Databasetransactionmodule4bcs403presentation

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Copyright © 2007 Ramez Elmasri and Shamkant B. Navathe

Chapter 17
Introduction to Transaction
Processing Concepts and Theory

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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

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1 Introduction to Transaction
Processing (1)
 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.

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Introduction to Transaction Processing (2)
 A Transaction:
 Logical unit of database processing that includes one or more
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.

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SIMPLE MODEL OF A DATABASE (for purposes of
discussing transactions):
 A database is a collection of named data items
 Granularity of data - a field, a record , or a whole disk
block (Concepts are independent of granularity)
 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.

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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.
 read_item(X) command includes the following steps:

Find the address of the disk block that contains item X.

Copy that disk block into a buffer in main memory (if that disk
block is not already in some main memory buffer).

Copy item X from the buffer to the program variable named X.

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READ AND WRITE OPERATIONS (contd.):
 write_item(X) command includes the following steps:

Find the address of the disk block that contains item X.

Copy that disk block into a buffer in main memory (if that disk
block is not already in some main memory buffer).

Copy item X from the program variable named X into its correct
location in the buffer.

Store the updated block from the buffer back to disk (either
immediately or at some later point in time).

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Two sample transactions
 FIGURE 17.2 Two sample transactions:
 (a) Transaction T1

(b) Transaction T2

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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.
 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.
 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.

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Concurrent execution is uncontrolled:
(a) The lost update problem.

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(b) The temporary update problem.

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(c) The incorrect summary problem.

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Processing (12)
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.
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.

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Processing (13)
Why recovery is needed (Contd.):
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.
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).

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Processing (14)
Why recovery is needed (contd.):
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.
6. Physical problems and catastrophes:
This refers to an endless list of problems that includes
power or air-conditioning failure, fire, theft,
sabotage, overwriting disks or tapes by mistake,
and mounting of a wrong tape by the operator.

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2 Transaction and System Concepts (1)
 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

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Transaction and System Concepts (2)
 Recovery manager keeps track of the 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.

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.

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 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.

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 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.

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State transition diagram illustrating
the states for transaction execution

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 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.

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 The System Log (cont):
 T in the following discussion refers to a unique transaction-id
that is generated automatically by the system and is used to
identify each transaction:

Types of log record:

[start_transaction,T]: Records that transaction T has started
execution.

[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.

[read_item,T,X]: Records that transaction T has read the
value of database item X.

[commit,T]: Records that transaction T has completed
successfully, and affirms that its effect can be committed
(recorded permanently) to the database.

[abort,T]: Records that transaction T has been aborted.

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 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).

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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.
1. 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.
2. 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.

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Commit Point of a Transaction:
 Definition a Commit Point:

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.
 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.

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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.)
 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 force-writing the log file before committing a
transaction.

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3 Desirable Properties of Transactions (1)
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.
 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.

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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.

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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.

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Recoverability (3)
Schedules classified on recoverability
(contd.):
 Schedules requiring cascaded rollback:
 A schedule in which uncommitted
transactions that read an item from a failed
transaction must be rolled back.
 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.

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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.

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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’.

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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.

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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.

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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

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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.

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Serializability (7)
 Two schedules are said to be view equivalent if the
following three conditions hold:
1. The same set of transactions participates in S and S’, and S
and S’ include the same operations of those transactions.
2. 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’.
3. 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’.

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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
must produce the same results.
 “The view”: the read operations are said to see
the same view in both schedules.

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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 serializable.
 Any conflict serializable schedule is also view
serializable, but not vice versa.

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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.

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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.

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Constructing the Precedence Graphs
 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).

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Another example of serializability
Testing

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Another Example of Serializability
Testing

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Another Example of Serializability
Testing

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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

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Other Types of Equivalence of Schedules (contd.)
 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

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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.

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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.

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Characteristics specified by a SET TRANSACTION
statement in SQL2 (contd.):
 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.

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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.

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 Potential problem with lower isolation levels
(contd.):
 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.

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 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: ...

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 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

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Summary
 Transaction and System Concepts
 Desirable Properties of Transactions
 Characterizing Schedules based on
Recoverability
 Characterizing Schedules based on Serializability
 Transaction Support in SQL

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