Presentation on theme: "CM20145 Transactions & Serializability"— Presentation transcript:
1 CM20145 Transactions & Serializability Chris MiddupCM20145 Transactions & Serializability
2 Lecture Plan Basic Concepts Data, Information & Knowledge Data Models (The E-R Model)The Relational AlgebraIntroduction to SQLFurther SQL (Joins, RA Equivalences)Database DesignFurther DB Design – NormalisationArchitectures and ImplementationsIntegrity and Security
3 Lecture Plan Ethics and Professional Conduct Legal Issues Transactions RecoveryConcurrency ControlStorage and File StructureIndexing and HashingQuery Processing & OptimisationXML DatabasesRevision
4 A While Ago… Now: Transactions, Concurrency & Recovery Architectures and ImplementationsIntroductions to Transactions & StorageArchitecture concerns:Speed, Cost, Reliability, Maintainability.Architectural Types:Centralized, Client/Server, Parallel, DistributedIntegrity and SecurityDomain ConstraintsReferential IntegrityForeign Keys, Cascading ActionsAssertionsTriggersAuthorizationGrant, Revoke, Roles, Audit TrailsNow: Transactions, Concurrency & Recovery
7 To preserve integrity of data, the database system must ensure: The ACID TestAtomicity: Either all operations of the transaction are properly reflected in the database or none are.Consistency: Execution of a transaction in isolation preserves the consistency of the database.Isolation: Although multiple transactions may execute concurrently, each transaction must be unaware of other concurrently executing transactions; intermediate transaction results must be hidden from other concurrently executed transactions.Durability: After a transaction completes successfully, the changes it has made to the database persist, even if the system fails.
8 Example: A Fund Transfer Transfer $50 from account A to B:1. read(A)2. A := A – 503. write(A)4. read(B)5. B := B + 506. write(B)Durability: once the user notified that the transaction complete, the updates to the database by the transaction must persist despite failures.Isolation: between steps 3-6, no other transaction should access the partially updated database, or it would see an inconsistent state (A + B will be less than it should be).Consistency: the sum of A and B is unchanged by the execution of the transaction.Atomicity: if the transaction fails after step 3 and before step 6, the system must ensure that no updates are reflected in the database, else an inconsistency will result.
9 Transaction StatesActive, the initial state; the transaction stays in this state while it is executingPartially committed, after the final statement has been executed.Committed, after successful completion.Failed, after the discovery that normal execution can no longer proceed.Aborted, after the transaction has been rolled back and the database restored to its state prior to the start of the transaction.
10 Transaction Definition in SQL Data manipulation languages must include a construct for specifying the set of actions that comprise a transaction.In SQL, a transaction begins implicitly.A transaction can be explicitly ended by:Commit work: commits current transaction and begins a new one.Rollback work: causes current transaction to abort.
12 Schedules & Concurrency Advantages to Concurrent execution (executing transactions simultaneously):Increased processor and disk utilization; better throughput.E.g. one transaction uses CPU while another uses disk.Reduced average response time.Short transactions need not wait behind long ones.Concurrency control schemes:Mechanisms to achieve isolation.Control concurrent transactions’ interaction to maintain database consistency.Schedules:Def: Sequences that indicate the chronological order in which instructions of concurrent transactions are executed.A schedule for a set of transactions must consist of all instructions of those transactions.Must preserve the order in which the instructions appear in each individual transaction.
13 Example: Serial Schedule Let T1 transfer $50 from A to B, and transfer 10% of the balance from A to B.In a serial schedule, one transaction just entirely follows the other.E.g. T2 follows T1.
14 Example: Concurrent Schedule Let T1 and T2 be the transactions defined previously.This schedule is not a serial schedule, but it is equivalent to the previous schedule.In both this and the sequential schedule, the sum A + B is preserved.
