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Constraints and triggers: maintaining the ACID properties of transactions

Constraints and triggers: maintaining the ACID properties of transactions. CSCI 2141 W2013 Slides from: www.cs.sjsu.edu/~lee/cs157b/Transactions.ppt www.cs.sunysb.edu/~cse515/Fall07/slides/ch21.ppt http://www.psut.edu.jo/sites/khamis/DB/ppt/ENCh08.ppt

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Constraints and triggers: maintaining the ACID properties of transactions

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  1. Constraints and triggers: maintaining the ACID properties of transactions CSCI 2141 W2013 Slides from: www.cs.sjsu.edu/~lee/cs157b/Transactions.ppt www.cs.sunysb.edu/~cse515/Fall07/slides/ch21.ppt http://www.psut.edu.jo/sites/khamis/DB/ppt/ENCh08.ppt cs.gmu.edu/~aobaidi/fall_05/index_files/.../ENCh09.ppt

  2. Constraints as Assertions • General constraints: constraints that do not fit in the basic SQL categories (presented in chapter 8) • Mechanism: CREAT ASSERTION • components include: a constraint name, followed by CHECK, followed by a condition

  3. Assertions: An Example • “The salary of an employee must not be greater than the salary of the manager of the department that the employee works for’’ CREAT ASSERTION SALARY_CONSTRAINT CHECK (NOT EXISTS (SELECT * FROM EMPLOYEE E, EMPLOYEE M, DEPARTMENT D WHERE E.SALARY > M.SALARY AND E.DNO=D.NUMBER AND D.MGRSSN=M.SSN))

  4. Using General Assertions • Specify a query that violates the condition; include inside a NOT EXISTS clause • Query result must be empty • if the query result is not empty, the assertion has been violated

  5. SQL Triggers • Objective: to monitor a database and take action when a condition occurs • Triggers are expressed in a syntax similar to assertions and include the following: • event (e.g., an update operation) • condition • action (to be taken when the condition is satisfied)

  6. SQL Triggers: An Example • A trigger to compare an employee’s salary to his/her supervisor during insert or update operations: CREATE TRIGGER INFORM_SUPERVISOR BEFORE INSERT OR UPDATE OF SALARY, SUPERVISOR_SSN ON EMPLOYEE FOR EACH ROW WHEN (NEW.SALARY> (SELECT SALARY FROM EMPLOYEE WHERE SSN=NEW.SUPERVISOR_SSN)) INFORM_SUPERVISOR (NEW.SUPERVISOR_SSN,NEW.SSN;

  7. Views in SQL • A view is a “virtual” table that is derived from other tables • Allows for limited update operations (since the table may not physically be stored) • Allows full query operations • A convenience for expressing certain operations

  8. Specification of Views • SQL command: CREATE VIEW • a table (view) name • a possible list of attribute names (for example, when arithmetic operations are specified or when we want the names to be different from the attributes in the base relations) • a query to specify the table contents

  9. SQL Views: An Example • Specify a different WORKS_ON table CREATE TABLE WORKS_ON_NEW AS SELECT FNAME, LNAME, PNAME, HOURS FROM EMPLOYEE, PROJECT, WORKS_ON WHERE SSN=ESSN AND PNO=PNUMBER GROUP BY PNAME;

  10. Using a Virtual Table • We can specify SQL queries on a newly create table (view): SELECT FNAME, LNAME FROM WORKS_ON_NEW WHERE PNAME=‘Seena’; • When no longer needed, a view can be dropped: DROP WORKS_ON_NEW;

  11. Efficient View Implementation • Query modification: present the view query in terms of a query on the underlying base tables • disadvantage: inefficient for views defined via complex queries (especially if additional queries are to be applied to the view within a short time period)

  12. Efficient View Implementation • View materialization: involves physically creating and keeping a temporary table • assumption: other queries on the view will follow • concerns: maintaining correspondence between the base table and the view when the base table is updated • strategy: incremental update

  13. View Update • Update on a single view without aggregate operations: update may map to an update on the underlying base table • Views involving joins: an update may map to an update on the underlying base relations • not always possible

  14. Un-updatable Views • Views defined using groups and aggregate functions are not updateable • Views defined on multiple tables using joins are generally not updateable • WITH CHECK OPTION: must be added to the definition of a view if the view is to be updated • to allow check for updatability and to plan for an execution strategy

