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Databases in general, and data warehouses in particular, need to regularly extract data from various sources and transform it into a more useful form. For example, a data warehouse may collect data from the OLTP data sources and transform it according to some business rules to make it useful for management. Traditionally, the way to load a data warehouse has been to first load staging tables with the raw data. Sometimes the data would be transformed outside of the database and loaded directly in one pass to the warehouse tables. Either method is usually very cumbersome, even when you use state-of-the-art extraction and transformation tools or custom scripts. Oracle allows the use of external tables that is, tables that use data that resides in external operating system files. External tables don t need any storage in terms of extents in the Oracle database the definition of an external table merely makes an entry in the data dictionary, which enables you to load data into other Oracle database tables from the external tables. If you drop an external table in Oracle, you ll only be removing its definition from the data dictionary the data itself remains safe in the external source files. External tables are commonly used as intermediate staging tables during data transformations. External tables enable you to view externally stored data as if it were inside a table in the Oracle database. You can perform queries and joins on external tables, but you can t update, insert, or delete from these tables; no DML operations are permissible on external tables.

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Now we determine if the current child process is the last one in the children array. If it is, print a terminating branch character (\) to the screen. Note that the code specifies two backslash characters in succession when we only need one in the output. This is because the backslash character tells the shell to ignore any special processing of the next character, and thus we need two to get one. If the child process isn t the last one in the children array, print a split branch (|\), which will allow for this child process and its direct descendants on the tree.

Oracle databases can be quite large, and it s not uncommon to encounter tables that hold several gigabytes worth of data. Partitioning is a way of logically dividing a large table into smaller chunks to facilitate query processing, DML operations, and database management. All the partitions share the same logical definition, column definitions, and constraints. Improvements in query response times are startling when you partition a 500-million-row table into a dozen or more partitions. Partitioning leads directly to better query performance because the database needs to search only the relevant partitions of the table during a query. This avoidance of unneeded partitions when querying is called partition pruning; the availability of one partition is independent of the availability of the other partitions. Data I/O can also be enhanced by using partitions because you can keep the partitions of a heavily accessed table on different disk drives. If you are using the Oracle parallel DML features, partitioned tables provide you with better performance.

The double-thunking problem described in the context of native function pointers can also occur when managed virtual functions are called from managed code. Figure 9-9 shows an example.

Partitioning a table also provides partition independence, meaning, among other things, that you can perform your backup and recovery operations, data loading, and index creation on partitions of a large table instead of the whole table. For example, you can copy a single partition s data using the Data Pump Export utility, reducing export and import times dramatically when you only need part of the entire data set. The ability to perform tasks on partitions instead of entire tables means that your database downtime will be reduced drastically.

Although partitioned tables generally improve query performance in very large tables, they aren t a panacea for poor coding or other design problems in the application. Partitioning also carries a price in terms of additional work to maintain the partitions and their indexes.