS while executing a set of Xacts:– Write-Ahead Log (WAL) Protocol: Before a change is

made to the database, the corresponding log entry is forced to a safe location. (OS support for this is often inadequate.)

– Rollback: After a crash, the effects of partially executed transactions are undone using the log.

Note: If log entry wasn’t saved before the crash, corresponding change was not applied to database!

19

A Flat Transaction Example: Debit/Credit (1)

exec sql CREATE TABLE accounts(

Aid NUMERIC(9),

Bid NUMERIC(9) FOREIGN KEY REFERENCES branches,

Abalance NUMERIC(10),

filler CHAR(48),

PRIMARY KEY (Aid);

accountsAid Bid Abalance filler

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/*** main program with the invocation environment */

/* global declarations*/

exec sql BEGIN DECLARE SECTION; /* declare working storage */

long Aid, Bid, Tid, delta, abalance; /* account id, branch id, teller id, debit or */

/* credit amount, account balance */

exec sql END DECLARE SECTION; /* front end for the transaction program */

DCApplication() /* */

{read input msg; /* deal with request messages */

exec sql BEGIN WORK; /* start the flat transaction */

Abalance = DoDebitCredit(Bid, Tid, Aid, delta); /* invoke transaction program */

send output msg; /* send response to terminal */

exec sql COMMIT WORK; /* successful end of transaction */

} /* */

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/* subroutine for doing the database accesses defined for TPC debit/credit transaction

long DoDebitCredit(long Bid, long Tid, long Aid, long delta) {

exec sql UPDATE accounts /* apply delta to the account balance

SET Abalance = Abalance + :delta /**/

WHERE Aid = :Aid; /* */

exec sql SELECT Abalance INTO :Abalance /* read new value of balance*/

FROM accounts /* */

WHERE Aid = :Aid /* */

exec sql UPDATE tellers /* apply delta to teller balance */

SET Tbalance = Tbalance + :delta /**/

WHERE Tid = :Tid; /* */

exec sql UPDATE branches /* apply delta to branch balance*/

SET Bbalance = Bbalance + delta /**/

WHERE Bid = :Bid; /* */

exec sql INSERT INTO history (Tid, Bid, Aid, delta, time) /* insert parameters of transaction */

VALUES (:Tid, :Bid, :Aid, :delta, CURRENT) /* into application history */

return(Abalance);

}

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ROLLBACK StatementsDCApplication() /* */

{ receive input message; /* deal with request messages*/

exec sql BEGIN WORK; /* start the flat transaction*/

Abalance = DoDebitCredit(Bid, Tid, Aid, delta); /* invoke transaction program*/

if (Abalance < 0 && delta < 0) /* check if it a debit and account overdrawn */

{ exec sql ROLLABCK WORK; } /* if so: don’t do it */

else /* this the good case: either credit or */

{ /* enough money in account */

send output message; /* send response to terminal*/

exec sql COMMIT WORK; /* successful end of transaction */

}

}ROLLBACK makes sure that all the records are returned to their Previous states.

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Limitations of Flat Transactions (1)

A one-layer control structure will not be able to model application structures that are significantly more complex.

Example1: Trip Planning

• If there are no direct flights between two places, we must book a number of connecting flights.

• If a partially done travel plan is not acceptable, there is no need to give back the reservation on all the flights.

Note: Partial rollback is not possible for flat transactions.

24

Limitations of Flat Transactions (2)

Example 2: Bulk Updates

• At the end of a month, a bank has to modify all of its accounts by crediting or debiting the accumulated interest.

• If the database process crashes after a large number of accounts have been updated, undoing these effects is undesirable.

Note: Partial commit is useful here.

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SPHERES OF CONTROL

Spheres of Control (SoC) are based on a hierarchy of abstract data types (ADTs) which execute atomically

26

Two Varieties of SPHERES OF CONTROL

One is statically established by structuring the system into a hierarchy of ADTs.