  15. REFERENTIAL INTEGRITY OPTIONS • We can specify RESTRICT, CASCADE, SET NULL or SET DEFAULT on referential integrity constraints (foreign keys)CREATE TABLE DEPT ( DNAME VARCHAR(10) NOT NULL, DNUMBER INTEGER NOT NULL, MGRSSN CHAR(9), MGRSTARTDATE CHAR(9), PRIMARY KEY (DNUMBER), UNIQUE (DNAME), FOREIGN KEY (MGRSSN) REFERENCES EMPON DELETE SET DEFAULT ON UPDATE CASCADE );

  16. REFERENTIAL INTEGRITY OPTIONS (continued) CREATE TABLE EMP ( ENAME VARCHAR(30) NOT NULL, ESSN CHAR(9), BDATE DATE, DNO INTEGER DEFAULT 1, SUPERSSN CHAR(9), PRIMARY KEY (ESSN), FOREIGN KEY (DNO) REFERENCES DEPT ON DELETE SET DEFAULT ON UPDATE CASCADE, FOREIGN KEY (SUPERSSN) REFERENCES EMP ON DELETE SET NULL ON UPDATE CASCADE );

  17. Transactions • Many enterprises use databases to store information about their state • e.g., Balances of all depositors at a bank • When an event occurs in the real world that changes the state of the enterprise, a program is executed to change the database state in a corresponding way • e.g., Bank balance must be updated when deposit is made • Such a program is called a transaction

  18. What Does a Transaction Do? • Return information from the database • RequestBalance transaction: Read customer’s balance in database and output it • Update the database to reflect the occurrence of a real world event • Deposit transaction: Update customer’s balance in database • Cause the occurrence of a real world event • Withdraw transaction: Dispense cash (and update customer’s balance in database)

  19. Transactions • The execution of each transaction must maintain the relationship between the database state and the enterprise state • Therefore additional requirements are placed on the execution of transactions beyond those placed on ordinary programs: • Atomicity • Consistency • Isolation • Durability ACID properties

  20. Database Consistency • Enterprise (Business) Rules limit the occurrence of certain real-world events • Student cannot register for a course if the current number of registrants equals the maximum allowed • Correspondingly, allowable database states are restricted cur_reg <= max_reg • These limitations are called (static)integrity constraints:assertions that must be satisfied by all database states (state invariants).

  21. Database Consistency(state invariants) • Other static consistency requirements are related to the fact that the database might store the same information in different ways • cur_reg = |list_of_registered_students| • Such limitations are also expressed as integrity constraints • Database is consistent if all static integrity constraints are satisfied

  22. Transaction Consistency • A consistent database state does not necessarily model the actual state of the enterprise • A deposit transaction that increments the balance by the wrong amountmaintains the integrity constraint balance  0, but does not maintain the relation between the enterprise and database states • A consistent transaction maintainsdatabase consistency and the correspondence between the database state and the enterprise state (implements its specification) • Specification of deposit transaction includes balance = balance + amt_deposit , (balance is the next value of balance)

  23. Dynamic Integrity Constraints(transition invariants) • Some constraints restrict allowable state transitions • A transaction might transform the database from one consistent state to another, but the transition might not be permissible • Example: A letter grade in a course (A, B, C, D, F) cannot be changed to an incomplete (I) • Dynamic constraints cannot be checked by examining the database state

  24. Transaction Consistency • Consistent transaction: if DB is in consistent state initially, when the transaction completes: • All static integrity constraints are satisfied (but constraints might be violated in intermediate states) • Can be checked by examining snapshot of database • New state satisfies specifications of transaction • Cannot be checked from database snapshot • No dynamic constraints have been violated • Cannot be checked from database snapshot

  25. Checking Integrity Constraints • Automatic:Embed constraint in schema. • CHECK, ASSERTION for static constraints • TRIGGER for dynamic constraints • Increases confidence in correctness and decreases maintenance costs • Not always desirable since unnecessary checking (overhead) might result • Deposit transaction modifies balance but cannot violate constraint balance  0 • Manual:Perform check in application code. • Only necessary checks are performed • Scatters references to constraint throughout application • Difficult to maintain as transactions are modified/added

