Transactions

Database System Concepts, 7th Ed.

©Silberschatz, Korth and Sudarshan
See www.db-book.com for conditions on re-use
 Outline
 Transaction Concept
 Transaction State
 Concurrent Executions
 Serializability
 Recoverability
 Implementation of Isolation
 Transaction Definition in SQL
 Testing for Serializability.
Database System Concepts - 7th Edition 17.2 ©Silberschatz, Korth and Sudarshan
 Transaction Concept
 A transaction is a unit of program execution that accesses
and possibly updates various data items.
 E.g., 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)
 Two main issues to deal with:
• Failures of various kinds, such as hardware failures and
system crashes
• Concurrent execution of multiple transactions
Database System Concepts - 7th Edition 17.3 ©Silberschatz, Korth and Sudarshan
 Transaction Concept (Cont..)
 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)
 Atomicity requirement
• If the transaction fails after step 3 and before step 6, money will be
―lost‖ leading to an inconsistent database state
 Failure could be due to software or hardware
• The system should ensure that updates of a partially executed
transaction are not reflected in the database
 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 even if there
are software or hardware failures.
Database System Concepts - 7th Edition 17.4 ©Silberschatz, Korth and Sudarshan
 Transaction Concept (Cont..)
 Consistency requirement in above example:
• The sum of A and B is unchanged by the execution of the transaction
 In general, consistency requirements include
• Explicitly specified integrity constraints such as primary keys and
foreign keys
• Implicit integrity constraints
 e.g., sum of balances of all accounts, minus sum of loan amounts
must equal value of cash-in-hand
• A transaction must see a consistent database.
• During transaction execution the database may be temporarily
inconsistent.
• When the transaction completes successfully the database must be
consistent
 Erroneous transaction logic can lead to inconsistency

Database System Concepts - 7th Edition 17.5 ©Silberschatz, Korth and Sudarshan
 Transaction Concept (Cont..)
 Isolation requirement — if between steps 3 and 6, another
transaction T2 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).
T1 T2
1. read(A)
2. A := A – 50
3. write(A)
read(A), read(B), print(A+B)
4. read(B)
5. B := B + 50
6. write(B
 Isolation 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 later.
Database System Concepts - 7th Edition 17.6 ©Silberschatz, Korth and Sudarshan
 ACID Properties
A transaction is a unit of program execution that accesses and possibly
updates various data items. To preserve the integrity of data the database
system must ensure:

 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.

Database System Concepts - 7th Edition 17.7 ©Silberschatz, Korth and Sudarshan
 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
 Can be done only if no internal logical error
• Kill the transaction
 Committed – after successful completion.

Database System Concepts - 7th Edition 17.8 ©Silberschatz, Korth and Sudarshan
 Transaction State (Cont.)

Database System Concepts - 7th Edition 17.9 ©Silberschatz, Korth and Sudarshan
 Concurrent Executions
 Multiple transactions are allowed to run concurrently in the system.
Advantages are:
• Increased processor and disk utilization, leading to better
transaction throughput
 E.g., 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
• That is, to control the interaction among the concurrent transactions in
order to prevent them from destroying the consistency of the database
 Will study in Chapter 18, after studying notion of correctness of
concurrent executions.

Database System Concepts - 7th Edition 17.10 ©Silberschatz, Korth and Sudarshan
 Schedules
 Schedule – a sequences of instructions that specify 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.
 A transaction that successfully completes its execution will have a commit
instructions as the last statement
• By default transaction assumed to execute commit instruction as its
last step
 A transaction that fails to successfully complete its execution will have an
abort instruction as the last statement

Database System Concepts - 7th Edition 17.11 ©Silberschatz, Korth and Sudarshan
 Schedule 1
 Let T1 transfer $50 from A to B, and T2 transfer 10% of the
balance from A to B.
 A serial schedule in which T1 is followed by T2 :

Database System Concepts - 7th Edition 17.12 ©Silberschatz, Korth and Sudarshan
 Schedule 2
 A serial schedule where T2 is followed by T1

Database System Concepts - 7th Edition 17.13 ©Silberschatz, Korth and Sudarshan
 Schedule 3
 Let T1 and T2 be the transactions defined previously. The
following schedule is not a serial schedule, but it is
equivalent to Schedule 1

 In Schedules 1, 2 and 3, the sum A + B is preserved.