The other results from dynamic interactions among SoCs on shared data, which cannot be committed yet.

B1C2

C1B3

B4B5

B2A1A2S

DD is a noncommitable data item.

Dynamically createdfor controlling the commitment of A1

Predefined hierarchyof functions

Dynamic interaction

27

Dependency in Transactions

• Structural Dependency• Dynamic Dependency

28

Structural Dependencies in

Transaction ModelsStructural dependencies reflect the hierarchical organization of the system into ADTs of increasing complexity.

Example: The commit of B3 depends on the commit of A2. The reason is that A2 appears as an atomic action to the outside.

B1C2

C1B3

B4

B5

B2A1

A2

D

S

D is a noncommitable data item.

S

29

Dynamic Dependencies in Transaction Models

Dynamic dependencies arise from the use of shared data.

Example: A2 depends on A1 in the sense that A2 can commit only if A1 does.

B1C2

C1B3

B4

B5

B2A1

A2

DD is a noncommitable data item.

S is dynamically created for controlling the commitment of A1

S is dynamically created for controlling the commitment of A1

30

Dynamic Behavior of SoC (1)

1. Beginning of scenario: At time t, a problem is discovered in the SoC B. Data from D1 is determined to be the case of the problem.

ttime

Problem

31

Dynamic Behavior of SoC (2)

2. Tracing dependencies backward in time:• A dynamic SoC, F, is extended backward in time to contain

the SoC that created the invalid data item D1.• F serves as the recovery environment.

t

Problem

Recoveryenvironment

F

ttime

Problem

32

Dynamic Behavior of SoC (3)3. Again going forward in time to do recovery:

The recovery SoC, F, is expanded forward in time. F must encompass all processes that have become dependent

on any data produced by the process that created D1.

Note: Execution history must be kept for as long as control might still need to be exercised

F

33

State-Transition Diagram for a Flat Transaction

– Flat transactions can be described as state machines,

– When describing phenomena for which it is not possible to define a prior a fixed number of states, this approach is not appropriate.

– We will adapt the SoC model for describing transaction models.

NULL active

abortedcommitted

BEGIN WORK

ROLLBACK WORK

WORKCOMMIT

terminate

terminate

34

Describing Transaction Models

• for creating the events that drive atomic actions, and

• for the conditions under which the rules can take effect.

Transaction models are distinguished by different sets of rules

35

Describing Transaction Models - Example

Dynamically created for controlling the commitment of A1

B1C2

C1B3

B4

B5

B2A1

A2

D

S

D is a noncommitable data item.

• The event ROLLBACK WORK for atomic action B3 can be triggered by the program running inside B3, or by the abort of A2

• The signal COMMIT WORK for B3 is not sufficient to actually commit B3, that can only happen if the condition “A2 is ready to commit” is also true.

36

Graphical Notation for Transaction Models

A B C

T

A C

State indicator of the action’s outcome

Aborted Committed

Begin

Abort Commit

Signal entries for the atomic action to perform a state transition

Eternally unique identifier of the atomic action

Each instance of an atomic action is depicted as a box with

• three entries at the top representing the signals for state transitions the action can receive, and

• two entries at the bottom representing the two (mutually exclusive) final outcomes of the action.

37

Describing Flat TransactionsA B C

System

A C

A B C

T

A C

a) Transaction T is active: An abort of the system transaction will cause it to roll back, too.

A flat transaction is an atomic action with only one structural dependency:

• If the system transaction aborts, the flat transaction is forced to abort, too.

• The system transaction is always in the active state, never commits, and aborts only as a result of a system crash.

• Once a flat transaction has committed, it stays around without any dependencies, only documenting which final result is relate to its name.

A B C

System

A C

A B C

T

A C

A B C

System

A C

A B C

T

A C

b) Termination scenario 1: Transaction T has committed; all of its event ports are deactivated; the final state is highlighted.

c) Termination scenario 2: Same as scenario 1, but T assumes the final abort sate.

