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Lecture 10: Transactions

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The Setting

Database systems are normally being accessed by many users or processes at the same time. Both queries and modifications.

Unlike operating systems, which support interaction of processes, a DMBS needs to keep processes from troublesome interactions.

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Example: Bad Interaction

You and your domestic partner each take $100 from different ATM’s at about the same time. The DBMS better make sure one

account deduction doesn’t get lost. Compare: An OS allows two people

to edit a document at the same time. If both write, one’s changes get lost.

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ACID Transactions

A DBMS is expected to support “ACID transactions,” processes that are: Atomic : Either the whole process is done

or none is. Consistent : Database constraints are

preserved. Isolated : It appears to the user as if only

one process executes at a time. Durable : Effects of a process do not get

lost if the system crashes.

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Transactions in SQL

SQL supports transactions, often behind the scenes. Each statement issued at the generic

query interface is a transaction by itself.

In programming interfaces like Embedded SQL or PSM, a transaction begins the first time a SQL statement is executed and ends with the program or an explicit transaction-end.

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COMMIT

The SQL statement COMMIT causes a transaction to complete. It’s database modifications are now

permanent in the database.

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ROLLBACK

The SQL statement ROLLBACK also causes the transaction to end, but by aborting. No effects on the database.

Failures like division by 0 or a constraint violation can also cause rollback, even if the programmer does not request it.

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An Example: Interacting Processes

Assume the usual Sells(bar,beer,price) relation, and suppose that Joe’s Bar sells only Bud for $2.50 and Miller for $3.00.

Sally is querying Sells for the highest and lowest price Joe charges.

Joe decides to stop selling Bud and Miller, but to sell only Heineken at $3.50.

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Sally’s Program

Sally executes the following two SQL statements, which we call (min) and (max), to help remember what they do.

(max)SELECT MAX(price) FROM SellsWHERE bar = ’Joe’’s Bar’;

(min) SELECT MIN(price) FROM SellsWHERE bar = ’Joe’’s Bar’;

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Joe’s Program

At about the same time, Joe executes the following steps, which have the mnemonic names (del) and (ins).

(del) DELETE FROM Sells WHERE bar = ’Joe’’s Bar’;

(ins) INSERT INTO Sells VALUES(’Joe’’s Bar’, ’Heineken’,

3.50);

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Interleaving of Statements

Although (max) must come before (min), and (del) must come before (ins), there are no other constraints on the order of these statements, unless we group Sally’s and/or Joe’s statements into transactions.

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Example: Strange Interleaving

Suppose the steps execute in the order (max)(del)(ins)(min).

Joe’s Prices:Statement:Result:

Sally sees MAX < MIN!

2.50, 3.00

(del) (ins)

3.50

(min)

3.50

2.50, 3.00

(max)

3.00

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Fixing the Problem by Using Transactions

If we group Sally’s statements (max)(min) into one transaction, then she cannot see this inconsistency.

She sees Joe’s prices at some fixed time. Either before or after he changes

prices, or in the middle, but the MAX and MIN are computed from the same prices.

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Another Problem: Rollback

Suppose Joe executes (del)(ins), not as a transaction, but after executing these statements, thinks better of it and issues a ROLLBACK statement.

If Sally executes her statements after (ins) but before the rollback, she sees a value, 3.50, that never existed in the database.

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Solution

If Joe executes (del)(ins) as a transaction, its effect cannot be seen by others until the transaction executes COMMIT. If the transaction executes ROLLBACK

instead, then its effects can never be seen.

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Isolation Levels

SQL defines four isolation levels = choices about what interactions are allowed by transactions that execute at about the same time.

How a DBMS implements these isolation levels is highly complex, and a typical DBMS provides its own options.

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Choosing the Isolation Level

Within a transaction, we can say:SET TRANSACTION ISOLATION LEVEL

Xwhere X =

1. SERIALIZABLE2. REPEATABLE READ3. READ COMMITTED4. READ UNCOMMITTED

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Serializable Transactions

If Sally = (max)(min) and Joe = (del)(ins) are each transactions, and Sally runs with isolation level SERIALIZABLE, then she will see the database either before or after Joe runs, but not in the middle.

It’s up to the DBMS vendor to figure out how to do that, e.g.: True isolation in time. Keep Joe’s old prices around to answer

Sally’s queries.

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Isolation Level Is Personal Choice

Your choice, e.g., run serializable, affects only how you see the database, not how others see it.

Example: If Joe Runs serializable, but Sally doesn’t, then Sally might see no prices for Joe’s Bar. i.e., it looks to Sally as if she ran in

the middle of Joe’s transaction.

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Read-Commited Transactions

If Sally runs with isolation level READ COMMITTED, then she can see only committed data, but not necessarily the same data each time.

Example: Under READ COMMITTED, the interleaving (max)(del)(ins)(min) is allowed, as long as Joe commits. Sally sees MAX < MIN.

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Repeatable-Read Transactions

Requirement is like read-committed, plus: if data is read again, then everything seen the first time will be seen the second time. But the second and subsequent reads

may see more tuples as well.

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Example: Repeatable Read

Suppose Sally runs under REPEATABLE READ, and the order of execution is (max)(del)(ins)(min). (max) sees prices 2.50 and 3.00. (min) can see 3.50, but must also see

2.50 and 3.00, because they were seen on the earlier read by (max).

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Read Uncommitted

A transaction running under READ UNCOMMITTED can see data in the database, even if it was written by a transaction that has not committed (and may never).

Example: If Sally runs under READ UNCOMMITTED, she could see a price 3.50 even if Joe later aborts.