Database System Concepts - 7th Edition 17.14 ©Silberschatz, Korth and Sudarshan
 Schedule 4
 The following concurrent schedule does not preserve the
value of (A + B ).

Database System Concepts - 7th Edition 17.15 ©Silberschatz, Korth and Sudarshan
 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

Database System Concepts - 7th Edition 17.16 ©Silberschatz, Korth and Sudarshan
 Simplified View of
Transactions
 We ignore operations other than read and write
instructions
 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.

Database System Concepts - 7th Edition 17.17 ©Silberschatz, Korth and Sudarshan
 Conflicting Instructions
 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.

Database System Concepts - 7th Edition 17.18 ©Silberschatz, Korth and Sudarshan
 Conflict Serializability
 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

Database System Concepts - 7th Edition 17.19 ©Silberschatz, Korth and Sudarshan
 Conflict Serializability (Cont.)
 Schedule 3 can be transformed into Schedule 6, a serial
schedule where T2 follows T1, by series of swaps of non-
conflicting instructions. Therefore Schedule 3 is conflict
serializable.

Schedule 3 Schedule 6
Database System Concepts - 7th Edition 17.20 ©Silberschatz, Korth and Sudarshan
 Conflict Serializability (Cont.)
 Example of a schedule that is not conflict serializable:

 We are unable to swap instructions in the above

schedule to obtain either the serial schedule < T3, T4
>, or the serial schedule < T4, T3 >.

Database System Concepts - 7th Edition 17.21 ©Silberschatz, Korth and Sudarshan
 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, for each
data item Q,
1. If in schedule S, transaction Ti reads the initial value of Q, then in
schedule S’ also transaction Ti must read the initial value of Q.
2. If in schedule S transaction Ti executes read(Q), and that value was
produced by transaction Tj (if any), then in schedule S’ also
transaction Ti must read the value of Q that was produced by the
same write(Q) operation of transaction Tj .
3. The transaction (if any) that performs the final write(Q) operation in
schedule S must also perform the final write(Q) operation in
schedule S’.
 As can be seen, view equivalence is also based purely on reads and
writes alone.

Database System Concepts - 7th Edition 17.22 ©Silberschatz, Korth and Sudarshan
 View Serializability (Cont.)
 A schedule S is view serializable if it is view equivalent to a
serial schedule.
 Every conflict serializable schedule is also view serializable.
 Below is a schedule which is view-serializable but not conflict
serializable.

 What serial schedule is above equivalent to?

 Every view serializable schedule that is not conflict
serializable has blind writes.

Database System Concepts - 7th Edition 17.23 ©Silberschatz, Korth and Sudarshan
 Other Notions of Serializability
 The schedule 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.
Database System Concepts - 7th Edition 17.24 ©Silberschatz, Korth and Sudarshan
 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 of a precedence graph

Database System Concepts - 7th Edition 17.25 ©Silberschatz, Korth and Sudarshan
 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.

Database System Concepts - 7th Edition 17.26 ©Silberschatz, Korth and Sudarshan
 Test for View Serializability
 The precedence graph test for conflict serializability cannot be
used directly to test for view serializability.
• Extension to test for view serializability has cost exponential
in the size of the precedence graph.
 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 extremely
unlikely.
 However practical algorithms that just check some sufficient
conditions for view serializability can still be used.

Database System Concepts - 7th Edition 17.28 ©Silberschatz, Korth and Sudarshan
 Recoverable Schedules
Need to address the effect of transaction failures on concurrently
running transactions.
 Recoverable schedule — if a transaction Tj reads a data item previously
written by a transaction Ti , then the commit operation of Ti appears before
the commit operation of Tj.
 The following schedule (Schedule 11) is not recoverable

 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.
Database System Concepts - 7th Edition 17.29 ©Silberschatz, Korth and Sudarshan
 Cascading Rollbacks
 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
Database System Concepts - 7th Edition 17.30 ©Silberschatz, Korth and Sudarshan
 Cascadeless Schedules
 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
Database System Concepts - 7th Edition 17.31 ©Silberschatz, Korth and Sudarshan
 Irrecoverable Schedule (Example)
When Tj is reading the value updated by Ti and Tj is committed
before committing of Ti, the schedule will be irrecoverable.

