Download Overview of Transaction Management

Transaction Management Overview
Chapter 16
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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/written
from/to the database.
 A transaction is the DBMS’s abstract view of a user
program: a sequence of reads and writes.

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Transaction ACID Properties

Atomic
• Either all actions are carried out or none are.
• Not worry about incomplete transaction.

Consistency
• DBMS assumes that the consistency holds for each transaction.

Isolation
• Transactions are isolated, or protected, from the effects of
concurrently scheduling other transactions.

Durability
• The effects of transaction is persist if DBMS informs the user
successful execution.
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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.
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Atomicity of Transactions

A transaction is seen by DBMS as a series or list of
actions.
 read/write database object.
 A transaction might commit after completing all its actions.
 or it could abort (or be aborted by the DBMS) after executing
some actions.

Transactions are atomic: a user can think of a
transaction 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.
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Example

Consider two transactions (Transactions):
T1:
T2:
BEGIN A=A+100, B=B-100 END
BEGIN A=1.06*A, B=1.06*B END
Intuitively, the first transaction is transferring $100
from B’s account to A’s account. The second is
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.

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Example (Contd.)

Consider a possible interleaving (schedule):
T1:
T2:

A=1.06*A,
B=B-100
B=1.06*B
This is OK. But what about:
T1:
T2:

A=A+100,
A=A+100,
A=1.06*A, B=1.06*B
B=B-100
The DBMS’s view of the second schedule:
T1:
T2:
R(A), W(A),
R(A), W(A), R(B), W(B)
R(B), W(B)
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Scheduling Transactions

Schedule: an actual or potential execution sequence.
 A list of actions from a set of transactions as seen by DBMS.
 The order in which two actions of a transaction T appear in a schedule
must be the same as the order in which they appear in T.

Classification :
 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 on any consistent database instance.
• (Note: If each transaction preserves consistency, every serializable schedule
preserves consistency. )
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Concurrent Execution of Transaction
 E.g. Serializable schedule, Equal to the serial schedule T1;T2.
T1:
T2:
R(A), W(A),
R(B), W(B),
C
R(A), W(A),
R(B), W(B),C
 E.g. Serializable schedule, Equal to the serial schedule T2;T1.
T1:
T2:

R(A), W(A),
R(A),
R(B), W(B),
W(A),R(B), W(B),
C
C
Why concurrent execution?
• CPU and I/O can work in parallel to increase system
throughput.
• Interleaved execution of a short transaction with a long
transaction allows the short transaction to complete quickly,
thus prevent stuck transaction or unpredicatable delay in
response time.
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Anomalies with Interleaved Execution

Reading Uncommitted Data (WR Conflicts, “dirty reads”):
e.g. T1: A+100, B+100, T2: A*1.06, B*1.06
T1:
T2:

R(A), W(A), C
R(B), W(B), Abort
Unrepeatable Reads (RW Conflicts):
E.g., T1: R(A), check if A >0, decrement, T2: R(A), decrement
T1:
T2:

R(A), W(A),
R(A),
R(A), W(A), C
R(A), W(A), C
Overwriting Uncommitted Data (WW Conflicts):
T1:
T2:
W(A),
W(A), W(B), C
W(B), C
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Schedules involving Aborted Transactions

Serializable schedule:
 A schedule whose effect on any consistent database
instance is guaranteed to be identical to that of some
complete serial schedule over the set of committed
transactions.
 Aborted transactions being undone completely – we
have to do cascading abort.
T1:
T2:
R(A),W(A),
R(A),W(A),R(B),W(B), Commit
Abort
• Eg: Can we do cascading abort above? We have to abort changes made by
T2, but T2 is already committed – we say the above schedule is an
Unrecoverable schedule.
•What we need is Recoverable schedule.
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Recoverable Schedules
Recoverable schedule: transactions commit only
after all transactions whose changes they read
commit.
 In such a case, we can do cascading abort
 Eg below: Note that T2 cannot commit before T1,
therefore when T1 aborts, we can abort T2 as well.

