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Transaction Processing: Concurrency and Serializability 10/4/05
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Interleave transactions to improve concurrency; increasing concurrency can increase throughput (performance). Some interleaved transactions will never violate isolation because they act on different data. Some interleaved transactions MAY violate isolation. Interleave transactions to improve concurrency; increasing concurrency can increase throughput (performance). Some interleaved transactions will never violate isolation because they act on different data. Some interleaved transactions MAY violate isolation.
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Concurrency control: An algorithm to (hopefully) permit good interleaving and refuse bad interleaving. NB, Executing a concurrency control algorithm will increase overhead of the transaction manager. This will increase response time, and reduce throughput. Concurrency control: An algorithm to (hopefully) permit good interleaving and refuse bad interleaving. NB, Executing a concurrency control algorithm will increase overhead of the transaction manager. This will increase response time, and reduce throughput.
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Concurrency control Input to the algorithm are the arriving requests for database reads/writes. The input is obtained from the various transactions. Output is a sequence of database read/write requests. The output is provided to the portion of the data manager actually accessing the disk. Input to the algorithm are the arriving requests for database reads/writes. The input is obtained from the various transactions. Output is a sequence of database read/write requests. The output is provided to the portion of the data manager actually accessing the disk.
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A serial schedule has no interleaving between transactions (a transaction completes before another begins). A schedule is correct if it is equivalent to a serial schedule. A serial schedule has no interleaving between transactions (a transaction completes before another begins). A schedule is correct if it is equivalent to a serial schedule.
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Isolation levels By relaxing the isolation requirement, more interleaving is possible -- at a greater risk to data integrity. Isolation levels characterize the amount of isolation imposed. By relaxing the isolation requirement, more interleaving is possible -- at a greater risk to data integrity. Isolation levels characterize the amount of isolation imposed.
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Commuting operations Two operations, p1 and p2, commute if, for all possible initial database states, p1 returns the same value when executed in order or p2 returns the same value when executed in order or The database state produced by both sequences is the same. Note, commutativity is symmetric. NOTE! Two operations on different data items always commute. Note, Two operations on the same data item MAY commute. Two operations, p1 and p2, commute if, for all possible initial database states, p1 returns the same value when executed in order or p2 returns the same value when executed in order or The database state produced by both sequences is the same. Note, commutativity is symmetric. NOTE! Two operations on different data items always commute. Note, Two operations on the same data item MAY commute.
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Conflicting operations Two operations that do not commute are conflicting operations. E.g., S1 : S1’ : If they are run on the same starting state, and end up in different states, then s11 and s12 conflict. Look at the following from the aspect of two different transactions, A read and read on the same item always commute. A read and a write on the same item conflict because (though the final state is the same), value returned depends on order of ops. A write and a write on the same item conflict. Two operations that do not commute are conflicting operations. E.g., S1 : S1’ : If they are run on the same starting state, and end up in different states, then s11 and s12 conflict. Look at the following from the aspect of two different transactions, A read and read on the same item always commute. A read and a write on the same item conflict because (though the final state is the same), value returned depends on order of ops. A write and a write on the same item conflict.
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If S2 can be obtained from S1 by “swapping” commuting operations, then S1 and S2 are equivalent. Equivalence of schedules is transitive! If S2 can be obtained from S1 by “swapping” commuting operations, then S1 and S2 are equivalent. Equivalence of schedules is transitive!
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Example schedules Two interleaved transactions T1 (t11, t12), T2 (t21, t22): S1: s11, s12, s13, s14 Suppose s12 and s13 commute, then S2 : s11, s13, s12, s14 Same start state Same end state Two interleaved transactions T1 (t11, t12), T2 (t21, t22): S1: s11, s12, s13, s14 Suppose s12 and s13 commute, then S2 : s11, s13, s12, s14 Same start state Same end state
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Schedule equivalence (not the same as E&N’s ‘complete schedule’ definition): Two schedules of the same set of ops are equivalent iff conflicting operations are ordered in the same way in both schedules. ==> A schedule S2 can be derived from a schedule S1 by interchanging commuting operations iff conflicting operations are ordered in the same way in both schedules. Schedule equivalence (not the same as E&N’s ‘complete schedule’ definition): Two schedules of the same set of ops are equivalent iff conflicting operations are ordered in the same way in both schedules. ==> A schedule S2 can be derived from a schedule S1 by interchanging commuting operations iff conflicting operations are ordered in the same way in both schedules.
