Chapter 17
Introduction to Transaction Processing
Concepts and Theory
17.1 - 17.3 p 551-563
Elmasri and Navathe, Fundamentals of Database Systems, Fourth Edition
Copyright © 2004 Pearson Education, Inc.
Note
These slides have been edited (improved by adding slides,
figures and symbols, and in minor ways) by Dr.
JDBrownsmith
Chapter Outline
1 Introduction to Transaction Processing
2 Transaction and System Concepts
3 Desirable Properties of Transactions
4 Characterizing Schedules based on Recoverability
5 Characterizing Schedules based on Serializability
6 Transaction Support in SQL
Chapter 17-4
17.1.1 Introduction to Transaction
Processing
Single-User System: At most one user at a time can
use the system.
Multiuser System: Many users can access the system
concurrently.
Concurrency
– Interleaved processing: concurrent execution of
processes is interleaved in a single CPU
– Parallel processing: processes are concurrently
executed in multiple CPUs.
Chapter 17-5
Figure 17.1 Interleaved processing versus
parallel processing of concurrent
transactions.
Chapter 17-6
17.1.2 Introduction to Transaction
Processing
A Transaction: logical unit of database processing that
includes one or more database access operations (read
-retrieval, write - insert or update, delete).
A transaction (set of operations) may be stand-
alone specified in a high level language like SQL
submitted interactively, or may be embedded within a
program.
Transaction boundaries: Begin and End transaction.
An application program may contain several
transactions separated by the Begin and End
transaction boundaries.
Chapter 17-7
Whoa
Chapter 17-8
Postgres SQL BEGIN
optional keywords
BEGIN [ WORK | TRANSACTION ] ;
BEGIN initiates a transaction block.
All statements after BEGIN command will be executed in a single
transaction until an explicit COMMIT or ROLLBACK is given.
By default (without BEGIN), PostgreSQL executes transactions in
"autocommit" mode.
That is, each statement is executed in its own transaction; a
commit is implicitly performed at the end of the statement
if execution was successful, otherwise a rollback is done.
Chapter 17-9
Postgres BEGIN
BEGIN is a PostgreSQL language extension.
There is no explicit BEGIN command in the SQL standard;
In the SQL standard, transaction initiation is always implicit.
and transaction termination is either with a COMMIT or
ROLLBACK statement.
Chapter 17-10
Pseudocode Example
BEGIN;
// move $$$ from account A to account B
UPDATE account A;
UPDATE account B;
if (everything worked fine)
then COMMIT;
else ROLLBACK;
ends the transaction
Chapter 17-11
Recall: Basic Definitions
Database System: The DBMS software together with the data
itself. Sometimes, the applications are also included.
database system
database
Application DBMS data
catalog
e.g., the student records database system
Chapter 17-12
Introduction to Transaction Processing
database
Simple model of a database (for purposes
of discussing transactions): data
catalog
A database - collection of named data items
Granularity of data - the size of a data item
Chapter 17-13
Introduction to Transaction Processing
DBMS
Buffer Manager
Chapter 17-14
Introduction to Transaction Processing
Basic operations are read and write
– read_item(X): Reads a database item named X into a
program variable. To simplify our notation, we assume
that the program variable is also named X.
– write_item(X): Writes the value of program variable X
into the database item named X.
database
read_item(X)
Application
DBMS write_item(X) data
catalog
Chapter 17-15
Introduction to Transaction Processing
READ AND WRITE OPERATIONS:
Basic unit of data transfer from the disk to the
computer main memory is one block. In general, a
data item (what is read or written) will be the field
of some record in the database, although it may be a
larger unit such as a record or even a whole block.
database
read_item(X)
Application
DBMS write_item(X) data
catalog
Chapter 17-16
Introduction to Transaction Processing
read_item(X) command includes the following
steps:
2. Find the address of the disk block that contains item X.
3. Copy that disk block into a buffer in main memory (if that
disk block is not already in some main memory buffer).
4. Copy item X from the buffer to the program variable named X.
1.
database
Application
code DBMS
data
3. memory 2. catalog
memory buffer
Chapter 17-17
Introduction to Transaction Processing
write_item(X) command includes the following
steps:
2. Find the address of the disk block that contains item X.
3. Copy that disk block into a buffer in main memory (if that
disk block is not already in some main memory buffer).
4. Copy item X from the program variable named X into its
correct location in the buffer.
5. Store the updated block from the buffer back to disk (either
immediately or at some later point in time).
1.
database
Application
code DBMS
2.
data
memory
3. memory catalog
buffer 4.
