transaction management overview

Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke 1

Transaction Management Overview

Chapter 16


Transactions Concurrent execution of user programs is essential

for good DBMS performance. Because disk accesses are frequent, and relatively slow, it

is important to keep the cpu humming by working on several user programs concurrently.

A user’s program may carry out many operations on the data retrieved from the database, but the DBMS is only concerned about what data is read from and written to the database.

A transaction is the DBMS’s abstract view of a user program: a sequence of reads and writes.


Concurrency in a DBMS Users submit transactions, and can think of each

transaction as executing by itself. Concurrency is achieved by the DBMS, which interleaves

actions (reads/writes of DB objects) of various transactions. Each transaction must leave the database in a consistent

state if the DB is consistent when the transaction begins.• DBMS will enforce some ICs, depending on the ICs

declared in CREATE TABLE statements.• 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).

Issues: Effect of interleaving transactions, and crashes.


Atomicity of Transactions A transaction might commit after completing all its

actions, or it could abort (or be aborted by the DBMS) after executing some actions.

A very important property guaranteed by the DBMS for all transactions is that they are atomic. That is, a user can think of a Xact as always executing all its actions in one step, or not executing any actions at all. DBMS logs all actions so that it can undo the actions of

aborted transactions.


Example

T1: BEGIN A=A+100, B=B-100 ENDT2: BEGIN A=1.06*A, B=1.06*B END

Consider two transactions (Xacts):

There is no guarantee that T1 will execute before T2 or vice-versa, if both are submitted together. However, the net effect must be equivalent to these two transactions running serially in some order.

Transfer $100 from B’s

account to A’s account

Crediting both accounts with a

6% interest payment


Example (Contd.) Consider a possible interleaving (schedule):

T1: A=A+100, B=B-100 T2: A=1.06*A, B=1.06*B

This is OK. But what about:T1: A=A+100, B=B-100 T2: A=1.06*A, B=1.06*B

The DBMS’s view of the second schedule:

T1: R(A), W(A), R(B), W(B)T2: R(A), W(A), R(B), W(B)

The $100 transfer amount is given

interest payment twice


Scheduling Transactions Serial schedule: Schedule that does not interleave

the actions of different transactions. Equivalent schedules: For any database state, the

effect (on the set of objects in the database) of executing the first schedule is identical to the effect of executing the second schedule.

Serializable schedule: A schedule that is equivalent to some serial execution of the transactions.

(Note: If each transaction preserves consistency, every serializable schedule preserves consistency.)


Anomalies with Interleaved Execution Reading Uncommitted Data (WR Conflicts, “dirty

reads”):

Unrepeatable Reads (RW Conflicts):

T1: R(A), W(A), R(B), W(B), AbortT2: R(A), W(A), C

T1: R(A), R(A), W(A), CT2: R(A), W(A), C

Unrepeatable read


Anomalies (Continued) Overwriting Uncommitted Data (WW Conflicts):

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

T1: W(A), W(B), CT2: W(A), W(B), C


Isolation Property

DBMS 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 2PL locking protocol.)

X T1T2 RW

I have the lockI wait

X T1T2 W

I am done

I can lock now


Lock-Based Concurrency Control

Each Xact must obtain an S (shared) lock on object before reading, and an X (exclusive) lock on object before writing.

All locks held by a transaction are released when the transaction completes

If an Xact holds an X lock on an object, no other Xact can get a lock (S or X) on that object.


2PL Locking Protocol 2PL Locking Protocol is sufficient and

more efficient

Num

ber o

f loc

ks a

cqui

red

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 restarted

YW4W1I have the lock

on YI wait for Y


Aborting a Transaction If a transaction Ti is aborted, all its actions have to be

undone. Not only that, if Tj reads an object last written by Ti , Tj must be aborted as well!

Most systems avoid such cascading aborts by releasing a transaction’s locks only at commit time (i.e., Strict 2PL) If Ti writes an object, Tj can read this only after Ti commits.

In order to undo the actions of an aborted transaction, the DBMS maintains a log in which every write is recorded. This mechanism is also used to recover from system crashes: all active Xacts at the time of the crash are aborted when the system comes back up.


The Log The following actions are recorded in the log:

Ti writes an object: the old value and the new value.• Log record must go to disk before the changed page! (WAL

protocol) Ti commits/aborts: a log record indicating this action.

Log records are chained together by Xact id, so it’s easy to undo a specific Xact.

Log is often duplexed and archived on stable storage. All log related activities (and in fact, all CC related

activities such as lock/unlock, dealing with deadlocks etc.) are handled transparently by the DBMS.


Buffer PoolCan the changes made to an object O in the buffer pool be written to disk before the transaction commits ?Steal approach: Such write are executed by the replacement policy of the buffer pool (i.e., another transaction needs to bring in a page)Force approach: When a transaction commits, all the changes it has made to objects in the buffer pool are immediately forced to disk.

Database

Buffer Pool

Application


Force Approach Advantage: Recovery after crash is simple

No need to undo the changes of an aborted transaction No need to redo the changes of a committed transaction

Disadvantage: There might not be enough pages for a large transaction

(e.g., payroll processing) It incurs excessive disk I/Os. (e.g., popular pages will be

written to disk frequently by different transactions)

Most systems use Steal approach:The in-memory copy of the page can be successively modified

by different transactions and written to disk only by the buffer replacement policy (e.g., LRU).


Recovering From a CrashThere are 3 phases in the Aries recovery algorithm:

Analysis: Scan the log forward (from the most recent checkpoint) to identify

• all Xacts that were active, and • all dirty pages in the buffer pool at the time of the crash.

Redo: Redo all updates to dirty pages in the buffer pool, as needed, to ensure that all logged updates are in fact carried out and written to disk. (restores the database state to what it was at the time of the crash)

Undo: The writes of all Xacts that were active at the crash are undone (by restoring the before value of the update, which is in the log record for the update), working backwards in the log. (makes sure the database reflects only the actions of committed transactions)


Recovery ExampleTime

Checkpoint Crash

T1

T4

T2

T3

T5

Need REDO

Need UNDO


Recovering From a Crash

Some care must be taken to handle the case of a crash occurring during the recovery process!


Summary Concurrency control and recovery are among the

most important functions provided by a DBMS. Users need not worry about concurrency.

System automatically inserts lock/unlock requests and schedules actions of different Xacts in such a way as to ensure that the resulting execution is equivalent to executing the Xacts one after the other in some order.

Write-ahead logging (WAL) is used to undo the actions of aborted transactions and to restore the system to a consistent state after a crash. Consistent state: Only the effects of commited Xacts seen.


TEST 2 Time: May 4th, 2009 10:00am – 11:30am Materials: Chapters 7, 8, 12, 16, 19 How to prepare for the test

Study the Powerpoint slides Review the homework assignments Practice the SQL in the text book For Chapter 7, you do not need to memorize the syntax

Grading policy90 – 100: A Significantly above average effort80 – 89.99: B Above average effort 70 – 79.99: C Average effort (e.g., studying 70% of materials)60 – 69.99: D Need more effort

transaction management overview

Documents