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CS 728 Advanced Database Systems Chapter 20 Foundation of Database Transaction Processing

CS 728 Advanced Database Systems Chapter 20 Foundation of Database Transaction Processing. 1 Introduction to Transaction Processing (1). A transaction is a sequence of operations whose execution transforms a database from one consistent state to another consistent state.

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CS 728 Advanced Database Systems Chapter 20 Foundation of Database Transaction Processing

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  1. CS 728Advanced Database SystemsChapter 20 Foundation of Database Transaction Processing

  2. 1 Introduction to Transaction Processing (1) • A transaction is a • sequence of operations whose execution transforms a database from one consistent state to another consistent state. • Transaction boundaries: • Begin and End transaction. • Consistent state: the data currently in the database satisfy all integrity constraints defined for the database. • During transaction execution the database may be inconsistent.

  3. Introduction to Transaction Processing (2) • When the transaction is committed, the database must be consistent. • Two main issues to deal with: • Failures of various kinds, such as hardware failures and system crashes • Concurrent execution of multiple transactions Execution of transaction Consistent Database State Consistent Database State Possible inconsistent state

  4. Introduction to Transaction Processing (3) • Consider a transaction that transfers $200 from account A to account B. read(A) A = A - 200 write(A) read(B) B = B + 200 write(B) System crash

  5. Introduction to Transaction Processing (5) • Basic operations are read and write • read_item(X): Reads a database item named X into a program variable. To simplify our notation, we assume that the program variable is also named X. • write_item(X): Writes the value of program variable X into the database item named X. • Basic unit of data transfer from the disk to the computer main memory is one block.

  6. Introduction to Transaction Processing (6) • read_item(X) command includes the following steps: • Find the address of the disk block that contains item X. • Copy that disk block into a buffer in main memory (if that disk block is not already in some main memory buffer). • Copy item X from the buffer to the program variable named X.

  7. Introduction to Transaction Processing (7) • write_item(X) command includes the following steps: • Find the address of the disk block that contains item X. • Copy that disk block into a buffer in main memory (if that disk block is not already in some main memory buffer). • Copy item X from the program variable named X into its correct location in the buffer. • Store the updated block from the buffer back to disk (either immediately or at some later point in time).

  8. Introduction to Transaction Processing (8) • FIGURE 20.2 Two sample transactions: • (a) Transaction T1 (b) Transaction T2

  9. Why Concurrency Control is needed • Multiple transactions are allowed to run concurrently. • Advantages are: • increased processor and disk utilization, leading to better transaction throughput • one transaction can be using the CPU while another is reading from or writing to the disk • throughput: # of transactions executed in a given amount if time. • reduced average response time for transactions • short transactions need not wait behind long ones. • Concurrency control is needed to achieve isolation i.e., to control the interaction among the concurrent transactions in order to prevent them from destroying the database consistency.

  10. Why Concurrency Control is needed • Problems occur when concurrent transactions execute in an uncontrolled manner: • The Lost Update • The Temporary Update (or Dirty Read) • The Incorrect Summary • Unrepeatable Read: • A transaction T1 may read a given value. If another transaction later updates that value and T1 reads that value again, then T1 will see a different value.

  11. The Lost Update Problem • This occurs when two transactions that access the same database items have their operations interleaved in a way that makes the value of some database item incorrect.

  12. The Temporary Update Problem(Dirty Read) • This occurs when one transaction updates a database item and then the transaction fails for some reason. • The updated item is accessed by another transaction before it is changed back to its original value.

  13. Incorrect Summary Problem • If one transaction is calculating an aggregate summary function on a number of records while other transactions are updating some of these records, the aggregate function may calculate some values before they are updated and others after they are updated.

  14. Incorrect Summary Problem

  15. Transaction and System Concepts (1) • A transaction is an atomic unit of work that is either completed in its entirety or not done at all. • For recovery purposes, the system needs to keep track of when the transaction starts, terminates, and commits or aborts. • A transaction must be in one of the following states: • Active: • the initial state; the transaction stays in this state while it is executing • Partially committed: • after the final statement has been executed. • Failed: • after the discovery that normal execution can no longer proceed.

  16. Transaction and System Concepts (2) • Committed: • after successful completion. • Aborted: • after the transaction has been rolled back and the database restored to its state prior to the start of the transaction. Two options after it has been aborted: • restart the transaction (only if no internal logical error) • kill the transaction

  17. Transaction and System Concepts (3) • Recovery manager keeps track of the following operations: • begin_transaction • This marks the beginning of transaction execution. • read or write: • These specify read or write operations on the database items that are executed as part of a transaction. • end_transaction: • This specifies that read and write transaction operations have ended and marks the end limit of transaction execution. • At this point it may be necessary to check whether the changes introduced by the transaction can be permanently applied to the database or whether the transaction has to be aborted because it violates concurrency control or for some other reason.

