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数据库管理系统 Database Management Systems

数据库管理系统 Database Management Systems. Chapter 7 Database Integrity and Transactions 第七章 数据库完整性和事务. Create code (1) Within the query system (2) In forms and reports (3) Hosted in external programs. Programming Environment. DBMS. Tables. Queries. (1). If ( . . ) Then SELECT . . .

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数据库管理系统 Database Management Systems

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  1. 数据库管理系统Database Management Systems Chapter 7 Database Integrity and Transactions 第七章 数据库完整性和事务

  2. Create code (1) Within the query system (2) In forms and reports (3) Hosted in external programs Programming Environment DBMS Tables Queries (1) If ( . . ) Then SELECT . . . Else . . . UPDATE . . . End If External Program Forms & Reports (3) C++ if (. . .) { // embed SQL SELECT … } (2) If (Click) Then MsgBox . . . End If

  3. User-Defined Function CREATE FUNCTION EstimateCosts (ListPrice Currency, ItemCategory VarChar) RETURNS Currency BEGIN IF (ItemCategory = ‘Clothing’) THEN RETURN ListPrice * 0.5 ELSE RETURN ListPrice * 0.75 END IF END

  4. Function to Perform Conditional Update CREATE FUNCTION IncreaseSalary (EmpID INTEGER, Amt CURRENCY) RETURNS CURRENCY BEGIN IF (Amt > 50000) THEN RETURN -1 -- error flag END UPDATE Employee SET Salary = Salary + Amt WHERE EmployeeID = EmpID; RETURN Amt END

  5. Looking Up Data CREATE FUNCTION IncreaseSalary (EmpID INTEGER, Amt CURRENCY) RETURNS CURRENCY DECLARE CURRENCY MaxAmount; BEGIN SELECT MaxRaise INTO MaxAmount FROM CompanyLimits WHERE LimitName = ‘Raise’; IF (Amt > 50000) THEN RETURN -1 -- error flag END UPDATE Employee SET Salary = Salary + Amt WHERE EmployeeID = EmpID; RETURN Amt; END

  6. Data Trigger Events INSERT DELETE UPDATE • Oracle additions: • Tables ALTER, CREATE, DROP • User LOGOFF, LOGON • Database SERVERERROR, SHUTDOWN, STARTUP BEFORE AFTER

  7. Statement v. Row Triggers UPDATE Employee SET Salary = Salary + 10000 WHERE EmployeeID=442 OR EmployeeID=558 SQL After Update On table Before Update On table Triggers for overall table Update Row 442 After Update Row 442 … other rows time Before Update Row 442 Triggers for each row

  8. Data Trigger Example CREATE TRIGGER LogSalaryChanges AFTER UPDATE OF Salary ON Employee REFERENCING OLD ROW as oldrow NEW ROW AS newrow FOR EACH ROW INSERT INTO SalaryChanges (EmpID, ChangeDate, User, OldValue, NewValue) VALUES (newrow.EmployeeID, CURRENT_TIMESTAMP, CURRENT_USER, oldrow.Salary, newrow.Salary);

  9. Canceling Data Changes in Triggers CREATE TRIGGER TestDeletePresident BEFORE DELETE ON Employee REFERENCING OLD ROW AS oldrow FOR EACH ROW WHEN (oldrow.Title = ‘President’) SIGNAL _CANNOT_DELETE_PRES;

  10. Cascading Triggers Sale(SaleID, SaleDate, …) SaleItem(SaleID, ItemID, Quantity, …) AFTER INSERT UPDATE Inventory SET QOH = QOH – newrow.Quantity Inventory(ItemID, QOH, …) AFTER UPDATE WHEN newrow.QOH < newrow.Reorder INSERT {new order} INSERT {new OrderItem} Order(OrderID, OrderDate, …) OrderItem(OrderID, ItemID, Quantity, …)

  11. Trigger Loop Employee(EID, Salary) AFTER UPDATE IF newrow.Salary > 100000 THEN Add Bonus END BonusPaid(EID, BonusDate, Amount) AFTER UPDATE Or INSERT IF newrow.Bonus > 50000 THEN Reduce Bonus Add Options END StockOptions(EID, OptionDate, Amount, SalaryAdj) AFTER UPDATE Or INSERT IF newrow.Amount > 100000 THEN Reduce Salary END

