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, none of the changes written to the log are actually made to the database Write-ahead logging is also useful in recovering a database from a system failure The log contains all the changes to the database, including information about whether each transaction was committed or rolled back To recover a database, the administrator can restore a previous backup of the database, and then process the transaction log, redoing committed transactions This is called roll forward recovery Some database systems use a write-ahead log, but also make changes to the database before the transaction is formally committed In such a system, recovery from failure can be accomplished by restarting the DBMS and undoing transactions in the log that were not committed This approach is called rollback recovery.

THE HashMap CLASS As the class hierarchy in Figure 8.1 shows, Java defines four implementations of its Map interface: the AbstractMap class, the HashMap class, the TreeMap class, and the WeakHashMap class. EXAMPLE 8.1 A German-English Dictionary

This program uses the HashMap class to build a German-English dictionary:

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TRANSACTION ISOLATION LEVELS When multiple users access a database simultaneously, there is a chance that one person s changes to the database will interfere with another person s work For instance, suppose two people using an on-line flight reservation system both see that the window seat in row 18 is available, and both reserve it, nearly simultaneously Without proper controls, both may believe they have successfully reserved the seat but, in fact, one will be disappointed This is an example of one sort of concurrency problem, and it is called the lost update problem The database literature describes desirable characteristics of transactions using the acronym ACID transactions should be atomic (all or nothing), consistent (all rows affected by the transaction are protected from other changes while the transaction is occurring), isolated (free from the effects of other activity in the database at the same time), and durable (permanent).

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The ideas of consistency and isolation are closely related Besides the lost update problem, there are several other potential problems For instance, dirty reads occur when one transaction reads uncommitted data provided by a second simultaneous transaction, which later rolls back the changes it made Another problem is the nonrepeatable read, which occurs when a transaction has occasion to read the same data twice while accomplishing its work, only to find the data changed when it reads the data a second time This can happen if another transaction makes a change to the data while the first is executing A similar issue is the phantom read If one transaction reads a set of records twice in the course of its work, it may find new records when it reads the database a second time.

public class TestDictionary { public static void main(String[] args) { Map map = new HashMap(); map.put("Tag","day"); map.put("Hut","hat"); map.put("Uhr","clock"); map.put("Rad","wheel"); map.put("Ohr","ear"); map.put("Tor","gate"); System.out.println("map=" + map); System.out.println("map.size()=" + map.size()); System.out.println("map.keySet()=" + map.keySet()); System.out.println("map.values()=" + map.values()); System.out.println("map.get(\"Uhr\")=" + map.get("Uhr")); System.out.println("map.remove(\"Rad\")=" + map.remove("Rad")); System.out.println("map.get(\"Rad\")=" + map.get("Rad")); System.out.println("map=" + map); System.out.println("map.size()=" + map.size()); } }

The output is:

That could happen if a second transaction inserted a new record in the database in the meantime The solutions to all these problems involve locking mechanisms to insure consistency and isolation of users and transactions In the old days, programmers managed their own locks to provide the necessary protection, but today one usually relies on the DBMS to manage the locks To prevent the lost update problem, the DBMS will manage read and write locks to insure lost updates do not occur To address the other possible problems, one simply specifies the level of isolation required, using one of four levels standardized by the 1992 SQL standard The reason the standard provides different levels of protection is that greater protection usually comes at the cost of reduced performance (less concurrency, and therefore fewer transactions per unit time)..

map={Rad=wheel, Uhr=clock, Ohr=ear, Tor=gate, Hut=hat, Tag=day} map.size()=6 map.keySet()=[Rad, Uhr, Ohr, Tor, Hut, Tag] map.values()=[wheel, clock, ear, gate, hat, day] map.get("Uhr")=clock map.remove("Rad")=wheel map.get("Rad")=null map={Uhr=clock, Ohr=ear, Tor=gate, Hut=hat, Tag=day} map.size()=5 The put() method inserts key/value pairs into the table. For example, map.put("Tag","day"); inserts the key/value pair ("Tag","day"), where "Tag" is the key and "day" is the value.

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