Digital Notes of Database Management System

CHAPTER 15: TRANSACTIONS
Transaction Concept
Transaction State
Implementation of Atomicity and Durability
Concurrent Executions
Serializability
Recoverability
Implementation of Isolation
Transaction Definition in SQL
Testing for Serializability.

TRANSACTION CONCEPT
A transaction is a unit of program execution that accesses and possibly
updates various data items.
A transaction must see a consistent database.
During transaction execution the database may be inconsistent.
When the transaction is committed, the database must be consistent.
Two main issues to deal with:
 Failures of various kinds, such as hardware failures and system crashes
 Concurrent execution of multiple transactions

ACID PROPERTIES
Atomicity. Either all operations of the transaction are properly reflected in the
database or none are.
Consistency. Execution of a transaction in isolation preserves the consistency of
the database.
Isolation. Although multiple transactions may execute concurrently, each
transaction must be unaware of other concurrently executing transactions.
Intermediate transaction results must be hidden from other concurrently
executed transactions.
 That is, for every pair of transactions Ti and Tj, it appears to Ti that either Tj,
finished execution before Ti started, or Tj started execution after Ti finished.
Durability. After a transaction completes successfully, the changes it has made to
the database persist, even if there are system failures.
To preserve integrity of data, the database system must ensure:

EXAMPLE OF FUND TRANSFER
Transaction to transfer $50 from account A to account B:
1.read(A)
2.A := A – 50
3.write(A)
4.read(B)
5.B := B + 50
6.write(B)
Consistency requirement – the sum of A and B is unchanged by the
execution of the transaction.
Atomicity requirement — if the transaction fails after step 3 and
before step 6, the system should ensure that its updates are not
reflected in the database, else an inconsistency will result.

EXAMPLE OF FUND TRANSFER (CONT.)
Durability requirement — once the user has been notified that the transaction has
completed (i.e., the transfer of the $50 has taken place), the updates to the
database by the transaction must persist despite failures.
Isolation requirement — if between steps 3 and 6, another transaction is allowed
to access the partially updated database, it will see an inconsistent database
(the sum A + B will be less than it should be).
Can be ensured trivially by running transactions serially, that is one after the
other. However, executing multiple transactions concurrently has significant
benefits, as we will see.

TRANSACTION STATE
Active, the initial state; the transaction stays in this state while it is
executing
Partially committed, after the final statement has been executed.
Failed, after the discovery that normal execution can no longer
proceed.
Aborted, after the transaction has been rolled back and the
database restored to its state prior to the start of the
transaction. Two options after it has been aborted:
 restart the transaction – only if no internal logical error
 kill the transaction
Committed, after successful completion.

IMPLEMENTATION OF ATOMICITY AND
DURABILITY
The recovery-management component of a database system implements the
support for atomicity and durability.
The shadow-database scheme:
 assume that only one transaction is active at a time.
 a pointer called db_pointer always points to the current consistent copy of the
database.
 all updates are made on a shadow copy of the database, and db_pointer is
made to point to the updated shadow copy only after the transaction reaches
partial commit and all updated pages have been flushed to disk.
 in case transaction fails, old consistent copy pointed to by db_pointer can be
used, and the shadow copy can be deleted.

IMPLEMENTATION OF ATOMICITY AND
DURABILITY (CONT.)
Assumes disks to not fail
Useful for text editors, but extremely inefficient for large databases: executing a single
transaction requires copying the entire database.
The shadow-database scheme:

CONCURRENT EXECUTIONS
Multiple transactions are allowed to run concurrently in the system. Advantages
are:
 increased processor and disk utilization, leading to better transaction
throughput: one transaction can be using the CPU while another is reading from
or writing to the disk
 reduced average response time for transactions: short transactions need not
wait behind long ones.
Concurrency control schemes – mechanisms to achieve isolation, i.e., to control
the interaction among the concurrent transactions in order to prevent them
from destroying the consistency of the database

SCHEDULES
Schedules – sequences that indicate the chronological order in which instructions of
concurrent transactions are executed
 a schedule for a set of transactions must consist of all instructions of those
transactions
 must preserve the order in which the instructions appear in each individual transaction.

EXAMPLE SCHEDULES
Let T1 transfer $50 from A to B, and T2 transfer 10% of the balance from A to B.
The following is a serial schedule (Schedule 1 in the text), in which T1 is
followed by T2.