Incoming port that cannot receive events, or final state that cannot be assumed

Trigger

Finalstate

38

Defining Transaction Models by Rules (1)

• The <rule id> specifies the signal port this rule is for

• This rule is not activated until the preconditions are fulfilled

<rule id>: <precodition> → <rule modifier list>,

<signal list>,<state transition>.

Wait

Precondition

Signal port

SA(T1)

39


• <signal list> describes which signals are generated as part of the state transition. (The signals are simply the names of rules that are to be activated by the signal).

• <state transition> is essentially redundant, but it is kept for clarity.


<signal list>,<state

transition>.A B C

System

A C

A B C

T

A C

Activate SA(T) is a signal from SA(System)

40


• <rule modifier list> is used to introduce transactional dependencies as they are needed, or to delete dependencies that have become obsolete. <rule modifier> ::= +(<rule id>|<signal>) <rule modifier> ::= - (<rule id>|<signal>) <rule modifier> ::= delete(x), x is an atomic action.

<signal> is the name of the rule to be activated by the signal



transition>.

A B C

System

A C

A B C

T

A C

Trigger+(SA(system)|SA(T))adds transactional

dependency !

41

<rule modifier list> vs <signal list>


<signal list>,<state transition>.

A B C

T1

A C

Signal port

SA(T1)

A B C

T1

A C

A B C

T2

A C

Signal port

SA(T1)

A B C

T1

A C

A B C

T2

A C

Trigger

SB(T2)SB(T2)

+(SA(T1)|SA(T2))+(SA(T1)|SA(T2))

Signal port

SA(T1)

42

Rules for Flat Transactions

SB(T): +(SA(system)|SA(T)), , BEGIN WORK

• The first rule establishes the dependency from the system transaction and then starts the flat transaction itself.

A B C

System

A C

A B C

T

A C

a) Transaction T is active: Abort of the system transaction will cause it to roll back, too.

A B C

System

A C

A B C

T

A C

A B C

System

A C

A B C

T

A C

b) Termination scenario 1: Transaction T has committed; all of its event pots are deactivated; the final state is highlighted.


Trigger

Removethe rulesRemove

the rules



transition>.

Note: No precondition, no signal list

43

Rules for Flat Transactions

SB(T): +(SA(system)|SA(T)), , BEGIN WORK

SA(T): (delete(SB(T)), delete(SC(T))), ,ROLLBACK WORK

SC(T): (delete(SB(T)), delete(SA(T))), ,COMMIT WORK

• The first rule establishes the dependency from the system transaction and then starts the flat transaction itself.

• The other rules specify the effects of the abort and commit events – since both resulting states are final states, the rules pertaining to the terminated transaction must be removed.

A B C

System

A C

A B C

T

A C

a) Transaction T is active: Abort of the system transaction will cause it to roll back, too.

A B C

System

A C

A B C

T

A C

A B C

System

A C

A B C

T

A C

b) Termination scenario 1: Transaction T has committed; all of its event pots are deactivated; the final state is highlighted.


Trigger

Removethe rulesRemove

the rules

44

Flat Transaction with Savepoints (1)

BEGIN WORK(get transaction started) implicit

SAVE WORK: 1

Action

Action

SAVE WORK: 2

Action

SAVE WORK: 3

Action

Action

Action

SAVE WORK: 4

Action

ROLLBACK WORK (2)

Action

Action

SAVE WORK: 5

Action

SAVE WORK: 6

Action

Action

SAVE WORK: 7

Action

Action

ROLLBACK WORK (7)

Action

Action

SAVE WORK: 8

Action

COMMIT WORK

Work “covered” by savepoint number 5

Work “covered” by savepoint number 2

undone

45

Flat Transaction with Savepoints (2)

• A savepoint is established by invoking the SAVE WORK function, which causes the system to record the current state of processing.

