transaction management overview

Database Management Systems 3ed, R. Ramakrishnan and J. Gehrke 1

Transaction Management Overview

Chapter 18


Objects, transections

Database `objects' are the units in which programs read or write information Pages, records …

A transaction is seen by the DBMS as a series, or list of actions. The actions that can be executed by a transaction include reads and writes of database objects


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.


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.


ACID four important properties of transactions Users should be able to regard the execution

of each transaction as Atomic must preserve the consistency of the

database even if the DBMS interleaves the actions of

several transactions for performance reason without considering the effect of other concurrently executing transactions: isolation:

Once the DBMS informs the user that a transaction has been successfully completed, its effects should persist even if the system crashes before all its changes are reflected on disk. durability.


Consistency and Isolation Users are responsible for ensuring

transaction consistency Transection will leave DB in Consistent state

• 100 depit acount A• 99 credit acount B, 1 difference ins users

logic problem isolation ensured by guaranteeing that

even though actions of several transactions might be interleaved, the net effect is identical to executing all transactions one after the other in some serial order.


Atomicity of Transactions A transeciton can be incomplete for

Being ABORTED, or terminated due to some kind of anomaly DBMS• İf terminated by DBMS it is restarted

System crash Unexpected stuation (access some disk )

a transaction that is interrupted in the middle may leave the database in an inconsistent state . either all of a transaction's actions are carried

out, or none are.DMBS undo actions from logs


Atomicity of Transactions

A transaction might commit after completing all its actions, or it could abort (or be aborted by the DBMS) after executing some actions.

A very important property guaranteed by the DBMS for all transactions is that they are atomic. That is, a user can think of a Xact 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.


http://www.vbdotnetheaven.com/blogs/4995/transaction-processing-concept-in-ado-net


Example

Consider two transactions (Xacts):

T1: BEGIN A=A+100, B=B-100 ENDT2: 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.


Example (Contd.)

Consider a possible interleaving (schedule):

T1: A=A+100, B=B-100 T2: A=1.06*A, B=1.06*B

This is OK. But what about:T1: A=A+100, B=B-100 T2: A=1.06*A, B=1.06*B

The DBMS’s view of the second schedule:

T1: R(A), W(A), R(B), W(B)T2: R(A), W(A), R(B), W(B)


Scheduling Transactions a schedule represents an actual or

potential execution sequence. DBMS interleaves the actions of

different transactions to improve performance


Scheduling Transactions Ensuring transaction isolation while

permitting such concurrent execution is difficult, but is necessary for performance reasons

I/O activity can be done in parallel with CPU activity in a computer.

Over-lapping I/O and CPU activity, Reduce

• i/o , cpu idle time Increase

• system throughput


Scheduling Transactions

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.

(Note: If each transaction preserves consistency, every serializable schedule preserves consistency. )


Anomalies with Interleaved Execution

Two actions on the same data object conflict if at least one of them is a write Write-Read WR conflict T1 T2 «dirty read» Read-Write RW conflict Write-Write WW conflict


Anomalies with Interleaved Execution

Reading Uncommitted Data (WR Conflicts, “dirty reads”):

Unrepeatable Reads (RW Conflicts):

T1: R(A), W(A), R(B), W(B), AbortT2: R(A), W(A), C

T1: R(A), R(A), W(A), CT2: R(A), W(A), C


Anomalies (Continued)

Overwriting Uncommitted Data (WW Conflicts):

if transaction does not reads object before writing it such a write is called a blind write

T1: W(A), W(B), CT2: W(A), W(B), C


Schedules Involving Aborted Transactions Intuitively, all actions of aborted

transactions are to be undone. if T2 had not been committed,

cascading abort of T1 and T2, also releated transection

But T2 is committed, thus it is Unrecoverable Schedule

recoverable schedule is one in which transactions commit only after (and if !) all transactions whose changes they read commit.


avoid cascading aborts schedule

If transactions read only the changes of committed transactions, not only is the schedule recoverable, but also aborting a transaction can be accomplished without cascading the abort to other transactions. Such a schedule is said to avoid cascading aborts


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.


Lock-Based Concurrency Control

Strict Two-phase Locking (Strict 2PL) Protocol: Each Xact must obtain a S (shared) lock on object

before reading, and an X (exclusive) lock on object before writing.

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.

