birt code 39

birt code 39

birt code 39

birt code 39

birt code 39

birt code 39,

birt code 39,

birt code 39,

birt code 39,
birt code 39,
birt code 39,
birt code 39,

birt code 39,
birt code 39,
birt code 39,
birt code 39,

birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,

birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,
birt code 39,

7. Naftaly H. Minsky and David Rozenshtein, A Software Development Environment for Law-Governed Systems, ACM SIGPLAN Notices, February 1989. 8. Frank DeRemer and Hans Kron, Programming-in-the-Large Versus Programming-in-the-Small, IEEE Transactions on Software Engineering, June 1976. 9. James M. Purtilo, The Polylith Software Bus, ACM Transactions on Programming Languages and Systems, January 1994. 10. Jan A. Bergstra and Paul Klint, The Discrete Time ToolBus: A Software Coordination Architecture, Science of Computer Programming, July 1998. 11. Steven P. Reiss, Connecting Tools Using Message Passing in the Field Environment, IEEE Software, July/August 1990. 12. David C. Luckham and James Vera, An Event-Based Architecture Definition Language, IEEE Transactions on Software Engineering, September 1995. 13. Robert Allen and David Garlan, Formalizing Architectural Connection (proceedings of the 16th International Conference on Software Engineering, Sorrento, Italy, May 1994). 14. Nenad Medvidovic, Richard N. Taylor, and E. James Whitehead, Jr., Formal Modeling of Software Architectures at Multiple Levels of Abstraction, (proceedings of the California Software Symposium, Los Angeles, CA, April 1996). 15. David Garlan, Robert Monroe, and David Wile, ACME: An Architectural Interconnection Language (technical report, Carnegie Mellon University, Pittsburgh, November 1995).

On the surface, expdp and impdp are quite similar to the traditional export and import utilities. However, while they are syntactically similar to the Data Pump clients, exp and imp are ordinary user processes that use SQL statements like SELECT, INSERT, and CREATE. In contrast, the new Data Pump utilities are more like control processes that initiate jobs. In Data Pump Export and Import, the database instance handles the Data Pump utilities. The Data Pump technology consists of three major components: DBMS_DATAPUMP package: This is the main engine for driving data dictionary metadata loading and unloading. The DBMS_DATAPUMP package (Data Pump API) contains the guts of the Data Pump technology in the form of procedures that actually drive the data loading and unloading jobs. The contents of this package perform the work of both the Data Pump Export and Import utilities. DBMS_METADATA package: To extract and modify metadata, Oracle provides the DBMS_ METADATA package (Metadata API), which has been available since Oracle9i. In the traditional export and import utilities, the metadata of the objects is included in the export dump file. In Data Pump technology, you need to use the DBMS_METADATA package to extract the appropriate metadata. Command-line clients: The two command-line utilities expdp and impdp correspond to the old exp and imp utilities. The expdp utility invokes the Data Pump Export utility, and the impdp utility invokes the Data Pump Import utility. The dump files you create with these new utilities aren t compatible with the older export/import utilities. Note that both packages DBMS_DATAPUMP and DBMS_METADATA act as APIs (the Data Pump API and the Metadata API), in the sense that you can use either of them directly in your programs to load and unload data without accessing the expdp and impdp clients.

A Data Pump Import or Export job can access table data in either of two ways: Direct path: This access uses the Direct Path API. Direct-path exports and imports lead to improved performance, since the direct-path internal stream format is the same format as the data stored in Oracle dump files. This leads to a reduced need for data conversions. The big advantage of the direct-path mode is that it bypasses the database buffer cache and doesn t generate any undo data. External tables: The external tables feature lets Oracle read data from and write data to operating system files that lie outside the database. 13 explains external tables in detail. It is up to Oracle to decide which access method it will employ for a given job. Oracle always tries to use the direct-path method to load or unload data, but under some conditions, it may not be able to employ that method. In the following cases, the structure of the table and/or the indexes precludes the use of direct-path access, so Data Pump will use external tables:

Clustered tables Active triggers in the tables A single partition in a table with a global index Referential integrity constraints Domain indexes on LOB columns Tables with fine-grained access control enabled in the insert mode Tables with BFILE or opaque type columns