– This returns to the application program a handle that can subsequently be used to reestablish (return to) that savepoint.

• A ROLLBACK does not affect the savepoint counter.

– Advantage: Increasing Numbers monotonically allows the complete execution history to be maintained.

– Disadvantage: It may lead to very unstructured programs. There is nothing that prevents the application program, after having generated savepoint number 8, from requesting a rollback to savepoint 4 (see next slide).

46

Unstructured ProgramBEGIN WORK

(get transaction started) implicit SAVE WORK: 1

Action

Action

SAVE WORK: 2

Action

SAVE WORK: 3

Action

Action

Action

SAVE WORK: 4

Action

ROLLBACK WORK (2)

Action

Action

SAVE WORK: 5

Action

SAVE WORK: 6

Action

Action

SAVE WORK: 7

Action

Action

ROLLBACK WORK (7)

Action

Action

SAVE WORK: 8

Action

ROLLBACK WORK (4)undone

There is nothing that prevents the application program, after having generated savepoint number 8, from requesting a rollback to savepoint 4.

“SAVE WORK: 4”

work never happended

“SAVE WORK: 4”

work never happended

47

Graphical Representation of the Savepoint Model (1)

• The basic idea is to regard the execution between two consecutive savepoints as an atomic action in the sense of SoC.

• The completion of a savepoint creates a new atomic action that is dependent on its predecessor.

A B C

System

A C

A B C

S1

A C

Trigger

A B C

S2

A C

Trigger DependencyDependency

SoC

Trigger

48

Graphical Representation of the Savepoint Model (2)

A B C

System

A C

A B C

S1

A C

Trigger

a) Transaction has started, establishing savepoint 1.

A B C

System

A C

A B C

S1

A C

Trigger

b) Next savepoint, S2, has been taken.

A B C

S2

A C

Trigger Trigger

A B C

System

A C

A B C

S1

A C

Trigger

A B C

S2

A C

Trigger

Trigger

A B C

S3

A C

Trigger Trigger

c) Next savepoint, S3, has been taken.

Forbidden state or event

49

The Rules for Savepoint Model

Note:

• The delete clauses in the abort and commit rules look exactly like in the case of flat transactions, and are omitted here.

First Savepoint, S1:

SB(S1) : +(SA(system)|SA (S1)), , BEGIN WORK

SA(ST) : (ST<S1) , , ROLLBACK WORK

SC(S1) : , , COMMIT WORK

SS(S1) : +(SA(S1)|SA (S2)), SB(S2).

ST: The target savepointof the rollback

(2) +(SA(S1)|SA(S2))

(1) SB(S2)

50

The Rules for Savepoint Model

Note:

• The delete clauses in the abort and commit rules look exactly like in the case of flat transactions, and are omitted here.

• During a rollback, all the atomic actions on the way back are aborted.

First Savepoint, S1:

SB(S1) : +(SA(system)|SA (S1)), , BEGIN WORK

SA(ST) : (ST<S1) , , ROLLBACK WORK

SC(S1) : , , COMMIT WORK

SS(S1) : +(SA(S1)|SA (S2)), SB(S2).

Intermediate Savepoint, Sn:

SB(Sn) : , , BEGIN WORK

SA(ST) : (ST<Sn) , SA(Sn-1), ROLLBACK WORK

SC(Sn) : , SC(Sn-1), COMMIT WORK

SS(Sn) : +(SA(Sn)|SA (Sn+1)), SB(Sn+1).

ST : The target savepoint of the rollback

51

Limitation of Savepoint

• All savepoints perish in case of a system crash

• A solution is to make savepoints persistent

the state of the transaction must be kept in durable (persistent) storage.

52

Persistent SavepointsRestart Strategy

•The last unfinished savepoint interval is roll back, but

•the state as of the previous successful persistent savepoint is reestablished.