EXAMPLE SCHEDULE (CONT.)
Let T1 and T2 be the transactions defined previously. The following
schedule (Schedule 3 in the text) is not a serial schedule, but it is
equivalent to Schedule 1.
In both Schedule 1 and 3, the sum A + B is preserved.

EXAMPLE SCHEDULES (CONT.)
The following concurrent schedule (Schedule 4 in the text) does not
preserve the value of the the sum A + B.

SERIALIZABILITY
Basic Assumption – Each transaction preserves database consistency.
Thus serial execution of a set of transactions preserves database consistency.
A (possibly concurrent) schedule is serializable if it is equivalent to a serial schedule.
Different forms of schedule equivalence give rise to the notions of:
1.conflict serializability
2.view serializability
We ignore operations other than read and write instructions, and we assume that
transactions may perform arbitrary computations on data in local buffers in
between reads and writes. Our simplified schedules consist of only read and
write instructions.

CONFLICT SERIALIZABILITY
Instructions li and lj of transactions Ti and Tj respectively, conflict if and only if there
exists some item Q accessed by both li and lj, and at least one of these
instructions wrote Q.
1. li = read(Q), lj = read(Q). li and lj don’t conflict.
2. li = read(Q), lj = write(Q). They conflict.
3. li = write(Q), lj = read(Q). They conflict
4. li = write(Q), lj = write(Q). They conflict
Intuitively, a conflict between li and lj forces a (logical) temporal order between them.
If li and lj are consecutive in a schedule and they do not conflict, their results
would remain the same even if they had been interchanged in the schedule.

CONFLICT SERIALIZABILITY (CONT.)
If a schedule S can be transformed into a schedule S´ by a series of swaps of non-
conflicting instructions, we say that S and S´ are conflict equivalent.
We say that a schedule S is conflict serializable if it is conflict equivalent to a serial
schedule
Example of a schedule that is not conflict serializable:
T3 T4
read(Q)
write(Q)
write(Q)
We are unable to swap instructions in the above schedule to obtain either the
serial schedule < T3, T4 >, or the serial schedule < T4, T3 >.

CONFLICT SERIALIZABILITY (CONT.)
Schedule 3 below can be transformed into Schedule 1, a serial schedule where T2
follows T1, by series of swaps of non-conflicting instructions. Therefore Schedule
3 is conflict serializable.

VIEW SERIALIZABILITY
Let S and S´ be two schedules with the same set of transactions. S and S´ are view
equivalent if the following three conditions are met:
1.For each data item Q, if transaction Ti reads the initial value of Q in schedule S, then
transaction Ti must, in schedule S´, also read the initial value of Q.
2.For each data item Q if transaction Ti executes read(Q) in schedule S, and that value
was produced by transaction Tj (if any), then transaction Ti must in schedule S´ also
read the value of Q that was produced by transaction Tj .
3.For each data item Q, the transaction (if any) that performs the final write(Q) operation
in schedule S must perform the final write(Q) operation in schedule S´.
As can be seen, view equivalence is also based purely on reads
and writes alone.

VIEW SERIALIZABILITY (CONT.)
A schedule S is view serializable it is view equivalent to a serial schedule.
Every conflict serializable schedule is also view serializable.
Schedule 9 (from text) — a schedule which is view-serializable but not conflict serializable.
Every view serializable schedule that is not conflict
serializable has blind writes.

OTHER NOTIONS OF SERIALIZABILITY
Schedule 8 (from text) given below produces same outcome as the serial
schedule < T1,T5 >, yet is not conflict equivalent or view equivalent to it.
Determining such equivalence requires analysis of operations other than
read and write.

RECOVERABILITY
Recoverable schedule — if a transaction Tj reads a data items previously written by a
transaction Ti , the commit operation of Ti appears before the commit operation of Tj.
The following schedule (Schedule 11) is not recoverable if T9 commits immediately after
the read
If T8 should abort, T9 would have read (and possibly shown to the user) an inconsistent
database state. Hence database must ensure that schedules are recoverable.
Need to address the effect of transaction failures on concurrently
running transactions.