Chapter 17-18
Figure 17.2 Two sample transactions. (a) Transaction T1.
(b) Transaction T2.
Chapter 17-19
Introduction to Transaction Processing
Why Concurrency Control is needed:
The Lost Update Problem.
This occurs when two transactions that access the same
database items have their operations interleaved in a
way that makes the value of some database item
incorrect.
Chapter 17-20
Figure 17.3 Some problems that occur when concurrent
execution is uncontrolled.
(a) The lost update problem.
Chapter 17-21
Introduction to Transaction Processing
Why Concurrency Control is needed:
The Temporary Update (or Dirty Read) Problem.
This occurs when one transaction updates a database
item and then the transaction fails for some reason
(see Section 17.1.4).
The updated item is accessed by another transaction
before it is changed back to its original value.
Chapter 17-22
Figure17.3 (continued) Some problems that occur when
concurrent execution is uncontrolled.
(b) The temporary update problem.
Chapter 17-23
Introduction to Transaction Processing
Why Concurrency Control is needed (cont.):
The Incorrect Summary Problem .
If one transaction is calculating an aggregate
summary function on a number of records while other
transactions are updating some of these records, the
aggregate function may calculate some values before
they are updated and others after they are updated.
Chapter 17-24
Figure17.3 (continued) Some problems that occur when
concurrent execution is uncontrolled.
(c) The incorrect summary problem.
Chapter 17-25
Introduction to Transaction Processing
Why recovery is needed:
(What causes a Transaction to fail)
1. A computer failure (system crash):
A hardware or software error occurs in the computer
system during transaction execution. If the hardware
crashes, the contents of the computer’s internal memory
may be lost.
Chapter 17-26
Introduction to Transaction Processing
Why recovery is needed:
(What causes a Transaction to fail)
2. A transaction or system error :
Some operation in the transaction may cause it to fail,
such as integer overflow or division by zero.
Transaction failure may also occur because of erroneous
parameter values or because of a logical programming
error. In addition, the user may interrupt the
transaction during its execution.
Chapter 17-27
Introduction to Transaction Processing
Why recovery is needed
(What causes a Transaction to fail)
3. Local errors or exception conditions detected by the
transaction:
certain conditions necessitate cancellation of the
transaction. For example, data for the transaction may
not be found. A condition, such as insufficient account
balance in a banking database, may cause a
transaction, such as a fund withdrawal from that
account, to be canceled.
a programmed abort in the transaction causes it to
fail.
Chapter 17-28
Introduction to Transaction Processing
Why recovery is needed
(What causes a Transaction to fail)
4. Concurrency control enforcement:
The concurrency control method may decide to abort
the transaction, to be restarted later, because it violates
serializability or because several transactions are in a
state of deadlock (see Chapter 18).
Chapter 17-29
Introduction to Transaction Processing
Why recovery is needed
(What causes a Transaction to fail)
5. Disk failure:
Some disk blocks may lose their data because of a read
or write malfunction or because of a disk read/write
head crash. This may happen during a read or a write
operation of the transaction.
Chapter 17-30
Introduction to Transaction Processing
Why recovery is needed
(What causes a Transaction to fail)
6. Physical problems and catastrophes:
This refers to an endless list of problems that includes
power or airconditioning failure, fire, theft, sabotage,
overwriting disks or tapes by mistake, and mounting
of a wrong tape by the operator.
Chapter 17-31
17.2 Transaction and System Concepts
A transaction is an atomic unit of work that is either
completed in its entirety or not done at all. For
recovery purposes, the system needs to keep track of
when the transaction starts, terminates, and commits
or aborts.
Transaction states:
Active state
Partially committed state
Committed state
Failed state
Terminated State
Chapter 17-32
Figure17.4 State transition diagram illustrating the
states for transaction execution.
Chapter 17-33
DBMS Components
DBMS
Buffer Manager
Recovery Manager
Chapter 17-34
Transaction and System Concepts
Recovery manager keeps track of the DBMS
following operations:
begin_transaction: This marks the beginning of
transaction execution.
read or write: These specify read or write operations
on the database items that are executed as part of a
transaction.
Chapter 17-35
Transaction and System Concepts
Recovery manager keeps track of the DBMS
following operations:
end_transaction: This specifies that read and write
transaction operations have ended and marks the end
limit of transaction execution.