  12. Some transactions result in multiple changes. These changes must all be completed successfully, or the group must fail. Protection for hardware and communication failures. example: bank customer transfers money from savings account to checking account. Decrease savings balance Increase checking balance Problem if one transaction and machine crashes. Possibly: give users a chance to reverse/undo a transaction. Performance gain by executing transactions as a block. Transactions Savings Accounts Inez: 5340.92 4340.92 $1000 Checking Accounts Inez: 1424.27 Transaction 1. Subtract $1000 from savings. (machine crashes) 2. Add $1000 to Checking. (money disappears)

  13. The computer needs to be told which changes must be grouped into a transaction. Turn on transaction processing. Signify a transaction start. Signify the end. Success: save all changes Failure: cancel all changes Must be set in module code Commit Rollback Defining Transactions

  14. SQL Transaction Code CREATE FUNCTION TransferMoney(Amount Currency, AccountFrom Number, AccountTo Number) RETURNS NUMBER curBalance Currency; BEGIN DECLARE HANDLER FOR SQLEXCEPTION BEGIN ROLLBACK; Return -2; -- flag for completion error END; START TRANSACTION; -- optional SELECT CurrentBalance INTO curBalance FROM Accounts WHERE (AccountID = AccountFrom); IF (curBalance < Amount) THEN RETURN -1; -- flag for insufficient funds END IF UPDATE Accounts SET CurrentBalance = CurrentBalance – Amount WHERE AccountID = AccountFrom; UPDATE Accounts SET CurrentBalance = CurrentBalance + Amount WHERE AccountID = AccountTo; COMMIT; RETURN 0; -- flag for success END;

  15. SAVEPOINT SAVEPOINT StartOptional start commit Required elements Risky steps time Partial rollback START TRANSACTION; SELECT … UPDATE … SAVEPOINT StartOptional; UPDATE … UPDATE … If error THEN ROLLBACK TO SAVEPOINT StartOptional; END IF COMMIT;

  16. Concurrent Access Multiple users or processes changing the same data at the same time. Final data will be wrong! Force sequential Locking Delayed, batch updates Two processes Receive payment ($200) Place new order ($150) Initial balance $800 Result should be $800 -200 + 150 = $750 Interference result is either $600 or $950 Concurrent Access Customers Receive Payment Place New Order ID Balance Jones $800 $600 $950 1) Read balance 800 2) Subtract pmt -200 4) Save new bal. 600 3) Read balance 800 5) Add order 150 6) Write balance 950

  17. Pessimistic Locks: Serialization • One answer to concurrent access is to prevent it. • When a transaction needs to alter data, it places a SERIALIZABLE lock on the data used, so no other transactions can even read the data until the first transaction is completed. SET TRANSACTION SERIALIZABLE, READ WRITE Customers Receive Payment Place New Order ID Balance Jones $800 $600 1) Read balance 800 2) Subtract pmt -200 4) Save new bal. 600 3) Read balance Receive error message that it is locked.

  18. SQL Pessimistic Lock CREATE FUNCTION ReceivePayment ( AccountID NUMBER, Amount Currency) RETURNS NUMBER BEGIN DECLARE HANDLER FOR SQLEXCEPTION BEGIN ROLLBACK; RETURN -2; END SET TRANSACTION SERIALIZABLE, READ WRITE; UPDATE Accounts SET AccountBalance = AccountBalance - Amount WHERE AccountNumber = AccountID; COMMIT; RETURN 0; END

  19. Deadlock Two (or more) processes have placed locks on data and are waiting for the other’s data. Many solutions Random wait time Global lock manager Two-phase commit - messages Deadlock 1) Lock Data A 3) Wait for Data B Data A Data B 2) Lock Data B 4) Wait for Data A

  20. Lock Manager

  21. Optimistic Locks • Assume that collisions are rare • Improved performance, fewer resources • Allow all code to read any data (no locks) • When code tries to write a new value • Check to see if the existing value is different from the one you were given earlier • If it is different, someone changed the database before you finished, so it is a collision--raise an error • Reread the value and try again

  22. Optimistic Locks for Simple Update (1) Read the balance (2) Add the new order value (3) Write the new balance (4) Check for errors (5) If there are errors, go back to step (1).

