icom 6005 – database management systems design

ICOM 6005 – Database Management ICOM 6005 – Database Management Systems DesignSystems Design

Dr. Manuel Rodríguez-Martínez

Electrical and Computer Engineering Department

Lecture 16 – Intro. to Transactions Processing and Concurrency Control

ICOM 6005 Dr. Manuel Rodriguez Martinez 2

Transaction ProcessingTransaction Processing

• Read :– Chapter 16, sec 16.1-16.6– Chapter 17– ARIES papers

• Purpose:– Study different algorithms to support transactions

and concurrency control in a DBMS


IntroductionIntroduction

• DBMS software and supporting server machine are a big investment

• Enterprise wishes to maximize its use• If each users get to use the DBMS by itself for a short

period of time, it takes a lot of time to run the tasks• Multiple user must be allowed to access the DBMS at

the same time– Concurrent access

• DBMS might crash– Power fails, software bugs appears, hardware fails, soda is

spilled …– Need recovery mechanism to recover loss data


Multiple-Users using a DBMSMultiple-Users using a DBMS

DBMS

T1T4 T3 T2

Waiting Queue

Users wait to get a hold onDBMS to run their tasks.Context switches make thisinefficient


Multiple-Users using a DBMS (2)Multiple-Users using a DBMS (2)

DBMS

T1T4

T3T2

DBMS executes differentTasks at the same time.Maximizes system throughput


System CrashSystem Crash

T1T2

Data Data

Disk is gone

Updates are lost


System Crash (2)System Crash (2)

T1T2

DataData

Disk is gone

Updates are lost

How to recover?


Concurrency and RecoveryConcurrency and Recovery

• DBMS must support– Concurrency

• Allow different users to access DBMS at the same time

• Control access to data to prevent inconsistencies in DBMS

– Recovery• Track progress of operations by an users

– Use a log for this

• If a crash occurs, must use this log to recover operations that were completed

• Log must be stored independently of data to prevent losing both

• Transactions – unit of work used by DBMS to support concurrency and recovery


Relational DBMS ArchitectureRelational DBMS Architecture

Disk Space Management

Buffer Management

File and Access Methods

Relational Operators

Query Optimizer

Query Parser

Client API

Client

DB

ExecutionEngine

Concurrencyand Recovery


The need for concurrency The need for concurrency

• Jil and Apu are married and share baking account A.• Jil and Apu go to the bank at the same time and use to different

ATMs– Jil asks to withdraw $300 from the $500 in A– Apu ask to withdraw $400 from the $500 in A

• The following might happen:– At ATM 1: System reads $500 in A– At ATM 2: System reads $500 in A– At ATM 1: System deducts $300 from A– At ATM 2: System deducts $400 from A– At ATM 1: Systems stored $200 as balance in A– At ATM 2: Systems stored $100 as balance in A

• Jil and Apu got $700 out of their $500 in account A!• DBMS must prevent such events via concurrency control


The need for recoveryThe need for recovery

• Tom goes to bank with a $1,000 deposit for this account A, which currently has $500

• Tom talks with teller X.• The following might happen:

– Teller X reads A and finds $500 dollars– Tom gives $1,000 to teller X in an envelope– Teller X changes balance in A to $1,500– Teller X sends a request to DBMS to update A to $1,500– Power fails at this time

• What is the balance of A?– $500 or $1,500? How do we make sure it is $1,500?

• DBMS must support recovering correct balance via crash recover


Transactions and ACID propertiesTransactions and ACID properties

• Transactions are the unit of work used to submit tasks to the DBMS– Selects, inserts, deletes, updates, create table, etc.