At this point it may be necessary to check whether
the changes introduced by the transaction can be
permanently applied to the database or whether the
transaction has to be aborted because it violates
concurrency control or for some other reason. ("Pre
commmit")
Chapter 17-36
Transaction and System Concepts
DBMS
Recovery manager keeps track of the
following operations (cont):
commit_transaction: This signals a successful end of the
transaction so that any changes (updates) executed by
the transaction can be safely committed to the database
and will not be undone.
rollback (or abort): This signals that the transaction has
ended unsuccessfully, so that any changes or effects that
the transaction may have applied to the database must
be undone.
Chapter 17-37
Transaction and System Concepts
DBMS
Recovery techniques use the
following operators:
undo: Similar to rollback except that it applies
to a single operation rather than to a whole
transaction.
redo: This specifies that certain transaction
operations must be redone to ensure that all the
operations of a committed transaction have been
applied successfully to the database.
Chapter 17-38
Figure17.4 State transition diagram illustrating the
states for transaction execution.
Chapter 17-39
Transaction and System Concepts
The System Log
Log or Journal : The log keeps track of all transaction
operations that affect the values of database items. This
information may be needed to permit recovery from
transaction failures. The log is kept on disk, so it is not
affected by any type of failure except for disk or
catastrophic failure. In addition, the log is periodically
backed up to archival storage (tape) to guard against
such catastrophic failures.
T in the following discussion refers to a unique
transactionid that is generated automatically by the
system and is used to identify each transaction:
Chapter 17-40
Transaction and System Concepts
The System Log (cont):
Types of log record:
3. [start_transaction,T]: Records that transaction T has
started execution.
4. [write_item,T,X,old_value,new_value]: Records that
transaction T has changed the value of database item X
from old_value to new_value.
5. [read_item,T,X]: Records that transaction T has read
the value of database item X.
6. [commit,T]: Records that transaction T has completed
successfully, and affirms that its effect can be
committed (recorded permanently) to the database.
7. [abort,T]: Records that transaction T has been aborted.
Chapter 17-41
Transaction and System Concepts
Recovery using log records:
If the system crashes, we can recover to a consistent
database state by examining the log and using one of
the techniques described in Chapter 19.
Because the log contains a record of every write
operation that changes the value of some database
item, it is possible to undo the effect of these write
operations of a transaction T by tracing backward
through the log and resetting all items changed by a
write operation of T to their old_values.
We can also redo the effect of the write operations of a
transaction T by tracing forward through the log and
setting all items changed by a write operation of T
(that did not get done permanently) to their
new_values.
Chapter 17-42
Transaction and System Concepts
Commit Point of a Transaction:
Definition: A transaction T reaches its commit point
when all its operations that access the database have
been executed successfully and the effect of all the
transaction operations on the database has been
recorded in the log.
Beyond the commit point, the transaction is said to be
committed, and its effect is assumed to be permanently
recorded in the database. The transaction then writes an
entry [commit,T] into the log.
Chapter 17-43
Transaction and System Concepts
Commit Point of a Transaction:
Roll Back of transactions: Needed for transactions
that have a [start_transaction,T] entry into the log but
no commit entry [commit,T] into the log.
Chapter 17-44
Transaction and System Concepts
Commit Point of a Transaction (cont):
Redoing transactions: Transactions that have written
their commit entry in the log must also have recorded
all their write operations in the log; otherwise they
would not be committed, so their effect on the
database can be redone from the log entries. (Notice
that the log file must be kept on disk. At the time of a
system crash, only the log entries that have been
written back to disk are considered in the recovery
process because the contents of main memory may be
lost.)
When would you redo transactions (under what circumstances?
Chapter 17-45
Transaction and System Concepts
Commit Point of a Transaction (cont):
Force writing a log: before a transaction reaches its
commit point, any portion of the log that has not been
written to the disk yet must now be written to the disk.
This process is called forcewriting the log file before
committing a transaction.
Chapter 17-46
17.3 Desirable Properties of Transactions
ACID properties:
Atomicity: A transaction is an atomic unit of
processing; it is either performed in its entirety
or not performed at all.
Consistency preservation: A correct execution
of the transaction must take the database from
one consistent state to another.
Chapter 17-47
Desirable Properties of Transactions
ACID properties (cont.):
Isolation: A transaction should not make its updates
visible to other transactions until it is committed; this
property, when enforced strictly, solves the temporary
update problem and makes cascading rollbacks of
transactions unnecessary (see Chapter 21).
Durability or permanency: Once a transaction changes
the database and the changes are committed, these
changes must never be lost because of subsequent
failure.