Potential Issue: Conventional programming languages do not understand transactions: •the data contents will return to the state as of the specified savepoint, but •the local programming language variables will not.

53

CHAINED TRANSACTIONS• Chained transactions are modeled by a

sequence of atomic actions, executed one at a time.

• Each transaction behaves like a flat transaction (i.e., no rollback after commit)

• The commitment of one transaction and the beginning of the next are wrapped together into one atomic operation. The database content remains intact across

the transaction boundaries.

Effect: The amount of work lost after a crash can be minimized.

Rules for Chained Transactions

SB(Cn): (delete(SB(Cn)),+(SA(system)|SA (Cn))),, BEGIN WORK

SA(Cn): (delete(SA(Cn)), delete(SC(Cn))),, ROLLBACK WORK

SC(Cn): (delete(SA(Cn)), delete(SC(Cn))), SB(Cn+1), COMMIT WORK

A B C

System

A C

A B C

C1

A C

A B C

C2

A C

TriggerTrigger

a) The first transaction in the chain has been started.

b) Start of the second one will be triggered by commit of the first one.

A B C

System

A C

A B C

C1

A C

A B C

C2

A C

Trigger

c) The first transaction in the chain has been committed; the second one got started as part of commit of C1. Now the second one is structurally dependent on “system”.

54

55

Chained Transaction v.s. Savepoints

• Since the chaining step irrevocably completes a transaction, rollback is limited to the currently active transaction (Not as flexible as Savepoint)

• The COMMIT allows the application to free locks that it does not later need (Note: Persistent Savepoint does not have this property)

• After a crash, the entire transaction is rolled back irrespective of any savepoints taken so far. The chained transaction schemes, on the other hand, can reestablish the state of the most recent commit.

A B C

System

A C

A B C

C1

A C

A B C

C2

A C

TriggerTrigger

Activetransaction

Committedtransaction

56

Restart Processing in Chained Transactions

From the application’s point of view, the whole chain is likely to be the sphere of control. What should actually happen in case one of the transactions in the chain aborts?

Abort: the application has to determine how to fix that.

A B C

System

A C

A B C

C1

A C

A B C

C2

A C

Trigger

commit

57

Restart Processing in Chained Transactions

From the application’s point of view, the whole chain is likely to be the sphere of control. What should actually happen in case one of the transactions in the chain aborts?

Abort: the application has to determine how to fix that.

Crash: the last transaction, after having been rollback, should be restarted.

A B C

System

A C

A B C

C1

A C

A B C

C2

A CA B C

C1’

A C

A B C

Restart

A C

TriggerTrigger

Trigger

Trigger

Trigger

C1’ is the new instance of C1

New instanceof C1 startsover again

Restart C2Restart C2

Chained Transaction vs. Savepoints

58

Savepoints Persistent Savepoints

Chained Transaction

Rollback Any previous savepoint

Any previous savepoint

Limited to currently active

transaction

RecoveryEntire

transaction is rolled back

Reestablish most recent savepoint

Reestablish the state of most

recent commit

ConcurrencyLocks kept until

transaction commit

Locks kept until transaction

commitFree locks early

59

Nested Transactions• A nested transaction is a tree of subtransactions.

• A subtransaction can either commit or rollback.

– Its commit takes effect only if the parent transaction commits.

– Any subtransaction can finally commit only if the root transaction commits.

Starting at the root. each transaction can create lower-level subtransactions, which are embedded in the sphere of control of the parent. Transactions at the leaf level are flat transactions, except that they lack the durability of non-nested flat transactions.

Nested Transaction - SOC

60

T1

T21

T22

T212

T211

T222

T221

T2122

T2121

T2112

T2111

Any subtransactioncan finally commit onlyif the root transaction

commits

Its commit takeseffect only if the

parent transactioncommits

61

Behavior of Nested Transactions Commit &

RollbackCommit rule: The commit of a

subtransaction makes its results accessible only to the parent transaction.