• Transactions must support ACID properties– Atomicity – all operations included in a transactions are

either completed as a whole or aborted as whole– Consistency – each transactions reads a consistent DB and

upon completion leaves DB in another consistent state– Isolation – transactions running concurrently have the same

effect on the DB as if they had been run in serial fashion • One at the other

– Durability – changes made by committed (transactions) survive crashes and can be recovered. Changes made by aborted transactions are undone


Supporting Transactions at DBMSSupporting Transactions at DBMS

• Transaction Manager– Module in charge of supporting transaction at DBMS

• Sub-components– Lock Manager

• Deals with granting locks to transaction to get access to DB objects such as records, data pages, tables or whole databases

– Log/Recovery Manager• Deals with tracking operations done by transactions as well as

determining which ones commit and which ones abort. After a crash, it recovers work done by committed transactions.

• Implementing Transaction Manager– Modules integrated with DBMS – Separate process from DBMS

• TP Monitor


SchedulesSchedules

• We can model operations done by a transaction with a schedule– List of operations done: read, write, plus logical operations– Often, we just care about

• Reads

• Writes

• Abort requests

• Commit requests

• Changes to individual objects (optional, just for clarity).

– Assumptions: • Only inter-transaction interaction is via reads/writes of shared

objects


Example SchedulesExample Schedules

T1 T2

R(A)

R(B)

W(A)

R(C)

W(B)

Commit

W(C)

Commit

T1 T2

R(A)

R(B)

W(A)

R(C)

W(B)

Abort

W(C)

Commit

Each row represent an action take a some pointIn time. DBMS make one action at a time

Schedule 1Schedule 2


Serialization of SchedulesSerialization of Schedules

• Serial schedule:– A schedule in which each transaction T1, T2, …, Tk is executed

one after the other without interleaving

• Key idea: – Transactions that interleave operations are ok as long as their

schedule is equivalent to a serial schedule

• Serializable schedule on transactions T1, T2, …, Tk– Its effect are equivalent to a serial schedule

– Performance is better• Interleaving of operations

• Not all schedules are serializable • System throughput – number of transactions completed per unit

of time– Increases with serializable transactions


Example of serializabilityExample of serializability

T1 T2

R(A)

R(B)

W(A)

R(C)

W(B)

Commit

W(C)

Commit

Schedule 1

T1 T2

R(A)

W(A)

R(C)

W(C)

Commit

R(B)

W(B)

Commit

Serial equivalent


Anomalies due to interleavingAnomalies due to interleaving

• You want your schedules to be serializable• Otherwise, the following things (considered bad)

could happen– Write-read (WR) conflicts– Read-write (RW) conflicts– Write-write (WW) conflicts

• SQL allows you to decide the level of concurrency you need– By default you get serializable support


Write-Read conflictsWrite-Read conflicts

• Transaction T1 reads uncommitted data produced by transaction T2.– Called a dirty read– Now, if T2 aborts, the work done by T1 is inconsistent

• Example: T1 and T2 access Bank account A– T1 reads A with balance $1000– T1 substract $100 from A – T2 reads A with balance $900– T1 aborts– T2 substract $200 from A – T2 stores A with balance $700– T2 commits

• Problem: Balance should be $800 not $700


Read-write conflicts Read-write conflicts

• Transaction T1 reads some object A, which is also read and modified by T2.

• When T1 reads A, the value has changed!!!– Called unrepeatable read

• Example: T1 and T2 access Bank account A– T1 reads A with balance $1000– T1 checks balance > $500, goes to do other checks– T2 reads A with balance $1000– T2 subtracts $700– T2 writes A– T2 commits – T1 reads A again– T1 subtracts $500 from A– T1 writes A– T1 commits

• Balance is - $300.


Write-Write ConflictsWrite-Write Conflicts

• Transactions T1 reads object A, and T2 writes a new value to object A.

• T1 then writes A to the DB – Called a blind write

• Example: T1 and T2 access Bank account A– T1 reads A with balance $1000– T2 sets A to $2000– T2 writes A– T2 commits – T1 subtracts $500 from A– T1 writes A– T1 commits

• Balance is $500, but update from T2 is lost

icom 6005 – database management systems design

Documents

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different users

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transactions processing

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