  18. Transaction and System Concepts (4) • Recovery manager keeps track of the following operations (cont): • commit_transaction: • This signals a successful end of the transaction so that any changes (updates) executed by the transaction can be safely committed to the database and will not be undone. • rollback (or abort): • This signals that the transaction has ended unsuccessfully, so that any changes or effects that the transaction may have applied to the database must be undone.

  19. Transaction and System Concepts (5) • Recovery techniques use the following operators: • undo: • Similar to rollback except that it applies to a single operation rather than to a whole transaction. • redo: • This specifies that certain transaction operations must be redone to ensure that all the operations of a committed transaction have been applied successfully to the database.

  20. State transition diagram illustrating the states for transaction execution Rollback

  21. Desirable Properties of Transactions (1) The ACID properties of a transaction • Atomicity • a transaction is an atomic processing unit; it is either performed in its entirety or not performed at all. • Consistency • a transaction transforms a database from a consistent state to another consistent state. • Isolation • A transaction should not make its updates visible to other transactions until it is committed; this property, when enforced strictly, solves the temporary update problem. • Durability • committed work must never be lost due to subsequently failure.

  22. ACID Properties • Example: T1 T2 value of X read(X) 200 (initial value) X = X + 100 300 (not saved yet) read(X) 200 X = X - 50 150 (not saved yet) write(X) 300 (saved) write(X) 150 (overwrite 300) • lost $100! Correct value of X should be 250.

  23. Schedules • A scheduleS of n transactions T1, T2, ..., Tn is an ordering of all the operations in these transactions subject to the constraint that: • for each transaction Ti, the operations of Ti in S must appear in the same order as they do in Ti. • Note, however, that operations from other transactions Tj can be interleaved with the operations of Ti in S. • Example: Given • T1 = R1(Q) W1(Q) & T2 = R2(Q) W2(Q) • a schedule: R1(Q) R2(Q) W1(Q) W2(Q) • not a schedule: W1(Q) R1(Q) R2(Q) W2(Q)

  24. Schedules • Sa: r1(X); r2(X); w1(X); r1(Y); w2(X); w1(Y);

  25. Schedules • Sb: r1(X); w1(X); r2(X);w2(X); r1(Y); a1;

  26. Conflict Operations • Instructions (Operations) li and lj of transactions Ti and Tj respectively, conflict if and only if there exists some item Q accessed by both li and lj, and at least one of these instructions wroteQ. 1. li = Read(Q), lj = Read(Q). li and ljdon’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 conflict • Two operations in a schedule are conflict if: • They belong to different transactions, • They access the same item Q, and • At least one them is a Write(Q) operation.

  27. Recoverable Schedule • Recoverable schedule: • One where no committed transaction needs to be rolled back. • A schedule S is recoverable if no transaction T in S commitsuntil all transactions T’ that have written an item that T reads have committed. • T reads from T’ in S if X is first written by T’ and later read by T. • T’ should not have been aborted before T reads X • There should be no transaction Ti that writes X after T’ writes it before T reads it (unless Ti, if any, has aborted before T reads X). • Sa, Sb and Sa’are recoverable: • Sa’: r1(X); r2(X); w1(X); r1(Y); w2(X); c2; w1(Y); c1;

  28. Recoverable Schedule • Consider the following schedules: • Sc: r1(X); w1(X); r2(X);r1(Y); w2(X); c2; a1; • Sd: r1(X); w1(X); r2(X);r1(Y); w2(X); w1(Y); c1; c2; • Se: r1(X); w1(X); r2(X);r1(Y); w2(X); w1(Y); a1; a2; • Sc is not recoverable because: • T2 reads item X from T1, and then T2 commits before T1 commits. • If T1 aborts after c2 operation in Sc, then the value of X that T2 read is no longer valid and T2 must be abortedafter it is committed, leading to a schedule that is not recoverable. • For the schedule to be recoverable c2 operation in Sc must be postponed until after T1 commits, as shown in Sd; • If T1 aborts instead of committing, then T2 should also abort as shown in Se, because the value of X it read is no longer valid.

  29. Cascade-less Schedule • Schedules requiring cascaded rollback: • A schedule in which uncommitted transactions that read an item from a failed transaction must be rolled back. • As shown in schedule Se • Cascadeless Schedule: • One where every transaction reads only the items that are written by committed transactions. • r2(X) in Sd and Se must be postponed until after T1 has committed (or aborted), thus delaying T2 but ensuring no cascading rollback if T1 aborts.

  30. Cascade-less Schedule • Strict Schedules: • A schedule in which a transaction can neither read or write an item X until the last transaction that wrote X has committed. • Consider the following schedule: • Sf: w1(X, 5); w2(X , 8); a1; • Suppose the value of X was originally 9. • If T1 aborts, as in Sf, the recovery system will restore the value of X to 9, even though it has already been changed to 8 by T2, thus leading to incorrect results. • Although Sf is cascade-less, it is not strict • It permits T2 to write X even though T1 that last wrote X had not yet committed (or aborted).