RECOVERABILITY (CONT.)
Cascading rollback – a single transaction failure leads to a series of transaction
rollbacks. Consider the following schedule where none of the transactions
has yet committed (so the schedule is recoverable)
If T10 fails, T11 and T12 must also be rolled back.
Can lead to the undoing of a significant amount of work

RECOVERABILITY (CONT.)
Cascadeless schedules — cascading rollbacks cannot occur; for each pair of
transactions Ti and Tj such that Tj reads a data item previously written by Ti, the
commit operation of Ti appears before the read operation of Tj.
Every cascadeless schedule is also recoverable
It is desirable to restrict the schedules to those that are cascadeless

IMPLEMENTATION OF ISOLATION
Schedules must be conflict or view serializable, and recoverable, for the sake of
database consistency, and preferably cascadeless.
A policy in which only one transaction can execute at a time generates serial
schedules, but provides a poor degree of concurrency..
Concurrency-control schemes tradeoff between the amount of concurrency they
allow and the amount of overhead that they incur.
Some schemes allow only conflict-serializable schedules to be generated, while
others allow view-serializable schedules that are not conflict-serializable.

TRANSACTION DEFINITION IN SQL
Data manipulation language must include a construct for specifying the set of
actions that comprise a transaction.
In SQL, a transaction begins implicitly.
A transaction in SQL ends by:
 Commit work commits current transaction and begins a new one.
 Rollback work causes current transaction to abort.
Levels of consistency specified by SQL-92:
 Serializable — default
 Repeatable read
 Read committed
 Read uncommitted

LEVELS OF CONSISTENCY IN SQL-92
Serializable — default
Repeatable read — only committed records to be read, repeated reads of same record
must return same value. However, a transaction may not be serializable – it may
find some records inserted by a transaction but not find others.
Read committed — only committed records can be read, but successive reads of record
may return different (but committed) values.
Read uncommitted — even uncommitted records may be read.
Lower degrees of consistency useful for gathering approximate
information about the database, e.g., statistics for query optimizer.

TESTING FOR SERIALIZABILITY
Consider some schedule of a set of transactions T1, T2, ..., Tn
Precedence graph — a direct graph where the vertices are the transactions
(names).
We draw an arc from Ti to Tj if the two transaction conflict, and Ti accessed
the data item on which the conflict arose earlier.
We may label the arc by the item that was accessed.
Example 1
x
y

EXAMPLE SCHEDULE (SCHEDULE A)
T1 T2 T3 T4 T5
read(X)
read(Y)
read(Z)
read(V)
read(W)
read(W)
read(Y)
write(Y)
write(Z)
read(U)
read(Y)
write(Y)
read(Z)
write(Z)
read(U)
write(U)

PRECEDENCE GRAPH FOR SCHEDULE A
T3
T4
T1 T2

TEST FOR CONFLICT SERIALIZABILITY
A schedule is conflict serializable if and only if its precedence graph is acyclic.
Cycle-detection algorithms exist which take order n2
time, where n is the number of
vertices in the graph. (Better algorithms take order n + e where e is the number
of edges.)
If precedence graph is acyclic, the serializability order can be obtained by a
topological sorting of the graph. This is a linear order consistent with the partial
order of the graph.
For example, a serializability order for Schedule A would be
T5  T1  T3  T2  T4 .

TEST FOR VIEW SERIALIZABILITY
The precedence graph test for conflict serializability must be modified to apply to a test
for view serializability.
The problem of checking if a schedule is view serializable falls in the class of NP-
complete problems. Thus existence of an efficient algorithm is unlikely.
However practical algorithms that just check some sufficient conditions for view
serializability can still be used.

CONCURRENCY CONTROL VS.
SERIALIZABILITY TESTS
Testing a schedule for serializability after it has executed is a little too late!
Goal – to develop concurrency control protocols that will assure serializability. They
will generally not examine the precedence graph as it is being created; instead a
protocol will impose a discipline that avoids nonseralizable schedules.
Will study such protocols in Chapter 16.
Tests for serializability help understand why a concurrency control protocol is correct.

SCHEDULE 2 -- A SERIAL SCHEDULE IN WHICH
T2 IS FOLLOWED BY T1

SCHEDULE 5 -- SCHEDULE 3 AFTER SWAPPING
A PAIR OF INSTRUCTIONS

SCHEDULE 6 -- A SERIAL SCHEDULE THAT IS
EQUIVALENT TO SCHEDULE 3

PRECEDENCE GRAPH FOR
(A) SCHEDULE 1 AND (B) SCHEDULE 2

ILLUSTRATION OF TOPOLOGICAL SORTING

Digital Notes of Database Management System

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Digital Notes of Database Management System