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They believe that they now have all of the records in the data warehouse that were modified since they did the initial pull They may actually have all of the records, but just as likely they may not This technique does work on some other databases ones that employ a locking system whereby reads are blocked by writes and vice versa But in a system where you have non-blocking reads, the logic is flawed To see the flaw in this example, all we need to do is assume that at 9:00 am there was at least one open, uncommitted transaction At 8:59:30 am, it had updated a row in the table we were to copy At 9:00 am, when we started pulling the data, reading the data in this table, we would not see the modifications to that row; we would see the last committed version of it.

Clustered tables: A clustered table is part of a group of tables that shares the same data blocks, because data from the clustered tables are often requested together. Partitioned tables: A partitioned table lets you divide a large amount of data into subtables, called partitions, according to various criteria. Partitioning is especially useful in a data warehouse environment. This section of the chapter will discuss the standard (heap-organized) Oracle tables. I ll discuss the other types of tables in the Special Oracle Tables section, later in the chapter.

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Before you create a new table, it s a good idea to estimate the size of the table you ll need now and the size you expect in the future. Knowing the size of the table allows you to make the right decisions about space allocation. Algorithms are available for figuring out the potential size of tables and indexes they take the row size in bytes and multiply it by the estimated number of rows in the table. Estimation of table size is more an art than a precise science, and you don t need to agonize over coming up with accurate figures. Just use common sense and make sure you are not wildly off the mark. You can simplify table-size estimation by using the OEM Database Control or by using the CREATE_TABLE_COST procedure of the DBMS_SPACE package. The following sections illustrate both approaches to sizing a new table.

If it was locked when we got to it in our query, we would read around the lock If it was committed by the time we got to it, we would still read around it since read consistency permits us to read only data that was committed in the database when our statement began We would not read that new version of the row during the 9:00 am initial pull, but nor would we read the modified row during the 10:00 am refresh The reason The 10:00 am refresh would only pull records modified since 9:00 am that morning but this record was modified at 8:59:30 am We would never pull this changed record In many other databases where reads are blocked by writes and a committed but inconsistent read is implemented, this refresh process would work perfectly.

You can use the OEM Database Control to examine quickly the current SQL response time compared to a normal baseline SQL response time. The Database Control computes the SQL response time percentage by dividing the baseline SQL response time by the current SQL response time, both expressed in microseconds. If the SQL response time percentage exceeds 100 percent, then the instance is processing SQL statements slower than the baseline times. If the percentage is approximately equal to 100 percent, then the current response time and the baseline response time are equal, and your instance is performing normally. The SQL Response Time section is right on the Database Control home page.

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There s no question that the new ADDM tool should be the cornerstone of your performance-tuning efforts. In 17, I showed how you can manually get an ADDM report or use the OEM Database Control to view the ADDM analysis. Use the findings and recommendations of the ADDM advisor to fine-tune database performance. Here s the partial output from an ADDM analysis (invoked by running the addmrpt.sql script located in the $ORACLE_HOME/rdbms/admin directory). Listing 20-18 shows part of an ADDM report.

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