chapter 11 transaction concepts l.
Download
Skip this Video
Loading SlideShow in 5 Seconds..
Chapter 11: Transaction Concepts PowerPoint Presentation
Download Presentation
Chapter 11: Transaction Concepts

Loading in 2 Seconds...

play fullscreen
1 / 38

Chapter 11: Transaction Concepts - PowerPoint PPT Presentation


  • 152 Views
  • Uploaded on

Chapter 11: Transaction Concepts. Service-Oriented Computing: Semantics, Processes, Agents – Munindar P. Singh and Michael N. Huhns, Wiley, 2005. Highlights of this Chapter. Basic concepts ACID properties Schedules Locking Transactions over composed services Relaxing serializability

loader
I am the owner, or an agent authorized to act on behalf of the owner, of the copyrighted work described.
capcha
Download Presentation

PowerPoint Slideshow about 'Chapter 11: Transaction Concepts' - padma


An Image/Link below is provided (as is) to download presentation

Download Policy: Content on the Website is provided to you AS IS for your information and personal use and may not be sold / licensed / shared on other websites without getting consent from its author.While downloading, if for some reason you are not able to download a presentation, the publisher may have deleted the file from their server.


- - - - - - - - - - - - - - - - - - - - - - - - - - E N D - - - - - - - - - - - - - - - - - - - - - - - - - -
Presentation Transcript
chapter 11 transaction concepts
Chapter 11:Transaction Concepts

Service-Oriented Computing: Semantics, Processes, Agents– Munindar P. Singh and Michael N. Huhns, Wiley, 2005

highlights of this chapter
Highlights of this Chapter
  • Basic concepts
    • ACID properties
    • Schedules
    • Locking
  • Transactions over composed services
  • Relaxing serializability
  • Extended transaction models

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

motivation
Motivation

As services are employed for serious purposes, they will inevitably update information resources

  • Can we be sure that such updates preserve integrity?
  • What about when multiple services need to work together?
  • What about when the services are involved in a long-lived activity?

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

transactions 1
Transactions: 1
  • A transaction is a computation (i.e., program in execution) that accesses and possibly modifies a database:
    • Not the source code; not the binaries
    • Can be interleaved with other transactions
    • But guarantees certain correctness properties

The purpose of the transaction concept is to avoid the problems (“race conditions”) that may arise from interleaving

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

transactions 2
Transactions: 2
  • Operation: action on a data item
  • Transaction: set of operations performed in a partial order according to the specifying program
    • Assume total order here for simplicity

A transaction makes a set of operations appear as one logical operation

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

acid properties
ACID Properties
  • If programmers guarantee correctness of individual transactions, then DBMS guarantees correctness of any set of them
  • The ACID properties formalize the notion of a transaction behaving as one operation
    • (Failure) Atomicity—all or none—if failed then no changes to DB or messages
      • This is the vernacular notion of “transaction”
    • Consistency—don't violate DB integrity constraints: execution of the op is correct
    • Isolation (Atomicity)—partial results are hidden
    • Durability—effects (of transactions that "happened" or committed) are forever

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

transaction lifecycle
Transaction Lifecycle

A transaction goes through well-defined stages in its life (always terminating)

  • Inactive
  • Active (may read and write)
    • Entire business logic takes place here
  • Precommit (no errors during execution; needed for mutual commitment protocols)
  • Failed (errors)
  • Committed (the DBMS decides this)
  • Forgotten (the DBMS reclaims data structures)

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

schedules
Schedules
  • Schedules are histories of computations showing all events of interest
  • Schedule of T1...Tn has all ops of T1...Tn in the same order as within each Ti, but interleaved across Ti to model concurrency
    • Includes active transactions
    • Typically a partial order among events
  • Two challenges
    • What are the bad schedules?
    • How can the DBMS prevent them?

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

conflict
Conflict

Order-sensitivity of operations

  • Two operations of different transactions, but on the same data item, conflict if
    • Their mutual order is significant, i.e., determines at least one of the following:
      • The final value of that item read by future transactions
      • The value of the item as read by present transactions

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

serial schedules
Serial Schedules

Transactions are wholly before or after others (i.e., occur one by one)

  • Clearly, we must allow for service requests to come in slowly, one-by-one
  • Thus, under independence of transactions (assuming each transaction is correct), serial schedules are obviously correct

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

serializable schedules
Serializable Schedules
  • Interleaved schedules are desirable
    • Why?
  • Those equivalent to some serial schedule. Here equivalent can mean
    • Conflict equivalent—all pairs of conflicting ops are ordered the same way
    • View equivalent—all users get the same view