Rollback rule: The rollback of a subtransaction causes all of its subtransactions to rollback.

– Subtransactions have only A,C, I, but not D.

62

Behavior of Nested Transactions Visibility Rule

• All changes done by a subtransaction become visible to the parent transaction upon the subtransaction’s commit.

• All objects held by a parent transaction can be made accessible to its subtransactions.

• Changes made by a subtransaction are not visible to its siblings, in case they execute concurrently.

63

Rules for Nested Transactions

Note: The arrows labeled “wait” correspond to the precondition clauses in the rules.

SB(Tkn): +(SA(Tk)|SA (Tkn)),, BEGIN WORK

SA(Tkn): , , ROLLBACK WORK

Sc(Tkn): C(Tk) , , COMMIT WORK

A B C

T

A C

A B C

T

A C

A B C

T

A C

A B C

T1

A C

A B C

T2

A C

A B C

T11

A C

A B C

T1

A C

SystemSystem

System

TriggerTrigger

Trigger Wait

Wait

Wait

a) Root transaction T is running.

b) Subtransaction T1 has been started.

c) T1 has created subtransaction T11, and after that the root transaction starts another subtransaction, T2.

Wait

Tk is the parent of Tkn

64

Using Nested TransactionStrong relationship between modularization in software engineering and the nested transaction mechanism.

– Modular design takes care of the application structure and encapsulates local (dynamic) data structures;

– the transactions make sure that the global data used by these modules are isolated and recover with the same granularity. Note: Database is a very

large global variable

65

Transactional C

• Transactional C (IBM) is a programming language supported by the Encina TP monitor.

• The run-time system of Transactional C supports the notion of nested transactions.

66

Emulating Nested Transaction by

Savepoints

Strategy: • A savepoint is generated at the beginning of each subtransaction • rolling back to a savepoint has the same effect as an abort of the

corresponding subtransaction.

Savepoint generatedat beginning of

each subtransaction

Rollback to savepoints121 has the effectof aborting Tk121

67

Limitations of the Emulation of Nesting by Savepoints (1)

– Reestablishing the state of the savepoint associated with a transaction can affect arbitrary subtransactions, rather then only the subtree of the aborting subtransaction.

• The emulations is limited to systems where everything within a top-level transaction is executed sequentially.Reason:

– If subtransactions are allowed to execute in parallel, the nesting order will no longer be monotonically mapped onto the sequence of savepoints.

68

Limitations of the Emulation of Nesting by Savepoints (2)

• In nested transactions, subtransactions inherit locks from their parent transactions, and parent transactions counter-inherit locks acquired by their subtransactions. This mechanism cannot be emulated by savepoints.

Reason: There is only one flat transaction in using savepoints.

69

Distributed Transactions• A distributed transaction is typically a flat

transaction that runs in a distributed environment.

• The decomposition into distributed transactions does not reflect a hierarchical structure in the programs to be executed, but is induced by the placement of the data in the network.

• In a distributed transaction, if a subtransaction commits, it forces all other subtransactions to commit.

Note: By comparison, in a nested transaction, this is simply a local commit of that subtransactions.

• Distributed subtransactions normally cannot roll back independently. Their decision to abort affects the entire transaction.

70

Multi-Level Transactions

A B C

T

A C

A B C

N

A C

Trigger

a) Root transaction T is running.

b) Subtransaction N has been started.

A B C

System

A C

Trigger

A B C

T

A C

A B C

System

A C

Trigger

A B C

N

A C

A B C

CN

A C

c) Subtransaction N has committed and has installed its compensation transaction, CN, that will get started if T aborts. CN must commit.

