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Each object will have at least one FREELIST associated with it, and as blocks are used, they will be placed on or taken off of the FREELIST as needed. It is important to note that only blocks under the HWM of an object will be found on the FREELIST. The blocks that remain above the HWM will be used only when the FREELISTs are empty, at which point Oracle advances the HWM and adds these blocks to the FREELIST. In this fashion, Oracle postpones increasing the HWM for an object until it has to. An object may have more than one FREELIST. If you anticipate heavy INSERT or UPDATE activity on an object by many concurrent users, then configuring more than one FREELIST can have a major positive impact on performance (at the cost of possible additional storage). Having sufficient FREELISTs for your needs is crucial. FREELISTs can be a huge positive performance influence (or inhibitor) in an environment with many concurrent inserts and updates. An extremely simple test can show the benefits of setting FREELISTS correctly. Consider this relatively simple table: ops$tkyte%ORA11GR2> create table t ( x int, y char(50) ) tablespace mssm; Table created.

When Oracle suspends a resumable session, it automatically issues an operation-suspended alert through the automatic Server Generated Alerts feature. Once you fix the problem by allocating the necessary resources and the operation completes, Oracle will automatically clear this alert.

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Given that we have an 8KB blocksize, Oracle will fit up to seven cluster keys (but maybe fewer if the data is larger than expected) per database block This is, the data for departments 10, 20, 30, 40, 50, 60, and 70 would tend to go onto one block, and as soon as we insert department 80, a new block will be used That does not mean that the data is stored in a sorted manner; it just means that if we inserted the departments in that order, they would naturally tend to be put together If we inserted the departments in the order 10, 80, 20, 30, 40, 50, 60, and then 70, the final department, 70, would tend to be on the newly added block.

You can monitor resumable operations by using the DBA_RESUMABLE view. This view provides the name of the operation, the user s SID, the start time of the statement, the error message encountered, the suspend and resume times, and the text and current status of the SQL statements. The V$SESSION_WAIT view also provides information about suspended resumable statements. The EVENT column of this view shows you that a statement is suspended, pending the clearance of a wait error. The DBMS_RESUMABLE package contains procedures to help you manage suspended sessions. The SET_SESSION_TIMEOUT procedure, for example, allows you to specify the time a suspended session will wait before failing.

Note mssm in the above example is the name of a tablespace, not a keyword. You may replace it with the name

Suppose you re running transactions in your database that are extremely long maybe even as long as a whole day. Oracle primarily uses locks to ensure concurrency and atomicity, but locks on a longrunning transaction can reduce concurrency dramatically because other users are forced to wait for the long-running transaction to complete. Fortunately, Oracle provides the Workspace Manager, a feature you can use to version-enable tables, so different users can maintain different versions of the data. During long-running transactions, changes can be made to the same table in different workspaces, and these versions are finally reconciled and the results are stored permanently in the original table. You can think of a workspace as a virtual environment shared by several users making changes to the same data. In addition to facilitating long transactions, the Workspace Manager enables you to create multiple data scenarios for what-if analyses. It can also help you track the history of all the changes to a set of tables. The feature is especially useful in collaborative projects because it allows teams to share content. The Workspace Manager enables simultaneous read and write access to production data during long transactions. It uses multiple versioning of tables to enable the simultaneous reading and writing of data. Consistency is guaranteed because the final, permanent version of the table will not

As we ll see shortly, both the size of the data and the order in which the data is inserted will affect the number of keys we can store per block The SIZE parameter therefore controls the maximum number of cluster keys per block It is the single largest influence on the space utilization of our cluster Set the size too high, and we ll get very few keys per block and we ll use more space than we need Set the size too low, and we ll get excessive chaining of data, which offsets the purpose of the cluster to store all of the data together on a single block It is the most important parameter for a cluster Now for the cluster index on our cluster We need to index the cluster before we can put data in it.

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