15 BAD Concurrency Gone Bad This concurrent schedule does not preserve the value of A + B.BAD
17 Concurrency & Serializability Goal – to develop concurrency control protocols that will ensure serializability.These protocols impose a discipline that avoids nonseralizable schedules.A common concurrency control protocol uses locks.While one transaction is accessing a data item, no other transaction can modify it.Require a transaction to lock the item before accessing it.Not as easy as it sounds…Topic of Lecture 15!
18 RecoverabilityHow do we address failures when we are running concurrent transactions?Recoverable schedule: if a transaction Tj reads a data item previously written by a transaction Ti , the commit operation of Ti appears before the commit operation of TjA Database must ensure that schedules are recoverable!
19 Recovery is the point of serializability. Basic Assumption: Each transaction, on its own, preserves database consistency.That is, serial execution of transactions preserves database consistency.A (possibly concurrent) schedule is serializable if it is equivalent to a serial schedule.Different forms of equivalence lead to different kinds of serializability: conflict and view.Recovery is the point of serializability.Serialization makes recovery easier, but can slow down throughput.
20 Conflict Serializability Instructions li and lj of transactions Ti and Tj respectively, conflict iff there exists some item Q accessed by both li and lj, and at least one of these instructions wrote Q.1. li = read(Q), lj = read(Q). li and lj don’t conflict. 2. li = read(Q), lj = write(Q). They conflict. 3. li = write(Q), lj = read(Q). They conflict 4. li = write(Q), lj = write(Q). They conflictA conflict between li and lj forces a (logical) temporal order between them.If li and lj are consecutive in a schedule and they do not conflict, their results would remain the same even if their order were reversed.Bottom Line: an order is forced on two transactions iff they both access the same data and at least one changes it.
21 Conflict Serializability (2) If a schedule S can be transformed into a schedule S´ by a series of swaps of non-conflicting instructions, we say that S and S´ are conflict equivalent.We say that a schedule S is conflict serializable if it is conflict equivalent to a serial schedule.Example of a schedule that is not conflict serializable:T3 T4read(Q) write(Q) write(Q)
22 Conflict Serializability (3) This concurrent schedule can be transformed into the serial one (where T2 follows T1) by a series of swaps of non-conflicting instructions.Therefore it is conflict serializable.
23 View SerializabilityLet S and S´ be two schedules with the same set of transactions. S and S´ are view equivalent if the following three conditions are met, where Q is a data item and Ti is a transaction:If Ti reads the initial value of Q in schedule S, then Ti in schedule S´ must also read the initial value of Q.If Ti executes read(Q) in schedule S, and that value was produced by transaction Tj (if any), then transaction Ti must in schedule S´ also read the value of Q that was produced by transaction Tj.The transaction (if any) that performs the final write(Q) operation in schedule S (for any data item Q) must perform the final write(Q) operation in schedule S´.View equivalence is a bit cleverer than conflict equiv. about the use of reads and writes
24 View Serializability (2) A schedule S is view serializable if it is view equivalent to a serial schedule.Every conflict serializable schedule is also view serializable.Some schedules are view-serializable but not conflict serializable (see below).Every view serializable schedule that is not conflict serializable has blind writes.
26 Testing for Serializability Consider some schedule of a set of transactions T1, T2, ..., TnPrecedence graph: a directed graph where the vertices are transaction names.We draw an arc from Ti to Tj if the two transactions conflict, and Ti accessed the data item before TjWe may label the arc by the item that was accessed.Example:xy
28 Testing Conflict Serializability A schedule is conflict serializable if and only if its precedence graph is acyclic.Cycle-detection algorithms exist which take order n2 time, where n is the number of vertices in the graph.If precedence graph is acyclic, the serializability order can be obtained by a topological sorting of the graph. This is a linear order consistent with the partial order of the graph.For example, one serializability order for this graph is : T1 T2 T4 T3 T (note there’s another!)Example of an acyclic precedence graph
29 Testing View Serializability The precedence graph test for conflict serializability must be modified to apply to a test for view serializability.The problem of checking if a schedule is view serializable is NP-complete. This means the existence of an efficient algorithm is unlikely.However, practical algorithms that just check some sufficient conditions for view serializability can still be used.
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