Trigger

N can commit independently of T, When it does so;

however, CN enter the scence

N can commit independently of T, When it does so;

however, CN enter the scence

CN is compensating transaction for N. It can

semantically reverse what N has done

CN is compensating transaction for N. It can

semantically reverse what N has done

Abort of T is unconditionally

linked to the commit of CN

Abort of T is unconditionally

linked to the commit of CN

71

Multi-Level Transactions vs

Nested Transactions

A B C

T

A C

A B C

System

A C

Trigger

A B C

N

A C

A B C

CN

A C

Trigger

A B C

T

A C

A B C

T1

A C

A B C

T2

A C

A B C

T11

A C

System

TriggerTrigger Wait

Wait

Wait

T2 does not havethe durability

property

Precommit: N hasthe durability

property

Nested transactionMulti-level transaction

72

Rules for Multi-Level Transactions

• Rules for subtransaction N:

SB(N): , , BEGIN WORK

SA(N): , , ROLLBACK WORK

SC(N): +(SA(T)|SB(CN)), SB(CN), COMMIT WORK

• Rules for the compensating translation CN:

SB(CN): +(SC(restart)|SB(CN’)), , BEGIN WORK

SA(CN): , SB(CN’), ROLLBACK WORK

SC(CN): delete(CN’), , COMMIT WORK

Restart: A system restart transaction runs after an abort caused by some internal malfunction

Note: CN’ is an instance of CN. It ensures that the compensation continues after restart.

73

Advantage & Disadvantage of Multi-

Level Transactions•Advantage: Multi-level transactions are

nested transactions with the ability to precommit the results of subtransactions, and therefore improve concurrency.

•Disadvantage: The compensation actions can be very expensive.

Note: Since rollback is not frequent, the advantages of having smaller units of commitment control outweigh the cost of compensation.

Summary: Transaction Models

74

Flat Transaction

SavepointPersistent Savepoint

Chained Transaction

Multilevel Transaction

Nested Transaction

Support partial

rollback

Support partial

rollback

Minimize lost work in case

of system crash

Minimize lost work in case

of system crash

Improve concurrency

Improve concurrency

Support structured

programming

Support structured

programming

Improve concurrency

Improve concurrency

75

Transaction Processing Context

Programs frequently use contextual information in addition to the input parameters; this information is called context and is (potentially) modified every time the program is invoked.

f(input_message, context) {output_message, context’}

:a

Computation

76

Transaction Processing Context Example

exec sql declare cursor x select a, b, c from rel_a where d = 10 order by a ascending; open cursor x;

do { exec sql fetch next x into :a, :b, :c; /* perfrom computation */

} while (sqlcode == 0);

exec sql close cursor x;

Private context: The cursor position is a context that is private to the program.

Global context: The contents of the database itself determines which “next” tuple can be retrieved.

a b c d

x101010101010

379

121621

:c:b

77

COMPUTE INTERESTS

• If all accounts are updated within one transaction, there is no need for maintaining context

Reason: If it fails, the same thing can be done over again (i.e., it is context-free)

• Splitting the job up into a sequence of transactions requires keeping context in durable memory

78

COMPUTE INTERESTS

ComputeInterest (){ read (interest_rate);

for (account_no = 1; account_no <= 1,000,000; account_no++){SingleAccount(interest_rate, account_no);}

reply (“done”)};

SingleAccount (interest_rate, account_no){ BEGIN WORK

/*do account update*/COMMIT WORK;return (“OK”);

} This transaction is context-freeBecause the next account number

is passed in the input message

The surrounding program needsto keep the context just in case

something happens along the way

79

DURABLE CONTEXT

Context can be volatile or durable:

– An end-of-file pointer is volatile context because it needs not be recovered.

– The context that says how far the sequence of ComputeInterest transactions has gotten must be durable because the program (reinstantiated version) and the database are out of synch after a crash.

80

THE MINI BATCH (1)A solution to the ComputeInterest problem:

– Executing a sequence of transactions, each of them updating only a small number of accounts (called mini batch).

– The application maintains its context as a database record.

n-2

0 1 … n-1 n n+1 … i stepsize …

Accounts | |

BATCHCONTEXT

Last_account_donePROCESS Note: Isolation is

guaranteed only for the tuples the step transaction is accessing.

