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For strongly named assemblies, there are more deployment options These will be discussed in the next section When the runtime searches an assembly, the version number is only relevant for assemblies with a strong name If the runtime searches a weakly named assembly that is referenced by your project, any available version will be loaded, no matter what version you built your code against..

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The AWR was designed by Oracle as a replacement for the traditional Statspack utility, which helps you gather database performance statistics (the Statspack utility is still available, but Oracle strongly recommends using the AWR instead) The AWR generates snapshots of key performance data, such as system and session statistics, segment-usage statistics, time-model statistics, and high-load-SQL statistics, and it stores the snapshots in the Sysaux tablespace By default, the database will generate a performance snapshot every hour You can customize the snapshot interval, the types of statistics the AWR collects, and the length of time the snapshots are retained in the AWR AWR provides performance statistics in two formats: A temporary in-memory collection of statistics in the SGA, accessible through dynamic performance (V$) views or the OEM interface.

A persistent type of performance data in the form of regular AWR snapshots, which you access either through data dictionary (DBA_*) views or the OEM Database Control The persistent data in the AWR snapshots helps in historical comparisons of performance MMON is a new Oracle Database 10g background process that performs mostly managementrelated tasks, including issuing database alerts and capturing statistics for recently modified database objects The MMON process transfers the memory version of AWR statistics to disk on a regular basis (in the form of snapshots) Oracle DBAs traditionally have needed to maintain special database tables to collect historical performance data The AWR automatically collects performance statistics for you and maintains.

if [ -f $userhome/.xdisp.$user ] then cat $userhome/.xauth.$user | /usr/openwin/bin/xauth nmerge DISPLAY=`cat $userhome/.xdisp.$user` export DISPLAY else echo "SSH Display information not available for $user. Is $user using it " exit 1 fi

historical data for analysis. You can view the data in the snapshots with the help of the V$ views or create reports to examine the data in detail. Various database components and features use the data from these AWR snapshots to monitor and diagnose performance issues. For example, as you saw in 17, the ADDM relies on these snapshots for the diagnosis of performance problems. In addition, the SQL Tuning Advisor, the Undo Advisor, and the Segment Advisor all use AWR data.

The AWR facility collects a large number of performance statistics, including the following: Base statistics that are also part of the V$SYSSTAT and V$SESSSTAT views SQL statistics that aid in the identification of resource-intensive SQL statements Database object-usage statistics that inform you about how the database is currently accessing various objects Time-model statistics, which tell you how much time each database activity is taking Wait statistics, which provide information about session waits (in previous versions, you needed to join the V$SESSION view with the V$SESSION_WAIT view to gather information on session waits; now several new columns have been added to the V$SESSION view, so you can query the view directly) Active Session History (ASH) statistics, which are flushed to the AWR on a regular basis Database feature-usage statistics that tell you whether and how intensively your database is utilizing various features The results of various management advisory sessions, such as the Segment Advisor and the SQL Access Advisor Operating system statistics such as disk I/O and memory usage within the database As explained in 17, the ADDM will automatically run after each AWR snapshot, analyzing the time period between the last two snapshots. By comparing the difference in statistics between snapshots, for example, the ADDM knows which SQL statements are contributing significantly to your system load. It then focuses on these SQL statements.