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Restatement of Serializable Schedule A schedule is serializable if it is equivalent to a serial schedule Equivalent construction: Commute commuting operators and use transitivity of equivalence, or Conflicting operations are in the same order in both schedules. A schedule is serializable if it is equivalent to a serial schedule Equivalent construction: Commute commuting operators and use transitivity of equivalence, or Conflicting operations are in the same order in both schedules.
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Try this: is S1 serializable (what commutations?), S2? S3? T1: T2: S1: S2: S3: T1: T2: S1: S2: S3:
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Try this: is S4 serializable? S4:
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More on schedule equivalence The preceding definition of equivalence (by commuting, AKA by maintaining order of conflicting ops) is called conflict equivalence. A different kind of equivalence is view equivalence, two schedules of the same set of ops are view equivalent if both the following are true: Corresponding read ops in each schedule return the same values, Both schedules yield the same final state. The preceding definition of equivalence (by commuting, AKA by maintaining order of conflicting ops) is called conflict equivalence. A different kind of equivalence is view equivalence, two schedules of the same set of ops are view equivalent if both the following are true: Corresponding read ops in each schedule return the same values, Both schedules yield the same final state.
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View equivalence If corresponding read ops in both schedules return the same values, then the transactions perform the same calculations and write the same results! I.e., transactions in both schedules have the same view of the database. Conflict equivalence implies view equivalence View equivalence does not imply conflict equivalence. I.e., Conflict equivalence is the stronger; but it turns out that conflict equivalence is easier to use for concurrency control. If corresponding read ops in both schedules return the same values, then the transactions perform the same calculations and write the same results! I.e., transactions in both schedules have the same view of the database. Conflict equivalence implies view equivalence View equivalence does not imply conflict equivalence. I.e., Conflict equivalence is the stronger; but it turns out that conflict equivalence is easier to use for concurrency control.
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Serialization graphs A schedule, S, is represented as a directed graph. Nodes are (committed) transactions. Edge between Ti and Tj (Ti -> Tj) if: Some op in Ti, pi, conflicts with some op, pj, in Tj, and pi appears before pj in S. A schedule, S, is represented as a directed graph. Nodes are (committed) transactions. Edge between Ti and Tj (Ti -> Tj) if: Some op in Ti, pi, conflicts with some op, pj, in Tj, and pi appears before pj in S.
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Example S1: T2 writes a after T1 reads a. The ops do not commute: r1(a), w2(a) Graph of S1: T1 T2 S1: T2 writes a after T1 reads a. The ops do not commute: r1(a), w2(a) Graph of S1: T1 T2
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A schedule is conflict serializable iff its serialization graph is acyclic. T2T4 T1 T3T5 T6T7 Topological sorts give conflict equivalent serial schedules, e.g.: T1, T3, T5, T2, T6, T7, T4. Others? T2T4 T1 T3T5 T6T7 Topological sorts give conflict equivalent serial schedules, e.g.: T1, T3, T5, T2, T6, T7, T4. Others?