  23. Optimistic Locks with SQL CREATE FUNCTION ReceivePayment ( AccountID NUMBER, Amount Currency) RETURNS NUMBER oldAmount Currency; testEnd Boolean = FALSE; BEGIN DO UNTIL testEnd = TRUE BEGIN SELECT Amount INTO oldAmount WHERE AccountNumber = AccountID; … UPDATE Accounts SET AccountBalance = AccountBalance - Amount WHERE AccountNumber = AccountID AND Amount = oldAmount; COMMIT; IF SQLCODE = 0 and nrows > 0 THEN testEnd = TRUE; RETURN 0; END IF -- keep a counter to avoid infinite loops END END

  24. ACID Transactions • Atomicity: all changes succeed or fail together. • Consistency: all data remain internally consistent (when committed) and can be validated by application checks. • Isolation: The system gives each transaction the perception that it is running in isolation. There are no concurrent access issues. • Durability: When a transaction is committed, all changes are permanently saved even if there is a hardware or system failure.

  25. SQL 99/200x Isolation Levels • READ UNCOMMITTED • Problem: might read dirty data that is rolled back • Restriction: not allowed to save any data • READ COMMITTED • Problem: Second transaction might change or delete data • Restriction: Need optimistic concurrency handling • REPEATABLE READ • Problem: Phantom rows • SERIALIZABLE • Provides same level of control as if all transactions were run sequentially. • But, still might encounter locks and deadlocks

  26. Phantom Rows SELECT SUM(QOH) FROM Inventory WHERE Price BETWEEN 10 and 20 Included in first query UPDATE Inventory SET Price = Price/2 WHERE … Additional rows will be included in the second query SELECT SUM(QOH) FROM Inventory WHERE Price BETWEEN 10 and 20

  27. Generated Keys Customer Table CustomerID, Name, … Create an order for a new customer: (1) Create new key for CustomerID (2) INSERT row into Customer (3) Create key for new OrderID (4) INSERT row into Order Order Table OrderID, CustomerID, …

  28. Methods to Generate Keys • The DBMS generates key values automatically whenever a row is inserted into a table. • Drawback: it is tricky to get the generated value to use it in a second table. • A separate key generator is called by a programmer to create a new key for a specified table. • Drawback: programmers have to write code to generate a key for every table and each row insertion. • Overall drawbacks: neither method is likely to be transportable. If you change the DBMS, you will have to rewrite the procedures to generate keys.

  29. Auto-Generated Keys • Create an order for a new customer: • INSERT row into Customer • Get the key value that was generated • Verify the key value is correct. How? • INSERT row into Order Major problem: Step 2 requires that the DBMS return the key value that was most recently generated. How do you know it is the right value? What happens if two transactions generate keys at almost the same time on the same table?

  30. Key-Generation Routine • Create an order for a new customer: • Generate a key for CustomerID • INSERT row into Customer • Generate a key for OrderID • INSERT row into Order This method ensures that unique keys are generated, and that you can use the keys in multiple tables because you know the value. But, none of it is automatic. It always requires procedures and sometimes data triggers.

  31. Purpose Track through table or query one row at a time. Data cursor is a pointer to active row. Why? Performance. SQL cannot do everything. Complex calculations. Compare multiple rows. Database Cursors Year Sales 1998 104,321 1999 145,998 2000 276,004 2001 362,736 1998 104,321 1999 145,998 2000 276,004 2001 362,736

  32. Database Cursor Program Structure DECLARE cursor1 CURSOR FOR SELECT AccountBalance FROM Customer; sumAccount, balance Currency; SQLSTATE Char(5); BEGIN sumAccount = 0; OPEN cursor1; WHILE (SQLSTATE = ‘00000’) BEGIN FETCH cursor1 INTO balance; IF (SQLSTATE = ‘00000’) THEN sumAccount = sumAccount + balance; END IF END CLOSE cursor1; -- display the sumAccount or do a calculation END

  33. Cursor Positioning with FETCH DECLARE cursor2 SCROLL CURSOR FOR SELECT … OPEN cursor2; FETCH LAST FROM cursor2 INTO … Loop… FETCH PRIOR FROM cursor2 INTO … End loop CLOSE cursor2; FETCH positioning options: FETCH NEXT next row FETCH PRIOR prior row FETCH FIRST first row FETCH LAST last row FETCH ABSOLUTE 5 fifth row FETCH RELATIVE -3 back 3 rows

  34. Problems with Multiple Users Original Data Modified Data Name Sales Alice 444,321 Carl 254,998 Donna 652,004 Ed 411,736 Name Sales Alice 444,321 Bob 333,229 Carl 254,998 Donna 652,004 Ed 411,736 New row is added--while code is running. The SQL standard can prevent this problem with the INSENSITIVE option: DECLARE cursor3 INSENSITIVE CURSOR FOR … But, this is an expensive approach, because the DBMS usually makes a copy of the data. Instead, avoid moving backwards.