If an Xact holds an X lock on an object, no other Xact can get a lock (S or X) on that object.

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


Deadlock Consider the following example:

transaction T1 gets an exclusive lock on object A, T2 gets an exclusive lock on B, T1 requests an exclusive lock on B and is queued, and T2 requests an exclusive lock on A and is queued. Now, T1 is waiting for T2 to release its lock and T2 is waiting for T1 to release its lock! Such a cycle of transactions waiting for locks to be released is called a deadlock


Deadlock Prevention giving each transaction a priority

and ensuring that lower priority transactions are not allowed to wait for higher priority transactions (or vice versa).

Timestamp priority. Ti requests a lock and transaction Tj

holds a conflicting lock• Wait –die

• lower priority transactions can never wait for higher priority transactions.

• Wound-wait• higher priority transactions never wait for lower

priority transactions


Deadlock Detection Deadlocks tend to be rare and typically

involve very few transactions The lock manager maintains a structure

called a waits-for graph to detect deadlock cycle The nodes correspond to active transactions,

and there is an arc from Ti to Tj if (and only if) Ti is waiting for Tj to release a lock. The lock manager adds edges to this graph when it queues lock requests and removes edges when it grants lock requests


CRASH RECOVERY

recovery manager of a DBMS is responsible for ensuring transaction atomicity and durability atomicity by undoing the actions of

transactions that do not commit durability by making sure that all actions of

committed transactions survive system crashes and media failures


after crashes

recovery manager is given control responsible

• for bringing the database to a consistent state

• for undoing the actions of an aborted transaction.


The Log

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 Xact id, so it’s easy to undo a specific Xact.

Log is often duplexed and archived on stable storage. All log related activities (and in fact, all CC related

activities such as lock/unlock, dealing with deadlocks etc.) are handled transparently by the DBMS.


Recovering 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 Xacts that were active, and all dirty pages in the buffer pool at the time of the crash.

Redo: Redoes 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 Xacts 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!)


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.


Sql server Transection isolation Dirty Reads occur when one transaction reads

data written by another, uncommitted, transaction. The danger with dirty reads is that the other transaction might never commit, leaving the original transaction with "dirty" data.

Non-repeatable Reads occur when one transaction attempts to access the same data twice and a second transaction modifies the data between the first transaction's read attempts. This may cause the first transaction to read two different values for the same data, causing the original read to be non-repeatable

Phantom Reads occur when one transaction accesses a range of data more than once and a second transaction inserts or deletes rows that fall within that range between the first transaction's read attempts. This can cause "phantom" rows to appear or disappear from the first transaction's perspective.


SQL Server's isolation models each attempt to conquer a subset of these problems, providing database administrators with a way to balance transaction isolation and business requirements. The five SQL Server isolation models are:

The Read Committed Isolation Model is SQL Server’s default behavior. In this model, the database does not allow transactions to read data written to a table by an uncommitted transaction. This model protects against dirty reads, but provides no protection against phantom reads or non-repeatable reads.


The Read Uncommitted Isolation Model offers essentially no isolation between transactions. Any transaction can read data written by an uncommitted transaction. This leaves the transactions vulnerable to dirty reads, phantom reads and non-repeatable reads.

The Repeatable Read Isolation Model goes a step further than the Read Committed model by preventing transactions from writing data that was read by another transaction until the reading transaction completes. This isolation model protect against both dirty reads and non-repeatable reads.


The Serializable Isolation Model uses range locks to prevent transactions from inserting or deleting rows in a range being read by another transaction. The Serializable model protects against all three concurrency problems.

The Snapshot Isolation Model also protects against all three concurrency problems, but does so in a different manner. It provides each transaction with a "snapshot" of the data it requests. The transaction may then access that snapshot for all future references, eliminating the need to return to the source table for potentially dirty data.