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In class Using concurrent transactions, deposit to a, withdraw from a, make a (non-serial) schedule: Give the serialization graph Is it acyclic? If so, give a conflict equivalent serial schedule. Identify commuting operations. Identify conflicting operations. Using the concurrent deposit, transfer and withdraw transactions (deposit to a, withdraw from b, transfer takes from b and puts in a), make a (non-serial) schedule: Give the serialization graph Is it acyclic? Is there a serial schedule? How many total pairs of operations are there? Identify, at least some, commuting operations. Identify, at least some, conflicting operations. Using concurrent transactions, deposit to a, withdraw from a, make a (non-serial) schedule: Give the serialization graph Is it acyclic? If so, give a conflict equivalent serial schedule. Identify commuting operations. Identify conflicting operations. Using the concurrent deposit, transfer and withdraw transactions (deposit to a, withdraw from b, transfer takes from b and puts in a), make a (non-serial) schedule: Give the serialization graph Is it acyclic? Is there a serial schedule? How many total pairs of operations are there? Identify, at least some, commuting operations. Identify, at least some, conflicting operations.
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A strict concurrency control A transaction is not allowed to read or write data that has been written by another still active transaction. (Recoverability topic later). Conflict avoidance: If operation requests by T1 and T2 do not conflict, they are granted. Requests don’t conflict if either: Requests are to different data items, OR Requests are both reads. A transaction is not allowed to read or write data that has been written by another still active transaction. (Recoverability topic later). Conflict avoidance: If operation requests by T1 and T2 do not conflict, they are granted. Requests don’t conflict if either: Requests are to different data items, OR Requests are both reads.
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In class Make the conflict table for the previous algorithm: (put X for conflicting requests) Granted op: Requested op:readwrite read write Make the conflict table for the previous algorithm: (put X for conflicting requests) Granted op: Requested op:readwrite read write
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But if you make a transaction wait … DEADLOCK (a cycle of k transactions waiting for each other) DEADLOCK (a cycle of k transactions waiting for each other)
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Dealing with deadlock Prevention: maintain a data structure that checks whether deadlock may result. If so, some transaction involved in the deadlock must be aborted. Timeout: if time to execute exceeds a threshold, force an abort. Timestamp:Timestamp start of each transaction. Use timestamp to implement a conflict resolution policy: Older transaction never waits for younger (e.g., by aborting younger, even though younger has been waiting a long time), Younger transaction can only wait for an older (place younger on wait-list) Prevention: maintain a data structure that checks whether deadlock may result. If so, some transaction involved in the deadlock must be aborted. Timeout: if time to execute exceeds a threshold, force an abort. Timestamp:Timestamp start of each transaction. Use timestamp to implement a conflict resolution policy: Older transaction never waits for younger (e.g., by aborting younger, even though younger has been waiting a long time), Younger transaction can only wait for an older (place younger on wait-list)
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Manual locking: an alternative to AUTOMATIC locking A transaction explicitly requests concurrency control to grant a lock on a data item, then makes the read/write request. Concurrency control grants (or refuses) locks. A transaction explicitly requests concurrency control to grant a lock on a data item, then makes the read/write request. Concurrency control grants (or refuses) locks.
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UNLOCKING Can be automatic -- when a transaction terminates, all locks held by it are released. Can be manual -- transaction explicitly releases a lock. Can be automatic -- when a transaction terminates, all locks held by it are released. Can be manual -- transaction explicitly releases a lock.
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Two phase locking: 2PL A transaction maintains 2PL protocol if it obtains all of its locks before making any unlocks … lock phase, followed by unlock phase Automatic locking is 2PL. Automatic unlocking is 2PL. 2PL protocol produces serializable schedules. A transaction maintains 2PL protocol if it obtains all of its locks before making any unlocks … lock phase, followed by unlock phase Automatic locking is 2PL. Automatic unlocking is 2PL. 2PL protocol produces serializable schedules.
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For next time, we’ll discuss the paper in the RedBook: “Granularity of Locks …” How are the different lock modes used? What are the degrees of consistency? How does the locking protocol relate to degrees of consistency. What are the overhead costs of the different locking protocols? For next time, we’ll discuss the paper in the RedBook: “Granularity of Locks …” How are the different lock modes used? What are the degrees of consistency? How does the locking protocol relate to degrees of consistency. What are the overhead costs of the different locking protocols?
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