  35. Changing Data with Cursors DECLARE cursor1 CURSOR FOR SELECT Year, Sales, Gain FROM SalesTotal ORDER BY Year FOR UPDATE OF Gain; priorSales, curYear, curSales, curGain BEGIN priorSales = 0; OPEN cursor1; Loop: FETCH cursor1 INTO curYear, curSales, curGain UPDATE SalesTotal SET Gain = Sales – priorSales WHERE CURRENT OF cursor1; priorSales = curSales; Until end of rows CLOSE cursor1; COMMIT; END

  36. Dynamic Parameterized Cursor Queries DECLARE cursor2 CURSOR FOR SELECT ItemID, Description, Price FROM Inventory WHERE Price < :maxPrice; maxPrice Currency; BEGIN maxPrice = … -- from user or other query OPEN cursor2; -- runs query with current value Loop: -- Do something with the rows retrieved Until end of rows CLOSE cursor2; END Parameters enable you to control the rows retrieved dynamically from within the procedure code. The value is applied when the cursor is opened.

  37. Sally’s Pet Store Inventory • Inventory method 1: calculate the current quantity on hand by totaling all purchases and sales every time the total is needed. • Drawback: performance • Inventory method 2: keep a running balance in the inventory table and update it when an item is purchased or sold. • Drawback: tricky code • Also, you need an adjustment process for “inventory shrink”

  38. Inventory QuantityOnHand Merchandise ItemID Description QuantityOnHand ListPrice Category Add items purchased Subtract items sold Adjust for shrink SaleItem SaleID ItemID Quantity SalePrice

  39. For a new sale, a row is added to the SaleItem table. A sale or an item could be removed because of a clerical error or the customer changes his or her mind. A SaleItem row will be deleted. An item could be returned, or the quantity could be adjusted because of a counting error. The Quantity is updated in the SaleItem table. An item is entered incorrectly. ItemID is updated in the SaleItem table. Inventory Events SaleItem SaleID ItemID Quantity SalePrice • Add a row. • Delete a row. • Update Quantity. • Update ItemID.

  40. New Sale: Insert SaleItem Row CREATE TRIGGER NewSaleItem AFTER INSERT ON SaleItem REFERENCING NEW ROW AS newrow FOR EACH ROW UPDATE Merchandise SET QuantityOnHand = QuantityOnHand – newrow.Quantity WHERE ItemID = newrow.ItemID;

  41. Delete SaleItem Row CREATE TRIGGER DeleteSaleItem AFTER DELETE ON SaleItem REFERENCING OLD ROW AS oldrow FOR EACH ROW UPDATE Merchandise SET QuantityOnHand = QuantityOnHand + oldrow.Quantity WHERE ItemID = oldrow.ItemID;

  42. Quantity Changed Event CREATE TRIGGER UpdateSaleItem AFTER UPDATE ON SaleItem REFERENCING OLD ROW AS oldrow NEW ROW AS newrow FOR EACH ROW UPDATE Merchandise SET QuantityOnHand = QuantityOnHand + oldrow.Quantity – newrow.Quantity WHERE ItemID = oldrow.ItemID;

  43. ItemID or Quantity Changed Event CREATE TRIGGER UpdateSaleItem AFTER UPDATE ON SaleItem REFERENCING OLD ROW AS oldrow NEW ROW AS newrow FOR EACH ROW BEGIN UPDATE Merchandise SET QuantityOnHand = QuantityOnHand + oldRow.Quantity WHERE ItemID = oldrow.ItemID; UPDATE Merchandise SET QuantityOnHand = QuantityOnHand – newRow.Quantity WHERE ItemID = newrow.ItemID; COMMIT; END

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