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The database shrinks one of the two tempfiles all the way down to 1MB and the other only by 1MB, leaving 999MB of space intact in that tempfile. If your goal is to shrink a particular tempfile down to a certain minimum, you can do so by specifying the name of the particular tempfile you want to shrink, as shown here: SQL> ALTER TABLESPACE temp SHRINK SPACE TEMPFILE tempfile '/u01/app/oracle/oradata/prod1/temp02.dbf' KEEP 100m; Tablespace altered. SQL> The ALTER TABLESPACE statement shown here shrinks just the tempfile you list by the amount you specify with the KEEP clause. It leaves the other tempfiles in the TEMP tablespace alone. The KEEP clause in the previous statement ensures that the tempfile I specify retains 500MB of space. The following example shows how to shrink a single tempfile without any specific retained space: SQL> ALTER TABLESPACE temp SHRINK tempfile '/u01/app/oracle/tempfile/temp03.dbf'; Since I didn t specify the KEEP clause in the previous statement, the database shrinks the tempfile I specified to the minimum possible size, which is about 1MB.

It is quite common for classes to be designed in a way that one class produces something that another consumes. Software systems often have many types of producer and consumer classes. Sometimes a class can act as a producer of some type of information, and as a consumer of another type. In the context of coupling, the producer-consumer pattern is important because the producer and consumer algorithms are logically coupled. Before the consumer can consume something, it must know a number of things about the producer, including What will be produced When will it be produced How will the information be packaged and formatted How will the information be accessible All this meta-information induces algorithmic logic coupling between the consumer and producer algorithms. If the producer changes something in the way it produces information, there is a good chance the consumer will have to be changed as well. Two algorithms are complementary if they work together to accomplish a task or operation. For example, one class might use an algorithm to store data in a buffer, while another class might use a complementary algorithm to read the data from the buffer. The overall operation that the writer and reader accomplish together might be anything, such as getting data from one place to another, making information persistent, making information secure, increasing the performance of the system, and so on.

recommendations according to the crucial DB time statistic (more on this in a little bit), you have a way of quantitatively estimating the effectiveness of different measures in improving performance.

Oracle recommends that you rely on the AWR for all the performance data you need for tuning purposes.

By automatically analyzing performance data for you, the ADDM relieves you of the responsibility of catching a problem at the right time to collect statistics. By default, the AWR collects new performance statistics in the form of an hourly snapshot and saves these snapshots for eight days before purging them. An AWR snapshot is a collection of database performance statistics at a single point in time, including statistics for resource-intensive SQL statements. Every time the AWR takes a new snapshot, the ADDM runs automatically, does its top-down system analysis, and reports its findings on the Database Control home page. The ADDM s output consists of a description of each performance problem it identifies, along with the recommended action. The recommendations are ranked by the expected benefit of implementing each of them. You can view the regular ADDM reports from the OEM Database Control or view them from a SQL*Plus session with the help of an Oracle-supplied SQL script. The ADDM runs automatically, but you can also manually invoke the tool to investigate problems that occur in between the scheduled snapshots. Oracle stores the ADDM analyses in the Sysaux tablespace.