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Statements that modify data in the database may have the potential to perform parallel DML (PDML). During PDML, Oracle uses many threads or processes to perform your INSERT, UPDATE, or DELETE instead of a single serial process. On a multi-CPU machine with plenty of I/O bandwidth, the potential increase in speed may be large for mass DML operations. In releases of Oracle prior to 9i, PDML required partitioning. If your tables were not partitioned, you could not perform these operations in parallel in the earlier releases. If the tables were partitioned, Oracle would assign a maximum degree of parallelism to the object, based on the number of physical partitions it had. This restriction was, for the most part, relaxed in Oracle9i and later with two notable exceptions. If the table you wish to perform PDML on has a bitmap index in place of a LOB column, then the table must be partitioned in order to have the operation take place in parallel, and the degree of parallelism will be restricted to the number of partitions. In general, though, you no longer need to partition to use PDML.

You can provide four different values to the TABLE_EXISTS_ACTION parameter: With SKIP (the default), Data Pump will skip a table if it exists The APPEND value appends rows to the table The TRUNCATE value truncates the table and reloads the data from the export dump file The REPLACE value drops the table if it exists, re-creates it, and reloads it..

The JOB_NAME, STATUS, and PARALLEL parameters carry identical meanings as their Data Pump Export counterparts. Note that if you have multiple dump files, you should specify them either explicitly or by using the %U notation, as shown earlier in the coverage of Data Pump Export parameters.

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The entry-level standard does not include features such as outer joins, the new inner join syntax, and so on. Transitional does specify outer join syntax and inner join syntax. Intermediate adds more, and Full is, of course all of SQL92. Most books on SQL92 do not differentiate between the various levels, which leads to confusion on the subject. They demonstrate what a theoretical database implementing SQL92 full would look like. It makes it impossible to pick up a SQL92 book, and apply what you see in the book to just any SQL92 database. The bottom line is that SQL92 will not go very far at the entry level and, if you use any of the features of intermediate or higher, you risk not being able to port your application. SQL99 defines only two levels of conformance: Core and Enhanced. It attempted to go far beyond traditional SQL and introduced object relational constructs (arrays, collections, etc.). It covered a SQL MM (multi-media) type, object-relational types, and so on. No vendors are certifying databases to be SQL99 Core or Enhanced compliant and, in fact, I know of no vendor who is even claiming his product is fully compliant with either level of conformance. You should not be afraid to make use of vendor-specific features after all, you are paying a lot of money for them. Every database has its own bag of tricks, and you can always find a way to perform a given operation in each database. Use what is best for your current database, and re-implement components as you go to other databases. Use good programming techniques to isolate yourself from

In the area of strictly read query performance (SELECT statements), partitioning comes into play with two types of specialized operations: Partition elimination: Some partitions of data are not considered in the processing of the query. We have already seen an example of partition elimination. Parallel operations: Examples of this are parallel full table scans and parallel index range scans. However, the benefit you can derive from these depends very much on the type of system you are using. OLTP Systems You should not look toward partitions as a way to massively improve query performance in an OLTP system. In fact, in a traditional OLTP system, you must apply partitioning with care so as to not negatively affect runtime performance. In a traditional OLTP system, most queries are expected to return virtually instantaneously, and most of the retrievals from the database are expected to be via very small index range scans. Therefore, the main performance benefits of partitioning listed previously would not come into play. Partition elimination is useful where you have full scans of large objects, because it allows you to avoid full scanning large

You can perform a Data Pump import in various modes, using the TABLE, SCHEMAS, TABLESPACES, and FULL parameters, just as with the Data Pump Export utility. You can use the TRANSPORTABLE_ TABLESPACES parameter when you wish to transport tablespaces between databases. You use the TRANSPORT_FULL_CHECK parameter in a manner analogous to its use under Data Pump Export, when you re performing a transportable tablespaces operation. The TRANSPORT_FULL_ CHECK parameter is applicable to a tablespace transport only if you re using the NETWORK_LINK parameter. The TRANSPORT_DATAFILES import parameter is used during a transportable tablespaces operation, to specify the list of datafiles the job should import into the target database. You must first copy

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