Database System Concepts - 7th Edition 17.32 ©Silberschatz, Korth and Sudarshan
 Recoverable with Cascading
Rollback (Example)
If Tj is reading value updated by Ti and commit of Tj is delayed
till commit of Ti, the schedule is called recoverable with
cascading rollback.

Database System Concepts - 7th Edition 17.33 ©Silberschatz, Korth and Sudarshan
 Cascadeless Recoverable
Rollback Schedule (Example)
If Tj reads value updated by Ti only after Ti is committed, the
schedule will be cascadeless recoverable.

Database System Concepts - 7th Edition 17.34 ©Silberschatz, Korth and Sudarshan
 Concurrency Control
 A database must provide a mechanism that will ensure that
all possible schedules are
• either conflict or view serializable
• recoverable 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
 Testing a schedule for serializability after it has executed is a
little too late!
 Goal – to develop concurrency control protocols that will
assure serializability.

Database System Concepts - 7th Edition 17.35 ©Silberschatz, Korth and Sudarshan
 Concurrency Control (Cont.)
 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.

Database System Concepts - 7th Edition 17.36 ©Silberschatz, Korth and Sudarshan
 Concurrency Control vs.
Serializability Tests
 Concurrency-control protocols allow concurrent schedules, but
ensure that the schedules are conflict/view serializable, and are
recoverable and cascadeless .
 Concurrency control protocols (generally) do not examine the
precedence graph as it is being created
• Instead a protocol imposes a discipline that avoids non-
serializable schedules.
 Different concurrency control protocols provide different
tradeoffs between the amount of concurrency they allow and
the amount of overhead that they incur.
 Tests for serializability help us understand why a concurrency
control protocol is correct.
Database System Concepts - 7th Edition 17.37 ©Silberschatz, Korth and Sudarshan
 Weak Levels of Consistency
 Some applications are willing to live with weak levels
of consistency, allowing schedules that are not
serializable
• E.g., a read-only transaction that wants to get an
approximate total balance of all accounts
• E.g., database statistics computed for query
optimization can be approximate (why?)
• Such transactions need not be serializable with
respect to other transactions
 Tradeoff accuracy for performance
Database System Concepts - 7th Edition 17.38 ©Silberschatz, Korth and Sudarshan
 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.
No other transaction allowed to update in-betwen.
• However, a transaction may not be serializable
 Read committed — only committed records can be read.
• Successive reads of record may return different (but
committed) values.
 Read uncommitted — even uncommitted records may be
read.

Database System Concepts - 7th Edition 17.39 ©Silberschatz, Korth and Sudarshan
 Levels of Consistency
 Lower degrees of consistency useful for gathering
approximate information about the database
 Warning: some database systems do not ensure
serializable schedules by default
 E.g., Oracle (and PostgreSQL prior to version 9) by
default support a level of consistency called snapshot
isolation (not part of the SQL standard)

Database System Concepts - 7th Edition 17.40 ©Silberschatz, Korth and Sudarshan
 Transaction Definition in SQL
 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.
 In almost all database systems, by default, every SQL statement
also commits implicitly if it executes successfully
• Implicit commit can be turned off by a database directive
 E.g., in JDBC -- connection.setAutoCommit(false);
 Isolation level can be set at database level
 Isolation level can be changed at start of transaction
 E.g. In SQL set transaction isolation level serializable
 E.g. in JDBC -- connection.setTransactionIsolation
(Connection.TRANSACTION_SERIALIZABLE)

Database System Concepts - 7th Edition 17.41 ©Silberschatz, Korth and Sudarshan
 Implementation of Isolation
Levels
 Locking
• Lock on whole database vs lock on items
• How long to hold lock?
• Shared vs exclusive locks
 Timestamps
• Transaction timestamp assigned e.g. when a transaction begins
• Data items store two timestamps
 Read timestamp
 Write timestamp
• Timestamps are used to detect out of order accesses
 Multiple versions of each data item
• Allow transactions to read from a ―snapshot‖ of the database

Database System Concepts - 7th Edition 17.42 ©Silberschatz, Korth and Sudarshan
 End of Chapter 17

Database System Concepts - 7th Edition 17.44 ©Silberschatz, Korth and Sudarshan