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

achieving serializability
Achieving Serializability
  • Optimistically: Let each transaction run, but check for serializability before committing
  • Pessimistically: Use a protocol, e.g., locking, to ensure that only serializable schedules are realized

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

locks
Locks

Lock item x while using item x

  • Binary: at most one party may lock x
    • Lock(x): acquire the lock
      • Computation hangs until lock(x) returns, i.e., the lock is acquired
    • Unlock(x): relinquish the lock
    • Gives mutual exclusion but restrictive

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

multimode locks
Multimode Locks

When one party has an exclusive lock, no other party may have an exclusive or a shared lock

  • Shared-lock(x) needed for read(x)
    • Others can also hold a shared lock
  • Exclusive-lock(x) needed for write(x)
    • No one else can concurrently hold a shared or exclusive lock
  • Can be upgraded (read to write) or downgraded (write to read)

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

achtung
Achtung!
  • By itself, using locks does not guarantee serializability
    • What is an example of a bad schedule obtained while using locks?
  • A locking protocol, i.e., how locks are acquired and released, is critical
  • That is, locks on different data items must be related

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

two phase locking 2pl
Two-Phase Locking (2PL)
  • Two phases in a transaction’s life
    • Growing phase: acquire but not release locks
    • Shrinking phase: release but not acquire locks
  • Guarantees serializability, but can deadlock
  • Strict 2PL releases all locks at once when the transaction commits or rolls back
    • Ensures rigorous schedules (to be discussed)
    • But can deadlock
  • Conservative 2PL: takes all locks early; risks starvation

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

reading from
Reading From

T1 reads from T2 if the schedule contains a subsequence w2(x)...r1(x), where

  • w2 is the first write on x going backwards from r1(x)
  • a2 doesn’t occur between w2 and r1

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

recoverable schedules
Recoverable Schedules

In which a transaction commits after all transactions it read from have committed

  • In terms of the ACID properties, what is the risk in allowing a nonrecoverable schedule?

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

avoid cascading aborts aca
Avoid Cascading Aborts (ACA)

In which a transaction does not read from uncommitted transactions

  • What is the risk in allowing such reads?
  • Are cascading aborts
    • Legal?
    • Expensive?

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

strict schedules
Strict Schedules

In which an item can't be read or written until the previous transaction to write that item has committed (the aborted ones having been factored out)

  • Compare with ACA
  • This allows us to UNDO by restoring the before image

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

rigorous schedules
Rigorous Schedules

In which an item can't be read or written until the previous transaction to read or write that item has committed

  • Compare with strict schedules

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

distributing acid transactions
Distributing ACID Transactions
  • ACID transactions are applicable for
    • Brief, simple activities (few updates; seconds, at most)
    • On centralized architectures
  • Without distribution, ACID transactions would be a nonstarter outside of a single DBMS

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

closed nested distributed transactions
Closed-Nested Distributed Transactions

ACID transactions can be implemented in distributed settings

  • Consider two or more subtransactions, conceptually organized as a tree
    • Ensure atomicity through two-phase commit (2PC)
    • Ensure isolation so that results are not exposed till the global transaction commits
  • As in WS-AtomicTransaction

Why would ACID transactions ever be useful for SOC?

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

transactions over composed services
Transactions over Composed Services

Composed service as a transaction

Expedia

Assume each service ensures serializability locally

Two main kinds of service agreements are possible:

  • Execution, e.g., LDB retains full control on execution even if in conflict with CTM
  • Communication, e.g., LDB decides what (control) information to release

Composed Transaction Manager

Direct

users

service

service

United

Sheraton

LDB1

LDB2

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

compositional serializability
Compositional Serializability

Transactions throughout the system should be serializable

  • CTM ensures that the composed transactions are serializable
  • This doesn't guarantee compositional serializability, because of indirect conflicts:
    • CTM does T1: r1(a); r1(c)
    • CTM does T2: r2(b); r2(d)
    • LDB1 does T3: w3(a); w3(b)
    • LDB2 does T4: w4(c); w4(d)
    • Since T1 and T2 are read-only, they are serializable.
    • LDB1 sees S1=r1(a); c1; w3(a); w3(b); c3; r2(b); c2
    • LDB2 sees S2=w4(c); r1(c); c1; r2(d); c2; w4(d); c4
    • Each LDB has a serializable schedule; yet jointly they put T1 before and after T2
  • Notice we would have lots of potential compositions, so the problem is worse

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

strawman 1 tickets
Strawman 1: Tickets

Compositional serializability fails because of local conflicts that the CTM does not see

  • Fix by always causing conflicts--whenever two composed transactions execute at a site, they must conflict there. Indirect conflicts become local conflicts visible to the LDB
    • Make each composed transaction increment a ticket at each site
  • Downside:
    • Causes all local subtransactions of a transaction to go through a local hotspot
    • Composed transactions are serialized, but only because many are aborted!