If you need to change the isolation model in use by SQL Server, simply issue the command:

SET TRANSACTION ISOLATION LEVEL <level>

where <level> is replaced with any of the following keywords: READ COMMITTED READ UNCOMMITTED REPEATABLE READ SERIALIZABLE SNAPSHOT


BEGIN TRAN

UPDATE authorsSET au_fname = 'John'WHERE au_id = '172-32-1176'

UPDATE authorsSET au_fname = 'Marg'WHERE au_id = '213-46-8915'

COMMIT TRAN


BEGIN TRAN

UPDATE authorsSET au_fname = 'John'WHERE au_id = '172-32-1176'

UPDATE authorsSET au_fname = 'JohnY'WHERE city = 'Lawrence'

IF @@ROWCOUNT = 5 COMMIT TRANELSE ROLLBACK TRAN


Create Proc TranTest1ASBEGIN TRAN

INSERT INTO [authors]([au_id], [au_lname], [au_fname], [phone], [contract])

VALUES ('172-32-1176', 'Gates', 'Bill', ' 800-BUY-MSFT', 1)

UPDATE authorsSET au_fname = 'Johnzzz'WHEREau_id = '172-32-1176'

COMMIT TRANGO


USE pubsDECLARE @intErrorCode INT

BEGIN TRAN UPDATE Authors SET Phone = '415 354-9866' WHERE au_id = '724-80-9391'

SELECT @intErrorCode = @@ERROR IF (@intErrorCode <> 0) GOTO PROBLEM

UPDATE Publishers SET city = 'Calcutta', country = 'India' WHERE pub_id = '9999'

SELECT @intErrorCode = @@ERROR IF (@intErrorCode <> 0) GOTO PROBLEMCOMMIT TRAN

PROBLEM:IF (@intErrorCode <> 0) BEGINPRINT 'Unexpected error occurred!' ROLLBACK TRANEND


Nested trasnectionFigure 1: A COMMIT always balances a BEGIN TRANSACTION by reducing the transaction count by one.

Figure 2: A single ROLLBACK always rolls back the entire transaction


USE pubsSELECT 'Before BEGIN TRAN', @@TRANCOUNT -- The value of @@TRANCOUNT is 0BEGIN TRAN SELECT 'After BEGIN TRAN', @@TRANCOUNT -- The value of @@TRANCOUNT is 1 DELETE sales BEGIN TRAN nested SELECT 'After BEGIN TRAN nested', @@TRANCOUNT -- The value of @@TRANCOUNT is 2 DELETE titleauthor COMMIT TRAN nested -- Does nothing except decrement the value of @@TRANCOUNT

SELECT 'After COMMIT TRAN nested', @@TRANCOUNT -- The value of @@TRANCOUNT is 1ROLLBACK TRAN

SELECT 'After ROLLBACK TRAN', @@TRANCOUNT -- The value of @@TRANCOUNT is 0 -- because ROLLBACK TRAN always rolls back all transactions and sets -- @@TRANCOUNT to 0.

SELECT TOP 5 au_id FROM titleauthor


USE pubsSELECT 'Before BEGIN TRAN', @@TRANCOUNT -- The value of @@TRANCOUNT is 0BEGIN TRAN SELECT 'After BEGIN TRAN', @@TRANCOUNT -- The value of @@TRANCOUNT is 1 DELETE sales BEGIN TRAN nested SELECT 'After BEGIN TRAN nested', @@TRANCOUNT -- The value of @@TRANCOUNT is 2 DELETE titleauthor ROLLBACK TRAN SELECT 'After COMMIT TRAN nested', @@TRANCOUNT -- The value of @@TRANCOUNT is 0 because -- ROLLBACK TRAN always rolls back all transactions and sets @@TRANCOUNT -- to 0.

IF (@@TRANCOUNT > 0) BEGIN COMMIT TRAN -- Never makes it here cause of the ROLLBACK SELECT 'After COMMIT TRAN', @@TRANCOUNTEND

SELECT TOP 5 au_id FROM titleauthor


CREATE PROCEDURE addTitle(@title_id VARCHAR(6), @au_id VARCHAR(11), @title VARCHAR(20), @title_type CHAR(12))AS

BEGIN TRAN INSERT titles(title_id, title, type) VALUES (@title_id, @title, @title_type)

IF (@@ERROR <> 0) BEGIN PRINT 'Unexpected error occurred!' ROLLBACK TRAN RETURN 1 END

INSERT titleauthor(au_id, title_id) VALUES (@au_id, @title_id)

IF (@@ERROR <> 0) BEGIN PRINT 'Unexpected error occurred!' ROLLBACK TRAN RETURN 1 END

COMMIT TRAN

RETURN 0

IF @@ERROR <> 0 BEGIN RAISERROR('error occured while recording purchase', 16, 1) ROLLBACK END

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