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Transactions. Paul Greenfield CSIRO. Why?. Why are transactions and transaction processing interesting? They make it possible for mere mortals to program high performance, reliable and scalable computing systems The basis of enterprise ‘mission critical’ computing. Programming is simple.

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Paul Greenfield


  • Why are transactions and transaction processing interesting?
    • They make it possible for mere mortals to program high performance, reliable and scalable computing systems
    • The basis of enterprise ‘mission critical’ computing
programming is simple
Programming is simple
  • Most business operations are really quite simple
    • Sell a book, withdraw cash, book a ticket, trade stocks, ….
      • Some database lookups
      • Some computation
      • Some database updates
  • But in the real world…
real programming is hard
Real programming is hard
  • Real systems have to be fast
  • Real systems have to scale
  • Real systems have to be reliable
  • Real systems have to recover from failure when it does happen
  • And real systems are built by the average programmer
speed and scale
Speed and Scale
  • Speed
    • Responding quickly to requests
    • Customers can’t be kept waiting too long, especially on the Web
  • Scale
    • Banks have thousands of ATMs, stores have hundreds of registers, Web sites can have many thousands of users
    • All need fast response times
speed and scale1
Speed and Scale
  • Solution is concurrency
    • Doing more than one operation at a time
    • Processing while waiting for I/O
    • Using multiple processors
  • Problem is concurrency
    • Interference between programs
    • Conflicts over shared resources
      • Can’t sell the same seat twice
  • What happens when a computer systems is down?
    • Lost customers, sales, money, ….
    • 24x7 operations, 99.99% availability
  • Solutions
    • Stand-by systems (warm or hot)
    • Clusters
    • Based on transactions
  • Computer hardware fails!
  • System software has bugs!!
  • Application programs have bugs!!!
  • System still has to be reliable!!!!
    • Fail cleanly (maintain data integrity)
    • Recover from transient errors
    • Recover after system failure
data integrity
Data Integrity
  • Business has rules about its data
    • Money must always be accounted for
    • Seats cannot be sold twice or lost
  • Easy if system never fails…
  • Transactions maintain integrity despite failures
transaction systems
Transaction Systems
  • Efficiently handle high volumes of requests
  • Avoid errors from concurrency
  • Avoid partial results after failure
  • Grow incrementally
  • Avoid downtime
  • And … never lose data
ancient history
Ancient History
  • Earliest transaction systems
    • Airline reservations (1960’s)
      • SABRE. 300,000 devices, 4200 requests/sec custom-made OS
    • Banking, government and other very large systems (1970’s)
      • CICS, IMS, COMS, TIP
      • Large (expensive) mainframe computers
recent past
Recent Past
  • UNIX systems (1980’s…)
    • TP monitors
      • Tuxedo, TopEnd, Encina, CICS, …
      • Object Transaction Monitors
    • Databases
      • Oracle, Sybase, Informix
    • Basis for mainstream commercial computing
      • Coexisting with mainframe TP
  • Commodity transaction processing
    • Windows NT, Windows 2000
    • MTS and COM+ from Microsoft
    • UNIX TP ports
      • Tuxedo, Orbix, Web Logic, …
    • SQL/Server, Oracle, …
  • Becoming pervasive
what is a transaction
What is a Transaction?
  • A complete, indivisible business operation
    • Book a seat
    • Transfer money
    • Withdraw cash
    • Sell something
    • Borrow a book
  • Transaction systems must pass the ACID test
    • Atomic
    • Consistent
    • Isolated
    • Durable
  • Transactions have to be atomic
    • All or nothing
    • Execute completely or not at all
    • Even after failure and recovery
    • Successful transactions commit
      • Changes made permanent
    • Failing transactions abort
      • Changes backed out
atomic example
Atomic Example
  • Transferring money
    • Move $100 from account A to account B
      • Take $100 from account A
      • Put $100 in account B
    • Both actions have to take place or none
    • Failure after withdrawal step?
      • Money disappears??
  • Move data from one consistent state to another
    • Money in bank is accounted for and not ‘lost‘
  • Really an application program responsibility
    • But AID makes helps by making programming simpler
  • Every transaction thinks it is running all alone (isolated)
  • Reality of concurrency is hidden
  • Transactions running together do not interfere with each other
  • Looks like transactions are run serially
  • Illusion assisted by databases
isolation example
Isolation Example
  • Banking
    • Two ATMs trying to withdraw the last $100 from an account

fetch balance from account

fetch balance from account

update account (balance=balance-$100)

update account(balance=balance-$100)

    • Isolation stops this from happening
      • Second transaction waits for first to complete
  • Once changes are committed they are permanent
    • Even after failure and recovery
    • Changes written to disk
    • Wait for write to complete
  • Largely responsibility of database
    • DB told to commit changes by transaction manager
distributed transactions
Distributed Transactions
  • Now do all this across multiple computer systems…
    • Geographically dispersed
    • Multiple application servers
    • Multiple database servers
  • All working together
    • A single transaction can use all of these resources
    • Full ACID properties still maintained
distributed transactions1
Distributed Transactions
  • What happens when a transaction updates data on two or more systems?
  • Transaction still needs to be atomic
    • All updates succeed or all fail
  • But systems can independently fail and recover!
    • Transaction manager keeps track and coordinates changes using 2PC
no two phase commit
No Two Phase Commit?
  • Without 2PC updates can be lost and data can become inconsistent when systems fail and recover

