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Lesson 2Introduction to Oracle: SQL and PL/SQL
Objective Complete your preparation for the first test as DBA

SQL Extensions for the Oracle Database Management System

The Oracle Database Management System (DBMS) offers a variety of SQL extensions that enhance the functionality and capabilities of the SQL language. These extensions provide advanced features for querying, managing, and manipulating data within the Oracle database, allowing developers and administrators to perform complex tasks more efficiently. This article will discuss the key types of SQL extensions available in the Oracle DBMS.
  1. Analytic Functions: Oracle provides a wide range of analytic functions that enable developers to perform complex calculations and data analysis tasks directly within SQL queries. These functions are designed to operate on result sets, aggregating and processing data to provide insights and valuable information. Examples of analytic functions include RANK, DENSE_RANK, ROW_NUMBER, NTILE, LAG, LEAD, and various statistical and window functions.
  2. Hierarchical Query Extensions: Oracle extends SQL with hierarchical query features, such as the CONNECT BY clause and the START WITH clause, allowing users to query and retrieve data from hierarchical structures and parent-child relationships. The CONNECT BY clause specifies the relationship between parent and child rows, while the START WITH clause determines the root of the hierarchy. These clauses enable developers to traverse and manipulate hierarchical data efficiently within SQL queries.
  3. Regular Expression Functions: Oracle supports regular expression functions that enable pattern matching and manipulation of character data within SQL queries. These functions provide powerful text searching and processing capabilities, allowing developers to perform complex string manipulation tasks directly within SQL queries. Key regular expression functions include REGEXP_LIKE, REGEXP_INSTR, REGEXP_SUBSTR, and REGEXP_REPLACE.
  4. Model Clause: The Oracle MODEL clause is a powerful SQL extension that allows users to perform multi-dimensional array calculations and data transformations within SQL queries. This feature enables developers to define complex calculations and relationships between columns, effectively creating a spreadsheet-like model for data processing. The MODEL clause supports various types of calculations, including arithmetic, aggregate, and window functions.
  5. Partitioning and Subquery Factoring: Oracle extends SQL with partitioning and subquery factoring features to improve query performance and maintainability. The PARTITION BY clause enables developers to divide a result set into partitions, allowing aggregate and window functions to operate on specific subsets of data. Subquery factoring, also known as the WITH clause, allows users to define subqueries that can be referenced multiple times within the main query, improving query readability and potentially boosting performance through materialization.
  6. Data Definition Language (DDL) and Data Manipulation Language (DML) Extensions: Oracle provides various extensions to the SQL Data Definition Language (DDL) and Data Manipulation Language (DML) to support advanced database management and data manipulation tasks. Examples of DDL extensions include CREATE MATERIALIZED VIEW, CREATE TYPE, and CREATE TRIGGER, which allow developers to create and manage specialized database objects. DML extensions, such as MERGE, FORALL, and BULK COLLECT, provide advanced data manipulation capabilities and support for bulk operations.

Oracle offers a diverse range of SQL extensions that enhance the functionality and capabilities of the SQL language within the Oracle DBMS. These extensions allow developers and administrators to perform complex data analysis, manipulation, and management tasks directly within SQL queries, resulting in more efficient and streamlined database operations.

Extensions for SQL

Extensions for SQL (oracle-sql) is the first course in a three-part series.
  1. Programming in PL/SQL and
  2. PL/SQL Stored Objects

will complete your preparation for the test in the Oracle Certified Database Administrator and/or Certified Application Developer track.
Oracle SQL has added many non-standard extensions to their implementation of the ANSI SQL standard. The Oracle variation of SQL includes additional features that can improve the speed of SQL queries. Current Oracle extensions consist of
  1. Explain,
  2. Jobs,
  3. Oracle Text,
  4. Sessions,
  5. Monitor, and
  6. Table spaces.

Oracle Extension to ANSI Standard SQL

The majority of relational database vendors proclaim that their SQL is 100% ANSI standard. While this is true in most cases, the database vendors always add additional features and functionality to distinguish their product from the other vendors. Oracle SQL has many useful, but non-standard extensions to their implementation of the ANSI SQL standard. The Oracle version of SQL includes additional features that can greatly improve the speed of SQL queries. These extensions are commonly referred to as built-in functions known as BIFs. The common BIFs include:
  1. Performance extensions (SQL hints, parallel queries)
  2. Data transformation extensions (null values (NVL), decode)
  3. Formatting extensions (to_char, to_date, to_upper)
It is important to note that these extensions are unique to Oracle SQL. This is because applications that are written to be portable between databases must not use any of the vendor-supplied extensions. The portable SQL application systems are specifically designed to be generic so they can be moved between relational database products without altering the SQL statements. These extensions are very helpful in quickly retrieving and formatting data, but they also have drawbacks to the database. The primary disadvantage is that until Oracle8i you could not use an index to query a column that contained a BIF. For example, assume that we have the last_name column of the CUSTOMER table indexed.
The following query would use the index:
Select * from customer where last_name like 'B%'; 

This query, because it uses a BIF, cannot use the index:
Select * from customer where last_name like to_upper('b%');

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