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RAID devices provide you with redundancy if a disk in a RAID system fails, you can immediately and automatically reconstruct the data on the failed disk from the data on the rest of the devices RAID systems are ubiquitous, and most Oracle databases employ them for the several performance and redundancy benefits they provide When it comes to the performance of disk systems, two factors are of interest: the transfer rate and the number of I/O operations per second The transfer rate refers to the efficiency with which data can move through the disk system s controller As for I/O operations, the more a disk system can handle in a specified period, the better Compared to traditional disks, which have an MTBF of tens of thousands of hours, disk arrays have an MTBF of millions of hours.

Even when a disk in a RAID system fails, the array itself continues to operate successfully Most modern arrays automatically start using one of the spare disks, called hot spares, to which the data from the failed drive is transferred Most disk arrays also permit the replacement of failed disks without bringing the system itself down (this is known as hot swapping)..

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The inherent trade-off in RAID systems is between performance and reliability. You can employ two fundamental techniques, striping and mirroring the disk arrays, to improve disk performance and enhance reliability. Mirroring schemes involve complete duplication of the data, and while most of the nonmirrored RAID systems also involve redundancy, it is not as high as in the mirrored systems. The redundancy in nonmirrored RAID systems is due to the fact that they store the parity information needed for reconstructing disks in case there is a malfunction in the array. The following sections describe the most commonly used RAID classifications. Except for RAID 0, all the levels offer redundancy in your disk storage system.

public static void main(String args[]) { Util.checkProgramUsage( args ); Connection conn = null; try { conn = JDBCUtil.getConnection("scott", "tiger", args[0]); _demoBindingByParameterIndex( conn ); _demoBindingByParameterName( conn ); } catch (SQLException e) { // handle the exception properly - in this case, we just // print the stack trace. JDBCUtil.printException ( e ); } finally { // release the JDBC resources in the finally clause. JDBCUtil.close( conn ); } } // end of main() In the main() method, after getting the JDBC connection, we invoke two methods: demoBindingByParameterIndex(): Demonstrates binding by parameter index demoBindingByParameterName(): Demonstrates binding by parameter name We then close the connection in the finally clause to end the main() method. The method _demoBindingByParameterIndex() starts by declaring required variables and beginning a try catch block (notice the constants declared for column indexes later): /* demo parameter binding by index */ private static void _demoBindingByParameterIndex( Connection conn ) throws SQLException { String stmtString = "select empno, ename, job from emp where job = and hiredate < "; System.out.println( "\nCase 1: bind parameter by index"); System.out.println( "Statement: " + stmtString ); PreparedStatement pstmt = null; ResultSet rset = null; final int JOB_COLUMN_INDEX = 1; final int HIREDATE_COLUMN_INDEX = 2; final int SELECT_CLAUSE_EMPNO_COLUMN_INDEX = 1; final int SELECT_CLAUSE_ENAME_COLUMN_INDEX = 2; final int SELECT_CLAUSE_JOB_COLUMN_INDEX = 3; try {

Oracle Database 11g includes several management advisors to provide you with automatic performance details about various subsystems of the database. These advisors are specialized tools that help in the performance tuning of various database components, identifying bottlenecks and suggesting optimal sizes for key database resources. For example, the Undo Advisor tells you what the optimal

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