T1:
T2:
R(A),W(A),
R(A),W(A),R(B),W(B),
Abort
Another technique: A transaction reads changes only of
committed transactions. Advantage of this approach is: the
schedule is recoverable, and we will never have to cascade
aborts.
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Lock-based Concurrency Control



Only serializable, recoverable schedules are allowed.
No actions of committed transactions are lost while undoing
aborted transactions.
Lock protocol: a set of rules to be followed by each transaction
( and enforced by DBMS) to ensure that, even though actions
of several transactions is interleaved, the net effect is identical
to executing all transactions in some serial order.
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Lock-Based Concurrency Control

Strict Two-phase Locking (Strict 2PL) Protocol:


Rule 1: Each Transaction must obtain a S (shared) lock on
object before reading, and an X (exclusive) lock on object
before writing.
Rule 2: All locks held by a transaction are released when
the transaction completes.
•


(Non-strict) 2PL Variant: Release locks anytime, but cannot acquire
locks after releasing any lock.
A transaction that has an exclusive lock can also read the object.
A transaction that requests a lock is suspended until the DBMS is able to
grant it the requested lock.
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Lock-Based Concurrency Control

In effect, only 'safe' interleavings of transactions are
allowed.



Two transactions access completely independent parts of
database.
If accessing same objects, all actions of one of transactions
(has the lock) are completed before the other transaction
can proceed.
Strict 2PL allows only serializable schedules.
 Additionally, it simplifies transaction aborts
 (Non-strict) 2PL also allows only serializable schedules,
but involves more complex abort processing
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Lock-based Concurrency Control

Strict 2PL
T1:
T2:
X(A),R(A),W(A),X(B),R(B),W(B),Commit
X(A),R(A),W(A),X(B),R(B),W(B), Commit
T1:
T2:
S(A),R(A),
S(A),R(A),X(B),R(B),W(B), Commit
X(C),R(C),W(C),Commit
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Deadlocks

Deadlock: Two transactions are waiting for
locks from each other.
e.g., T1 holds exclusive lock on A, requests an
exclusive lock on B and is queued. T2 holds an
exclusive lock on B, and request lock on A and
queued.

Deadlock detecting
 Timeout mechanism…
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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.


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.
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Performance of locking

Lock-based schemes
 Resolve conflicts between transactins.
 Two basic mechanisms: blocking and aborting.
• Blocked transactions hold lock, and force others to wait.
• Aborting wastes the work done thus far.
• Deadlock is an extreme instance of blocking. A set of
transactions is forever blocked unless one of the
deadlocked transactions is aborted.
 Overhead of locking is primarily from delays due
to blocking.
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Crash Recovery

Recovery Manager is responsible for ensuring
transaction atomicity and durability.
 Ensure atomicity by undoing the actions of transactions
that do not commit.
 Ensure durability by making sure that all actions of
committed transactions survive system crashes and
media failure.

Transaction Manager controls execution of
transactions.
 Acquire lock before reading and writing.
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Stealing Frames and Forcing Pages

Steal approach:
 Can the changes made to an object O in the buffer pool
by a transaction R be written to disk before T commits?
Happen in Page replacement.

Force approach:
 When a transaction commits, must we ensure that all
the changes it has made to objects in the buffer pool
are immediately forced to disk?
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Stealing Frames and Forcing Pages

Simplest: No-steal, force.
 Why? No-steal --- No undo. Force --- No redo.

Most system use steal, no-force approach.
 Why?
• Assumption in No-steal: all pages modified by ongoing
transactions can be accommodated in the buffer pool.
Unrealistic.
• Force results in excessive page I/O.
 Steal: replaced page is written to disk even if its
transaction is still alive. No-force: pages in the buffer
pool that are modified by a transaction are not forced
to disk when the transaction commits.
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The Log
Log: information maintained during normal execution
of transactions to enable it to perform its task in the
event of a failure.
 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!



Ti commits/aborts: a log record indicating this action.
Log records are chained together by transaction id, so it’s
easy to undo a specific transaction.
All log related activities are handled transparently by
DBMS.
 In fact, all CC related activities such as lock/unlock, dealing
with deadlocks etc.
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Recovering From a Crash


Checkpointing: saves information about active transactions
and dirty buffer pool pages, also helps reduce the time taken to
recover 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 transactions 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.
Undo: The writes of all transactions 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.
Some care must be taken to handle the case of a crash occurring during the
recovery process!
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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.
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