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Using five concurrent sessions, we start inserting into this table like wild If we measure the systemwide wait events for block-related waits both before and after inserting, we will find large waits, especially on data blocks (trying to insert data) This is frequently caused by insufficient FREELISTs on tables (and on indexes, but we ll cover that in detail in the next chapter Indexes ) I used Statspack for this I took a statspacksnap, executed a script that started the five concurrent SQL*Plus sessions, and waited for them to exit, before taking another statspacksnap The script these sessions ran was simply: begin for i in 1 . 100000 loop insert into t values ( i, 'x' ); end loop; commit; end; / exit; Now, this is a very simple block of code, and I m the only user in the database here I should get the best possible performance.

have any conflicts within the data. All the users see is their own virtual version of the database that is, different versions of the rows in the same tables. But the versions each user sees from his or her workspace are guaranteed to be transactionally consistent; the user s versions will have the original data the user started with, plus all the changes he or she made to the original data.

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Among other things, the Workspace Manager enables you to try out various scenarios with your data (such as the effects of different marketing campaigns) before you finally settle on one acceptable version that you can make permanent by merging all the virtual versions of the table data. Merging, in effect, incorporates the child workspace data with the original (parent workspace) data. If, after analysis, you decide to nullify all the child workspace s data, you can do so by rolling it back, just like you would roll back a transaction under normal circumstances.

I have plenty of buffer cache configured, my redo logs are sized appropriately, indexes won t be slowing things down, I m running on a machine with two hyperthreaded Xeon CPUs this should run fast What I discovered afterward, however, is the following: Snapshot Snap Id Snap Time Sessions Curs/Sess Comment ~~~~~~~~ ---------- ------------------ -------- --------- -----------------Begin Snap: 364 17-Mar-10 11:58:24 26 17 End Snap: 365 17-Mar-10 11:59:01 24 18 Elapsed: 062 (mins) Av Act Sess: 49 DB time: 304 (mins) DB CPU: 118 (mins) Top 5 Timed Events Avg %Total ~~~~~~~~~~~~~~~~~~ wait Call Event Waits Time (s) (ms) Time ----------------------------------------- ------------ ----------- ------ -----buffer busy waits 199,708 107 1 535 CPU time 70 350 db file async I/O submit 44 11 252 55 log file parallel write 1,130 9 8 45 control file parallel write 56 1 16 .

We could create tables in the cluster right now, but we re going to create and populate the tables simultaneously, and we need a cluster index before we can have any data The cluster index s job is to take a cluster key value and return the block address of the block that contains that key It is a primary key in effect, where each cluster key value points to a single block in the cluster itself So, when we ask for the data in department 10, Oracle will read the cluster key, determine the block address for that, and then read the data The cluster key index is created as follows: ops$tkyte@ORA10GR1> create index emp_dept_cluster_idx 2 on cluster emp_dept_cluster 3 / Index created It can have all of the normal storage parameters of an index and can be stored in another tablespace.

Although the Workspace Manager provides you with the capability to create multiple versions of one table, or even of all the tables in your database, it doesn t impose a severe storage cost because only the changed rows in each workspace are versioned, and these new versions are saved in the original table (and in the original tablespace). In other words, you don t need to make any special storage allocations for the database tables that belong to different versions.

The Workspace Manager offers the following features: You can maintain multiple versions of data, which you can keep or discard as necessary. Multiple users can simultaneously access and modify the same data. The updates made by several users over time are isolated in workspaces until they re merged into the production database. Conflicts between multiple versions are resolved automatically by the Workspace Manager.

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