Withdraw $100Deposit $100


Withdraw $100Commit


Deposit $100*System fails*

System recovers but update lost

Money withdrawn but deposit lost

two phase commit
Two Phase Commit
  • Transaction manager coordinates updates made by resource managers
  • Phase 1
    • Prepare to commit
  • Phase 2
    • Commit
  • Transaction manager always knows the state of the transaction
phase 1
Phase 1
  • Transaction manager asks all RMs to prepare to commit.
    • RMs can save their intended changes and then say ‘yes’.
    • Any RM can say ‘no’.
    • No RM actually commits yet!
  • If all RMs said ‘yes’, go to Phase 2.
  • If any RMs said ‘no’, tell everyone to abandon their intended changes.
phase 2
Phase 2
  • Transaction manager asks all resource managers to go ahead and commit their changes.
  • Can now recover from failure
    • RM knows what transactions were questionable at point of failure
    • TM knows whether transactions succeeded or failed
two phase commit1
Two Phase Commit













Successful transaction

Failing transaction

transaction managers
Transaction Managers
  • Just what is a TM?
    • Can be part of the database software
      • Updating multiple Oracle databases…
    • Can be part of a ‘transaction monitor’
      • CICS, Tuxedo, …
    • Can be stand-alone
      • MS DTC, X/Open model
distributed transactions2
Distributed Transactions
  • Multiple Transaction managers
    • One per node (computer) involved, looking after their local resource managers
    • TMs cooperate in distributed transactions
  • Produces transaction trees
    • Each TM coordinates TMs below it
    • One root TM (where it all started)
    • New branch when apps invoke code or access a resource on a new node
transaction trees
Transaction Trees










x open standards
X/Open Standards
  • Standard model and interfaces
    • XA: TM to RM
    • TX: Application to TM

Application program




Resource manager

Transaction manager

  • Much more than just databases
    • ATMs, printers, terminal responses, …
    • Can only issue cash or print cheque if transaction is successful

Begin update account dispense cashCommit

Begin update accountCommit dispense cash


  • Older TP systems supported files, printers, terminal output, data comm
    • App wrote output normally
    • OS/TP deferred actual output until transaction committed
  • Application problem?
    • Write to database for background app?
    • Use transactional message queues?
tp monitor
TP Monitor
  • Mainframe transaction processing (TP)
    • CICS, IMS, COMS, TIP, …
    • Terminals, batch input
    • Screen formatting
    • Message-based with transaction code routing
    • Normally ‘stateless applications’ for scalability
  • Transaction is a single atomic and complete operation
    • No data left behind in application
  • Scalability through multiple copies of server applications
    • A transaction can be sent to any copy of the application
    • Copies can be created as necessary
  • Burroughs/Unisys TP Monitor (1984+)

TP app


TP app


controlling transactions
Controlling Transactions
  • Who really controls the transaction?
    • Client or server?
    • Explicit vs implicit transactions?
    • SQL transactions
  • Started somehow
    • Tx_begin, method call, SQL statement
  • Finished by application code
    • Commit or Abort
api models
API Models
  • Client-side transaction control
    • Explicit begin-transaction
    • Explicit Commit/Abort
  • Server-side transaction control
    • Perform one complete business transaction in each call

Tx_beginCall withdraw(accno, amount)Call deposit(accno, amount)SQL insert into audit ….Tx_commit

Dim acc = new AccountAccount.transfer(accfrom, accto, amount)

transaction models
Transaction Models
  • Server-side fits with n-tier models
    • Client just does presentation
    • Business logic in server transactions
    • Declarative transactions (EJB, MTS)
    • No leakage between layers




api models1
API models
  • Message-based
    • Route by transaction code (eg BKFLT)
    • Very flexible, returns another message
  • Procedure calls (RPC-based)
    • Calling transactional procedures with parameters & return values
  • Method calls
    • Objects with transactional methods
procedure models
Procedure Models
  • Extension of RPC technologies
    • Encina
    • Faded technology, not fashionable
    • Not object-oriented
  • Marshalling parameters
    • Turns function to message & back
    • Mask differences between platforms
    • Uses proxies and stubs
object models
Object Models
  • Extension of ORB technologies
    • Call methods on remote objects
    • CORBA standards (OTMs)
    • Fading technology
  • An OO model
    • Objects on servers  state on server
    • Balancing load? Scalability?
component models
Component Models
  • Rising star
    • Microsoft with MTS & COM+
    • EJB
  • Call methods on remote components
    • Look like objects to clients
    • Normally stateless
  • Declarative
    • Transactional-ness is a property, not coding concern
  • Clients think they have server objects
    • Reference stays around but not object
    • Object created when method called
    • Object ‘destroyed’ when method finishes
  • Reduced server resource usage
  • Methods can run anywhere
    • Not bound to server objects
    • Scales to server farms
more complications
More Complications
  • Security
  • Implementation models & internals
  • Scaling questions
  • Reliability and fault-tolerance
  • Programming models
next week
Next Week
  • Databases
    • How do we get isolation?
    • How do recover?
  • More technical details
    • Protocols, logging
    • Recovering from failure