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Transaction Management Overview
Chapter 16
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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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.
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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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.
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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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.
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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Example

Consider two transactions (Xacts):
T1:
T2:

BEGIN A=A+100, B=B-100 END
BEGIN A=1.06*A, B=1.06*B END
Transfer $100
from B’s account
to A’s account
Crediting both
accounts with a
6% interest
payment
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.
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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Example (Contd.)

Consider a possible interleaving (schedule):
T1:
T2:
A=A+100,
B=B-100
A=1.06*A,
B=1.06*B
The $100 transfer
amount is given
 This is OK. But what about:
interest payment twice
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:
T2:
R(A), W(A),
R(B), W(B)
R(A), W(A), R(B), W(B)
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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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.)
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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Anomalies with Interleaved Execution

Reading Uncommitted Data (WR Conflicts, “dirty
reads”):
T1:
T2:

R(A), W(A),
R(B), W(B), Abort
R(A), W(A), C
Unrepeatable Reads (RW Conflicts):
T1:
T2:
R(A),
R(A), W(A), C
R(A), W(A), C
Unrepeatable read
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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Anomalies (Continued)

Overwriting Uncommitted Data (WW Conflicts):
T1:
T2:
W(A),
W(B), C
W(A), W(B), C
Isolation: Even though transactions execute
concurrently, it appears to each transaction,
T, that other executed either before or
after T, but not both.
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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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.)
I have
the lock
I wait
T2
W
X
R
T1
I can lock
now
T2
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
W
I am
done
X
T1
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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.
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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2PL Locking Protocol
2PL Locking Protocol is sufficient and
more efficient
Number of locks acquired


2PL
What if I need
the lock again
before commit ?
Strict 2PL
Time
2PL offers more concurrency; but it is difficult to
implement
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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Deadlock
I wait
for X
X
R2
W3
T2
I have the lock
on Y
I have the lock
on X
W1
T1
Y
W4
I wait
for Y
A solution: T1 or T2 is aborted and restarted
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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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.
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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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.
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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Buffer Pool
Can 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 Management Systems 3ed, R. Ramakrishnan and J. Gehrke
Application
Buffer
Pool
Database
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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).
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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Recovering From a Crash
There 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)
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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Recovery Example
Time
T1
T4
Need REDO
T2
T3
T5
Need UNDO
Checkpoint
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
Crash
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Recovering From a Crash
Some care must be taken to handle
the case of a crash occurring during
the recovery process!
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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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.
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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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 policy
90 – 100:
A
Significantly above average effort
80 – 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
Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke
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