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Concurrency Control

T1 T2 … Tn

DB(consistencyconstraints)

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Review

Why do we need transaction? What’s ACID? What’s SQL support for transaction? What’s the four isolation level

SERIALIZABLE REPEATABLE READ READ COMMITTED READ UNCOMMITTED

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Example:

T1: Read(A) T2: Read(A)A A+100 A A2Write(A) Write(A)Read(B) Read(B)B B+100 B B2Write(B) Write(B)

Constraint: A=B

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Schedule A

T1 T2Read(A); A A+100Write(A);Read(B); B B+100;Write(B);

Read(A);A A2;

Write(A);

Read(B);B B2;

Write(B);

A B25 25

125

125

250

250250 250

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Schedule B

T1 T2

Read(A);A A2;

Write(A);

Read(B);B B2;

Write(B);Read(A); A A+100Write(A);Read(B); B B+100;Write(B);

A B25 25

50

50

150

150150 150

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Schedule C

T1 T2Read(A); A A+100Write(A);

Read(A);A A2;

Write(A);Read(B); B B+100;Write(B);

Read(B);B B2;

Write(B);

A B25 25

125

250

125

250250 250

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Schedule D

T1 T2Read(A); A A+100Write(A);

Read(A);A A2;

Write(A);

Read(B);B B2;

Write(B);Read(B); B B+100;Write(B);

A B25 25

125

250

50

150250 150

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Schedule E

T1 T2’Read(A); A A+100Write(A);

Read(A);A A1;

Write(A);

Read(B);B B1;

Write(B);Read(B); B B+100;Write(B);

A B25 25

125

125

25

125125 125

Same as Schedule Dbut with new T2’

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Want schedules that are “good”,regardless of

initial state and transaction semantics

Only look at order of read and writes

Example: Sc=r1(A)w1(A)r2(A)w2(A)r1(B)w1(B)r2(B)w

2(B)

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Sc’=r1(A)w1(A) r1(B)w1(B)r2(A)w2(A)r2(B)w2(B)

T1 T2

Example: Sc=r1(A)w1(A)r2(A)w2(A)r1(B)w1(B)r2(B)w2(B)

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Review

Why do we need transaction? What’s ACID? What’s SQL support for transaction? What’s the four isolation level

SERIALIZABLE REPEATABLE READ READ COMMITTED READ UNCOMMITTED

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Example:

T1: Read(A) T2: Read(A)A A+100 A A2Write(A) Write(A)Read(B) Read(B)B B+100 B B2Write(B) Write(B)

Constraint: A=B

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Schedule D

T1 T2Read(A); A A+100Write(A);

Read(A);A A2;

Write(A);

Read(B);B B2;

Write(B);Read(B); B B+100;Write(B);

A B25 25

125

250

50

150250 150

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However, for Sd:Sd=r1(A)w1(A)r2(A)w2(A)

r2(B)w2(B)r1(B)w1(B)

as a matter of fact, T2 must precede T1

in any equivalent schedule, i.e., T2 T1

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T1 T2 Sd cannot be rearrangedinto a serial

scheduleSd is not “equivalent” to

any serial scheduleSd is “bad”

T2 T1

Also, T1 T2

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Schedule C

T1 T2Read(A); A A+100Write(A);

Read(A);A A2;

Write(A);Read(B); B B+100;Write(B);

Read(B);B B2;

Write(B);

A B25 25

125

250

125

250250 250

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Returning to Sc

Sc=r1(A)w1(A)r2(A)w2(A)r1(B)w1(B)r2(B)w2(B)

T1 T2 T1 T2

no cycles Sc is “equivalent” to aserial schedule(in this case T1,T2)

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Concepts

Transaction: sequence of ri(x), wi(x) actionsConflicting actions: r1(A) w2(A) w1(A)

w2(A) r1(A) w2(A)

Schedule: represents chronological orderin which actions are executed

Serial schedule: no interleaving of actions or transactions

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Definition

S1, S2 are conflict equivalent schedulesif S1 can be transformed into S2 by a series of swaps on non-conflicting actions.

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Definition

A schedule is conflict serializable if it is conflict equivalent to some serial schedule.

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Nodes: transactions in SArcs: Ti Tj whenever

- pi(A), qj(A) are actions in S- pi(A) <S qj(A)

- at least one of pi, qj is a write

Precedence graph P(S) (S is

schedule)

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Exercise:

What is P(S) forS = w3(A) w2(C) r1(A) w1(B) r1(C) w2(A) r4(A) w4(D)

Is S serializable?

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Another Exercise:

What is P(S) forS = w1(A) r2(A) r3(A) w4(A) ?

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Lemma

S1, S2 conflict equivalent P(S1)=P(S2)

Proof:Assume P(S1) P(S2) Ti: Ti Tj in S1 and not in S2

S1 = …pi(A)... qj(A)… pi, qj

S2 = …qj(A)…pi(A)... conflict

S1, S2 not conflict equivalent

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Note: P(S1)=P(S2) S1, S2 conflict equivalent

Counter example:

S1=w1(A) r2(A) w2(B) r1(B) S2=r2(A) w1(A) r1(B) w2(B)

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Theorem

P(S1) acyclic S1 conflict serializable

() Assume S1 is conflict serializable Ss: Ss, S1 conflict equivalent P(Ss) = P(S1)

P(S1) acyclic since P(Ss) is acyclic

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() Assume P(S1) is acyclicTransform S1 as follows:(1) Take T1 to be transaction with no incident arcs(2) Move all T1 actions to the front

S1 = ……. qj(A)…….p1(A)…..

(3) we now have S1 = < T1 actions ><... rest ...>(4) repeat above steps to serialize rest!

T1

T2 T3

T4

TheoremP(S1) acyclic S1 conflict serializable