Chapter 17-48
Notes
Chapter 17-49
Notes
Chapter 17-50
Transaction and System Concepts
The System Log (cont):
protocols for recovery that avoid cascading
rollbacks do not require that read operations
be written to the system log, whereas other
protocols require these entries for recovery.
strict protocols require simpler write entries
that do not include new_value (see Section
17.4).
Chapter 17-51
Notes
Chapter 17-52
17.4 Characterizing Schedules
based on Recoverability (1)
Transaction schedule or history: When transactions are
executing concurrently in an interleaved fashion, the order of
execution of operations from the various transactions forms
what is known as a transaction schedule (or history).
A schedule (or history) S of n transactions T1, T2, ..., Tn :
It is an ordering of the operations of the transactions subject to
the constraint that, for each transaction Ti that participates in
S, the operations of T1 in S must appear in the same order in
which they occur in T1. Note, however, that operations from
other transactions Tj can be interleaved with the operations of
Ti in S.
Chapter 17-53
Characterizing Schedules based on
Recoverability (2)
Schedules classified on recoverability:
Recoverable schedule: One where no transaction needs
to be rolled back.
A schedule S is recoverable if no transaction T in S commits
until all transactions T’ that have written an item that T reads
have committed.
Cascadeless schedule: One where every transaction reads
only the items that are written by committed transactions.
Schedules requiring cascaded rollback: A schedule in
which uncommitted transactions that read an item from a
failed transaction must be rolled back.
Chapter 17-54
Characterizing Schedules based on
Recoverability (3)
Schedules classified on recoverability (cont.):
Strict Schedules: A schedule in which a transaction
can neither read or write an item X until the last
transaction that wrote X has committed.
Chapter 17-55
17.5 Characterizing Schedules
based on Serializability (1)
Serial schedule: A schedule S is serial if, for every
transaction T participating in the schedule, all the
operations of T are executed consecutively in the
schedule. Otherwise, the schedule is called nonserial
schedule.
Serializable schedule: A schedule S is serializable
if it is equivalent to some serial schedule of the same
n transactions.
Chapter 17-56
Characterizing Schedules based on
Serializability (2)
Result equivalent: Two schedules are called result
equivalent if they produce the same final state of the
database.
Conflict equivalent: Two schedules are said to be
conflict equivalent if the order of any two conflicting
operations is the same in both schedules.
Conflict serializable: A schedule S is said to be
conflict serializable if it is conflict equivalent to
some serial schedule S’.
Chapter 17-57
Characterizing Schedules based on
Serializability (3)
Being serializable is not the same as being serial
Being serializable implies that the schedule is a
correct schedule.
– It will leave the database in a consistent state.
– The interleaving is appropriate and will result in a
state as if the transactions were serially executed, yet
will achieve efficiency due to concurrent execution.
Chapter 17-58
Characterizing Schedules based on
Serializability (4)
Serializability is hard to check.
– Interleaving of operations occurs in an operating
system through some scheduler
– Difficult to determine beforehand how the
operations in a schedule will be interleaved.
Chapter 17-59
Characterizing Schedules based on
Serializability (5)
Practical approach:
Come up with methods (protocols) to ensure
serializability.
It’s not possible to determine when a schedule begins
and when it ends. Hence, we reduce the problem of
checking the whole schedule to checking only a
committed project of the schedule (i.e. operations
from only the committed transactions.)
Current approach used in most DBMSs:
– Use of locks with two phase locking
Chapter 17-60
Characterizing Schedules based on
Serializability (6)
View equivalence: A less restrictive definition of
equivalence of schedules
View serializability: definition of serializability
based on view equivalence. A schedule is view
serializable if it is view equivalent to a serial
schedule.
Chapter 17-61
Characterizing Schedules based on
Serializability (7)
Two schedules are said to be view equivalent if the following
three conditions hold:
2. The same set of transactions participates in S and S’, and S
and S’ include the same operations of those transactions.
3. For any operation Ri(X) of Ti in S, if the value of X read by
the operation has been written by an operation Wj(X) of Tj
(or if it is the original value of X before the schedule started),
the same condition must hold for the value of X read by
operation Ri(X) of Ti in S’.
4. If the operation Wk(Y) of Tk is the last operation to write
item Y in S, then Wk(Y) of Tk must also be the last operation
to write item Y in S’.
Chapter 17-62
Characterizing Schedules based on
Serializability (8)
The premise behind view equivalence:
As long as each read operation of a transaction reads
the result of the same write operation in both
schedules, the write operations of each transaction
musr produce the same results.