Database

81

THE MINI BATCH (2)while (last_account_done < max_account_no)

{ EXEC SQL BEGIN WORK; /* initiate next mini-batch */

EXEC SQL UPDATE accounts /* compute current mini-batch */ SET account_total = account_total * (1+interest_rate) WHERE account_no

BETWEEN :last_account_done + 1 AND :last_account_done + :stepsize;

EXEC SQL UPDATE batchcontext /* update context */ SET last_account_done = last_account_done +

stepsize;

EXEC SQL COMMIT WORK;

last_account_done = last_account_done + stepsize; /* next mini-batch */ }

0 1 … n-1 n n+1 … i stepsize …

Accounts | |

Last_account_doneLast_account_done Last_account_done + stepsize

Last_account_done + stepsize

82

Mini-batch is not Strictly Atomic

• Mini-batch does not achieve strict atomicity for the entire computation

• Nevertheless, it is suitable for the ComputeInterest application because the interests must eventually be computed (i.e., transaction eventually commits)

• Commit cannot always be guaranteed for other types of long-lived transactions– Examples include many engineering design

and office automation applications

83

LONG-LIVED TRANSACTIONSGeneral Requirements

1. Minimize lost work: It must be possible to split up bulk transactions in order to control the amount of lost work in case of a system crash.

2. Recoverable computation: There must be ways to temporarily stop the computation without having to commit the results (ACID has no notion of “suspending” a transaction).

3. Explicit control flow: Under all failure conditions, it must be possible to either proceed along the pre-specified path or remove from the system what has been done so far.

84

SAGAS

Saga is an extension of the notion of chained transactions.

1. It defines a chain of transactions as a unit of control.

2. It uses the compensation idea from multi-level transactions to make the entire chain atomic.

Added to Chained Transaction 85

SAGAS - Properties• Commit case: S1, S2, …, Si, … , Sn-1, Sn

• Rollback scenario: S1, S2, …, Sj(abort), CSj-1… , CS2, CS1

A B C

A C

A B C

A C

A B C

A C

A B C

A C

A B C

A C

A B C

A C

System S1 S2 S3

CS1 CS2

TriggerTrigger

Trigger

A backward chain of compensating transactions is established as the original chain proceeds in a forward direction.

86

COOPERATING TRANSACTIONS (1)

Cooperative transactions allow for explicit interactions among collaborating users on shared (design) objects.

Transaction A

Transaction Bcreate object X

X

do some design work

show meobject X

granted

Use object X

Give back X

Time

Preliminary,must not

be modified

B may resumecomputation

on X

87

COOPERATING TRANSACTIONS (2)

• Prerelease upon request:

– object X is isolated until the surrounding SoC has decided to commit.

– However, there may be special transactions that are allowed to access it without creating a commit dependency on it.

• Explicit return:

A transaction T that selectively releases commitment control knows:

– who has access to the object

– what kind of access is requested to the object, and

– T gets informed as soon as the object is returned to its original SoC.


88

Savepoints

Flattransaction

Persistentsavepoints

Chainedtransaction

Single layerof control

Can rollbackto a

savepoint

Reestablishlast savepoint

after recovery – Minimize lost work in case of system crash

Free locks early


89

Savepoints

Flattransaction

Persistentsavepoints

Chainedtransaction

NestedTransaction

MultilevelTransaction

Supportsmodularization

in softwareengineering

Precommit allowsearly release

of locks

SAGAS

Chained transactionwith compensating

transactions


90

Transaction1

Transaction2

May IUse “X”

CooperatingTransaction

I am donewith “X”

I know howTransaction 2

uses “X”

Documents

1 Transaction-Oriented Computing COP 6730. 2 The Temporary Update Problem Problem: T2 reads the invalid “temporary” value. X=80 Y=60 Transfer $5 Deposit