  31. Schedules Classification • In term of: • 1. Recoverability • 2. Avoidance of cascading rollback • 3. Strictness • Condition 2 implies condition 1, and condition 3 implies both 1 and 2. • Thus, • all strict schedules are cascade-less, and • All cascade-less schedules are recoverable

  32. Recoverability • Need to address the effect of transaction failures on concurrently running transactions. • Recoverable schedule • if a transaction Tjreads a data items previouslywritten by a transaction Ti, the commit operation of Ti appears before the commit operation of Tj. • The following schedule (Schedule 11) is not recoverable if T9 commits immediately after the read

  33. Recoverability • If T8should abort, T9 would have read (dirty read) an inconsistent database state. Hence database must ensure that schedules are recoverable.

  34. Recoverability (Cont.) • Cascading rollback • a single transaction failure leads to a series of transaction rollbacks. • Consider the following schedule where none of the transactions has yet committed (so the schedule is recoverable) • If T10 fails, T11 and T12 must also be rolled back.

  35. Recoverability (Cont.) • Can lead to the undoing of a significant amount of work • Cascadelessschedules • cascading rollbacks cannot occur; for each pair of transactions Tiand Tj such that Tj reads a data item previously written by Ti, the commit operation of Ti appears before the read operation of Tj. • Every cascadeless schedule is also recoverable • It is desirable to restrict the schedules to those that are cascadeless

  36. Schedules • A schedule S is serial, • if for every transaction T participating in the schedule, all the operations of T are executed consecutively • if operations from different transactions are not interleaved. • otherwise the schedule is called nonserial. • Serial schedules: • R1(Q) W1(Q) R2(Q) W2(Q) • R2(Q) W2(Q) R1(Q) W1(Q) • Non-serial schedule: • R1(Q) R2(Q) W1(Q) W2(Q)

  37. Example Schedules • The following is a serial schedule (Schedule 1), in which T1 is followed by T2.

  38. Example Schedule (Cont.) • The following schedule (Schedule 3) is not a serial schedule, but it is equivalent to Schedule 1. • In both Schedule 1 & 3, the sum A+B is preserved.

  39. Example Schedules (Cont.) • The following concurrent schedule (Schedule 4) does not preserve the value of the the sum A + B.

  40. Example Schedules • (a) Serial schedule A: T1 followed by T2. • (b) Serial schedules B: T2 followed by T1.

  41. Example Schedule (Cont.) • (c) Two nonserial schedules C and D with interleaving of operations.

  42. Several Observations • Serial schedule guarantees database consistency. • n transactions may form n! different serial schedules. • Different serial schedule may produce different result. • Suppose Q = 20 initially. • R1(Q), Q=Q+10, W1(Q), R2(Q), Q=Q*2, W2(Q) produces Q = 60 • R2(Q), Q=Q*2, W2(Q), R1(Q), Q=Q+10, W1(Q) produces Q = 50 • Allowing only serial schedule may cause poor system performance (i.e., low throughput)

  43. Several Observations • Serial schedule is not a must for guaranteeing transaction consistency. • If X and Y are independent, then the following two schedules always produces the same result: • non-serial schedule: • R1(X) W1(X) R2(X) W2(X) R1(Y) W1(Y) • serial schedule: • R1(X) W1(X) R1(Y) W1(Y) R2(X) W2(X)

  44. Serializability • A schedule S of n transactions is serializable if it is equivalent to some serial schedule of the same n transactions. • Basic Assumption • each transaction preserves database consistency • We ignore operations other than read and write instructions • schedules consist of only read and write instructions

  45. Serializability • One way to ensure correctness of concurrent transactions is to enforce serializability of transactions • that is the interleaved execution of the transactions must be equivalent to some serial execution of those transactions. • The interleaved execution of a set of transactions is considered correct iff it is serializable. • A nonserial but serializable schedule often permits higher degree of concurrency than a serial schedule. • Different forms of schedule equivalence give rise to the notions of: • conflict serializability • view serializability

  46. Serializability • Two schedules that are result equivalent for the initial value of X = 100, but are not result equivalent in general.

  47. Conflict Serializability • If li and lj are consecutive in a schedule and they do not conflict, their results would remain the same even if they had been interchanged in the schedule. • 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. • Two schedules are called conflict equivalent if the order of any two conflicting operations is the same in both schedules • We say that a schedule S is conflict serializable if it is conflict equivalent to a serial schedule

  48. Example • Consider two transactions: • T1 = R1(X) W1(X) R1(Y) W1(Y) • T2 = R2(X) W2(X) • The following two schedules are equivalent: • S1: R1(X) W1(X)R2(X) W2(X) R1(Y) W1(Y) • S2: R1(X) W1(X) R1(Y) W1(Y)R2(X) W2(X)

  49. Conflict Serializability (Cont.) • Example of a schedule that is not conflict serializable: T3T4 read(Q)write(Q)write(Q) • We are unable to swap instructions in the above schedule to obtain either the serial schedules • T3, T4 or T4, T3

  50. Conflict Serializability (Cont.) • Schedule 3 below can be transformed into Schedule 1, a serial schedule where T2 follows T1, by series of swaps of non-conflicting instructions. • Therefore Schedule 3 is conflict serializable.

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