“The view”: the read operations are said to see the
the same view in both schedules.
Chapter 17-63
Characterizing Schedules based on
Serializability (9)
Relationship between view and conflict equivalence:
The two are same under constrained write
assumption which assumes that if T writes X, it is
constrained by the value of X it read; i.e., new X =
f(old X)
Conflict serializability is stricter than view
serializability. With unconstrained write (or blind
write), a schedule that is view serializable is not
necessarily conflict serialiable.
Any conflict serializable schedule is also view
serializable, but not vice versa.
Chapter 17-64
Characterizing Schedules based on
Serializability (10)
Relationship between view and conflict equivalence
(cont):
Consider the following schedule of three transactions
T1: r1(X), w1(X); T2: w2(X); and T3: w3(X):
Schedule Sa: r1(X); w2(X); w1(X); w3(X); c1; c2; c3;
In Sa, the operations w2(X) and w3(X) are blind writes, since T1
and T3 do not read the value of X.
Sa is view serializable, since it is view equivalent to the serial
schedule T1, T2, T3. However, Sa is not conflict serializable,
since it is not conflict equivalent to any serial schedule.
Chapter 17-65
Characterizing Schedules based on
Serializability (11)
Testing for conflict serializability
Algorithm 17.1:
Looks at only read_Item (X) and write_Item (X) operations
Constructs a precedence graph (serialization graph) - a graph
with directed edges
An edge is created from Ti to Tj if one of the operations in Ti
appears before a conflicting operation in Tj
The schedule is serializable if and only if the precedence graph
has no cycles.
Chapter 17-66
Figure 17.7 Constructing the precedence graphs for schedules A and D from
Figure 17.5 to test for conflict serializability. (a) Precedence graph for serial
schedule A. (b) Precedence graph for serial schedule B. (c) Precedence graph for
schedule C (not serializable). (d) Precedence graph for schedule D (serializable,
equivalent to schedule A).
Chapter 17-67
Figure 17.8 Another example of serializability testing. (a)
The READ and WRITE operations of three transactions T1,
T2, and T3.
Chapter 17-68
FIGURE 17.8 (continued)
Another example of serializability testing. (b) Schedule E.
Chapter 17-69
FIGURE 17.8 (continued) Another example of
serializability testing. (c) Schedule F.
Chapter 17-70
Characterizing Schedules based on
Serializability (14)
Other Types of Equivalence of Schedules
Under special semantic constraints, schedules that
are otherwise not conflict serializable may work
correctly. Using commutative operations of addition
and subtraction (which can be done in any order)
certain non-serializable transactions may work
correctly
Chapter 17-71
Characterizing Schedules based on
Serializability (15)
Other Types of Equivalence of Schedules (cont.)
Example: bank credit / debit transactions on a given item are
separable and commutative.
Consider the following schedule S for the two transactions:
Sh : r1(X); w1(X); r2(Y); w2(Y); r1(Y); w1(Y); r2(X); w2(X);
Using conflict serializability, it is not serializable.
However, if it came from a (read,update, write) sequence as
follows:
r1(X); X := X – 10; w1(X); r2(Y); Y := Y – 20;r1(Y);
Y := Y + 10; w1(Y); r2(X); X := X + 20; (X);
Sequence explanation: debit, debit, credit, credit.
It is a correct schedule for the given semantics
Chapter 17-72
17.6 Transaction Support in SQL2 (1)
A single SQL statement is always considered to
be atomic. Either the statement completes
execution without error or it fails and leaves the
database unchanged.
With SQL, there is no explicit Begin Transaction
statement. Transaction initiation is done
implicitly when particular SQL statements are
encountered.
Every transaction must have an explicit end
statement, which is either a COMMIT or
ROLLBACK.
Chapter 17-73
Transaction Support in SQL2 (2)
Characteristics specified by a SET
TRANSACTION statement in SQL2:
Access mode: READ ONLY or READ WRITE. The
default is READ WRITE unless the isolation level of
READ UNCOMITTED is specified, in which case
READ ONLY is assumed.
Diagnostic size n, specifies an integer value n,
indicating the number of conditions that can be held
simultaneously in the diagnostic area. (Supply user
feedback information)
Chapter 17-74
Transaction Support in SQL2 (3)
Characteristics specified by a SET
TRANSACTION statement in SQL2 (cont.):
Isolation level <isolation>, where <isolation> can be
READ UNCOMMITTED, READ COMMITTED,
REPEATABLE READ or SERIALIZABLE. The
default is SERIALIZABLE.