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

strawman 2 rigorous scheduling
Strawman 2: Rigorous Scheduling

Hold read and write locks till end (no tickets)

  • Check that this prevents the bad example
  • The CTM must delay all commits until all actions are completed
    • possible only if allowed by LDB
    • requires an operation-level interface to LDB
  • Downside:
    • Causes all sites to be held up until all are ready to commit
    • Essentially like the 2PC approach

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

possible methodology
Possible Methodology
  • When no cross-service constraints apply, local serializability is enough
  • Split data into local and shared partitions
    • LDB controls local data
    • CTM controls shared (local transactions can read, but write only via CTM)
  • Downside: doesn’t work in all cases
    • All shared data is managed through a special service
    • Only for the most trivial compositions

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

compositional atomicity
Compositional Atomicity
  • Can succeed only if the services restrict their autonomy through service-level agreements, e.g., 2PC
  • Otherwise, the services
    • May not release their prepare-to-commit state
    • May not participate in a mutual commit protocol such as 2PC

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

compositional deadlock
Compositional Deadlock

Assume LDB1 and LDB2 use 2PL. If a deadlock is formed

  • Solely of upper-level transactions, then the CTM may detect it
  • Of a combination of local and upper transactions, then
    • CTM won't know of it
    • LDBs won't share control information

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

compositional atomicity durability
Compositional Atomicity & Durability

Without 2PC, what would happen when a CT fails?

  • Each service individually ensures “correctness” according to its local policies
  • Achieve weaker atomicity, durability via:
    • Redo: rerun the writes from log
    • Retry: rerun all of a subtransaction
    • Compensate: semantically undo all other subtransactions

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

beyond acid transactions
Beyond ACID Transactions
  • Composed services feature in business processes, which
    • Cross administrative boundaries
    • Are complex, i.e., long-running, failure-prone, multisite, with subtle consistency requirements
    • Cooperate with other processes, involving computational and human tasks
    • Respect autonomy and heterogeneity of components

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

extended transactions
Extended Transactions

Extended transaction models relax the ACID properties by modifying various features

  • Allowing open nesting, wherein partial results are revealed (newer, non-ACID)
  • Atomicity, e.g., contingency procedures, to ensure “all”
  • Consistency restoration, e.g., via compensation, to ensure “none”
  • Constraints among subtransactions, such as
    • Commit dependencies
    • Abort dependencies

Ultimately, a transaction must be atomic (albeit in a relaxed sense)

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

compensation
Compensation
  • Something that semantically undoes the effect of a transaction
  • Common in business settings
  • Compensations are necessary even if imperfect
    • Deposit and withdraw
    • Reserve and cancel
    • Ship and return
    • Pay and refund

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

extended transaction models
Extended Transaction Models
  • The ones we consider
    • Sagas
    • Flex Transactions
    • DOM Transactions
  • Several others, mostly either
    • Implementation-specific or
    • Narrower than the above
  • General-purpose scheduling approach (Chapter 14)

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

sagas
Sagas
  • Guarantee atomicity but not isolation
  • Execute a sequence of transactions
    • If all transactions succeed, then good (all)
    • If any transaction fails, undo all previous in reverse order (none)
  • Assumptions
    • Compensations succeed (eventually) for the first several members of sequence
    • Retries succeed for the last several

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

distributed object management
Distributed Object Management

Avoid partial failure of a multitransaction via either total success or total failure

  • Total success
    • Redo from log
    • Retry
    • Contingency procedures
  • Total failure
    • Undo from log
    • Compensations

Uses ordering constraints and vital subtransactions

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns

chapter 11 summary
Chapter 11 Summary
  • We need a means to ensure that services behave reasonably, i.e., by ensuring the integrity of data
  • Database management provides the notion of transactions for this purpose
  • Distributed transactions can apply in closed settings
  • Ensuring the ACID properties is infeasible in open settings
  • Extended transaction models are needed
    • Simple constructs of such models are helpful, and being encoded in standards
    • Often, an important application is process management (coming up)
    • More sophisticated behaviors require increased intelligence in modeling and enactment, also to be discussed later

Service-Oriented Computing: Semantics, Processes, Agents - Munindar Singh and Michael Huhns