  26. Atomicity • A real-world event either happens or does not happen • Student either registers or does not register • Similarly, the system must ensure that either the corresponding transaction runs to completionor, if not, it has no effect at all • Not true of ordinary programs. A crash could leave files partially updated on recovery

  27. Commit and Abort • If the transaction successfully completes it is said to commit • The system is responsible for ensuring that all changes to the database have been saved • If the transaction does not successfully complete, it is said to abort • The system is responsible for undoing, or rolling back, all changes the transaction has made

  28. Reasons for Abort • System crash • Transaction aborted by system • Execution cannot be made atomic (a site is down) • Execution did not maintain database consistency (integrity constraint is violated) • Execution was not isolated • Resources not available (deadlock) • Transaction requests to roll back

  29. API for Transactions • DBMS and TP monitor provide commands for setting transaction boundaries. Example: • begin transaction • commit • rollback • The commit command is a request • The system might commit the transaction, or it might abort it for one of the reasons on the previous slide • The rollback command is always satisfied

  30. Durability • The system must ensure that once a transaction commits, its effect on the database state is not lost in spite of subsequent failures • Not true of ordinary programs. A media failure after a program successfully terminates could cause the file system to be restored to a state that preceded the program’s execution

  31. Implementing Durability • Database stored redundantly on mass storage devices to protect against media failure • Architecture of mass storage devices affects type of media failures that can be tolerated • Related to Availability: extent to which a (possibly distributed) system can provide service despite failure • Non-stop DBMS (mirrored disks) • Recovery based DBMS (log)

  32. Isolation • Serial Execution: transactions execute in sequence • Each one starts after the previous one completes. • Execution of one transaction is not affected by the operations of another since they do not overlap in time • The execution of each transaction is isolated from all others. • If the initial database state and all transactions are consistent, then the final database state will be consistent and will accurately reflect the real-world state, but • Serial execution is inadequate from a performance perspective

  33. Isolation • Concurrent execution offers performance benefits: • A computer system has multiple resources capable of executing independently (e.g., cpu’s, I/O devices), but • A transaction typically uses only one resource at a time • Hence, only concurrently executing transactions can make effective use of the system • Concurrently executing transactions yield interleaved schedules

  34. Concurrent Execution begin trans .. op1,1 .. op1,2 .. commit sequence of db operations output by T1 T1 op1,1 op1.2 local computation DBMS op1,1 op2,1 op2.2 op1.2 T2 op2,1 op2.2 interleaved sequence of db operations input to DBMS local variables

  35. Isolation • Interleaved execution of a set of consistent transactions offers performance benefits, butmight not be correct • Example: course registration; cur_reg is number of current registrants local computation not seen by DBMS T1: r(cur_reg : 29)…………w(cur_reg : 30) commit T2: r(cur_reg : 29)……………..…w(cur_reg : 30) commit time  Result: Database state no longer corresponds to real-world state, integrity constraint violated cur_reg <> |list_of_registered_students|

  36. Interaction of Atomicity and Isolation T1: r(bal:10) w(bal:1000010) abort T2: r(bal:1000010) w(yes!!!) commit time • T1 deposits $1000000 • T2 grants credit and commits before T1 completes • T1 aborts and rolls balance back to $10 • T1 has had an effect even though it aborted!

  37. Isolation • An interleaved schedule of transactions is isolatedif its effect is the same as if the transactions had executed serially in some order (serializable) • It follows that serializable schedules are always correct (for any application) • Serializable is better than serial from a performance point of view • DBMS uses locking to ensure that concurrent schedules are serializable T1:r(x) w(x) T2:r(y) w(y)

  38. Isolation in the Real World • SQL supports SERIALIZABLE isolation level, which guarantees serializability and hence correctness for all applications • Performance of applications running at SERIALIZABLE is often not adequate • SQL also supports weaker levels of isolation with better performance characteristics • But beware! -- a particular application might not run correctly at a weaker level

  39. Summary • Application programmer is responsible forcreating consistent transactions and choosing appropriate isolation level • The system is responsible forcreating the abstractions of atomicity, durability, and isolation • Greatly simplifies programmer’s task since she does not have to be concerned with failures or concurrency

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