With SERIALIZABLE: the interleaved execution of
transactions will adhere to our notion of
serializability. However, if any transaction executes
at a lower level, then serializability may be violated.
Chapter 17-75
Transaction Support in SQL2 (4)
Potential problem with lower isolation levels:
Dirty Read: Reading a value that was written by a
transaction which failed.
Nonrepeatable Read: Allowing another transaction to
write a new value between multiple reads of one
transaction.
A transaction T1 may read a given value from a table.
If another transaction T2 later updates that value and
T1 reads that value again, T1 will see a different value.
Consider that T1 reads the employee salary for Smith.
Next, T2 updates the salary for Smith. If T1 reads
Smith's salary again, then it will see a different value for
Smith's salary.
Chapter 17-76
Transaction Support in SQL2 (5)
Potential problem with lower isolation levels
(cont.):
Phantoms: New rows being read using the same read
with a condition.
A transaction T1 may read a set of rows from a
table, perhaps based on some condition specified
in the SQL WHERE clause. Now suppose that a
transaction T2 inserts a new row that also satisfies
the WHERE clause condition of T1, into the table
used by T1. If T1 is repeated, then T1 will see a row
that previously did not exist, called a phantom.
Chapter 17-77
Transaction Support in SQL2 (6)
Sample SQL transaction:
EXEC SQL whenever sqlerror go to UNDO;
EXEC SQL SET TRANSACTION
READ WRITE
DIAGNOSTICS SIZE 5
ISOLATION LEVEL SERIALIZABLE;
EXEC SQL INSERT
INTO EMPLOYEE (FNAME, LNAME, SSN, DNO, SALARY)
VALUES ('Robert','Smith','991004321',2,35000);
EXEC SQL UPDATE EMPLOYEE
SET SALARY = SALARY * 1.1
WHERE DNO = 2;
EXEC SQL COMMIT;
GOTO THE_END;
UNDO: EXEC SQL ROLLBACK;
THE_END: ...
Chapter 17-78
Transaction Support in SQL2 (7)
Possible violation of serializabilty:
Type of Violation
___________________________________
Isolation Dirty nonrepeatable
level read read phantom
_____________________ _____ _________ ____________________
READ UNCOMMITTED yes yes yes
READ COMMITTED no yes yes
REPEATABLE READ no no yes
SERIALIZABLE no no no
Chapter 17-79
Chapter 17
Introduction to Transaction
Processing Concepts and Theory
Figure17.2Two sample transactions.
(a) Transaction T1. (b) Transaction T2.
Chapter 17-82
Figure17.3 Some problems that occur when
concurrent execution is uncontrolled. (a) The lost
update problem.
Chapter 17-83
Figure17.3 (continued) Some problems that occur when
concurrent execution is uncontrolled. (b) The temporary
update problem.
Chapter 17-84
Figure17.3 (continued) Some problems that occur when
concurrent execution is uncontrolled. (c) The incorrect
summary problem.
Chapter 17-85
Figure17.4 State transition diagram illustrating the states for
transaction execution.
Chapter 17-86
Figure17.5 Examples of serial and nonserial schedules
involving transactions T1 and T2. (a) Serial schedule A: T1
followed by T2. (b) Serial schedules B: T2 followed by T1.
Chapter 17-87
Figure17.5 (continued) Examples of serial and nonserial
schedules involving transactions T1 and T2. (c) Two
nonserial schedules C and D with interleaving of
operations.
Chapter 17-88
Figure 17.6 Two schedules that are result equivalent for the
initial value of X = 100 but are not result equivalent in
general.
Chapter 17-89
Figure 17.7 Constructing the precedence graphs for schedules A and
D from Figure 17.5 to test for conflict serializability. (a) Precedence
graph for serial schedule A. (b) Precedence graph for serial schedule
B. (c) Precedence graph for schedule C (not serializable). (d)
Precedence graph for schedule D (serializable, equivalent to schedule
A).
Chapter 17-90
Figure 17.8 Another example of serializability
testing. (a) The READ and WRITE operations of
three transactions T1, T2, and T3.
Chapter 17-91
Figure17.8 (continued) Another example of
serializability testing. (b) Schedule E.
Chapter 17-92
FIGURE 17.8 (continued)
Another example of serializability testing. (c) Schedule F.
Slide 17-93
Figure 17.8
(continued)
Another example
of serializability
testing.
(d) Precedence graph
for schedule E.
(e) Precedence graph
for schedule F.
(f) Precedence graph
with two equivalent
serial schedules.
Slide 17-94
