With today’s economy in such dire straits, many companies are getting back to basics and reviewing the overlooked areas in order to save any money possible. In particular, Oracle licensing is expensive and complicated, and therefore becomes a viable discussion for many companies looking at potentially migrating their databases over to more economical Oracle, or non-Oracle releases. The key to this equation remains on what the database release can deliver, it’s overall encompassing support, and then lastly, how is it competitively priced.

In reading Bridget Botelho’s 2007 article on ‘Licensing for quad-core processors gets tricky‘, chip manufactures such as Intel are pushing to make the Quad-Core the industry standard for all servers. Microsoft’s position on licensing remains the same when it relates to cores, which is licensed ‘per physical processor’, and has no future plans to change this model. Keeping in tune with their competitors and their releases, Oracle’s pricing on Standard Edition was simplified so customers can run systems with as many as four processors with no limit on the number of cores. However, Oracle’s pricing on Enterprise Edition remains complicated  in regards to cores. "Oracle has four categories for licensing, and each category has a unique processor factor that is used to determine the total number of processor licenses. For instance, the processor factor for the UltraSPARC T1 is 0.25. To determine how many licenses are required, Oracle multiplies that number by the number of cores. A Sun Fire T2000 server with one 1.2 GHz UltraSPARC T1 processor and eight cores requires two licenses (eight multiplied by a processor factor of .25 totals two processor licenses). Processor factors for AMD and Intel chips are 0.50, so a Hewlett-Packard Co. (HP) ProLiant DL145 G2 with two AMD Opteron 200 series dual-core processors will require two multiplied by two multiplied by a 0.5 processor factor, totaling two processor licenses with a list license fee of $80,000. All other multicore chips, like Sun’s UltraSPARC IV, have a 0.75 processor factor, and single core chips have a processor factor of 1.0. "

Oracle Database is available in four editions, each suitable for different development and deployment scenarios.

The Oracle Database Product Family:

Oracle Database Standard Edition One:
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Oracle Database Standard Edition One delivers unprecedented ease of use, power, and performance for workgroup, department-level, and Web applications. Standard Edition One can only be licensed on servers with a maximum capacity of two processors.

Oracle Database Standard Edition:
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Oracle Database Standard Edition delivers the unprecedented ease of use, power, and performance of Standard Edition One, with support for larger machines and clustering of services with Real Application Clusters. Oracle Database Standard Edition can be licensed on single servers or server clusters that have a maximum capacity of four processors. Real Application Clusters is not included in the Standard Edition of releases prior to Oracle Database 10g, nor is it an available option with those earlier releases. When used in a clustered server environment, Oracle Database Standard Edition requires the use of Oracle Cluster Ready Services (CRS). Third-party clusterware management solutions are not supported. In addition, Automatic Storage Management (ASM) must be used to manage the data stored in Oracle Database. Third-party volume managers and file systems are not supported for this purpose. CRS and ASM are required in a clustered server environment in order to facilitate the installation, configuration, and support of Real Application Clusters on Standard Edition.

Oracle Database Enterprise Edition:
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Oracle Database Enterprise Edition provides the performance, availability, scalability, and security required for mission-critical applications such as high-volume online transaction processing (OLTP) applications, query-intensive data warehouses, and demanding Internet applications. Oracle Database Enterprise Edition contains all of the components of Oracle Database, and can be further enhanced with the purchase of the options and packs.

Oracle Database Personal Edition:
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Oracle Database Personal Edition supports single-user development and deployment environments that require full compatibility with Oracle Database Standard Edition One, Oracle Database Standard Edition, and Oracle Database Enterprise Edition. Personal Edition includes all of the components that are included with Enterprise Edition, as well as all of the options that are available with Enterprise Edition, with the exception of the Oracle Real Application Clusters option, which cannot be used with Personal Edition. Personal Edition is available on Windows 2000, Windows NT, Windows XP, and Windows Server 2003 (32-bit and 64-bit versions). The Management Packs are not included in Personal Edition.

The following table lists the options available with this release:

The following table lists the features available with this release:

The Oracle SQL aggregate FIRST and LAST are very similar functions. Both are aggregate and analytic functions that operate on a set of values from a set of rows that rank as the FIRST or LAST with respect to a given sorting specification. If only one row ranks as FIRST or LAST, the aggregate operates on the set with only one element.

This function takes as an argument any numeric datatype or any nonnumeric datatype that can be implicitly converted to a numeric datatype. The function returns the same datatype as the numeric datatype of the argument.

APPLIES TO: Oracle 9i, Oracle 10g, Oracle 11g

SYNTAX: aggregate_function(column_name) KEEP (DENSE_RANK FIRST ORDER BY column_name [ASC|DESC NULLS FIRST|LAST) OVER (PARTITION BY column_name)

AGGREGATE EXAMPLE: The following example returns, within each department of the sample table employees, the minimum salary among the employees who make the lowest commission and the maximum salary among the employees who make the highest commission:

SELECT
 emp.last_name,
 emp.department_id,
 emp.salary,
 MIN(emp.salary) KEEP (DENSE_RANK FIRST ORDER BY emp.commission_pct) OVER
(PARTITION BY emp.department_id) min_salary,
 MAX(emp.salary) KEEP (DENSE_RANK LAST ORDER BY emp.commission_pct) OVER
(PARTITION BY emp.department_id) max_salary
FROM
 employees emp
WHERE
 emp.department_id in (20, 30)
ORDER BY emp.department_id, emp.salary;

OVERVIEW: Aggregate functions return a single result row based on groups of rows, rather than on single rows. Aggregate functions can appear in select lists and in ORDER BY and HAVING clauses. They are commonly used with the GROUP BY clause in a SELECT statement, where Oracle Database divides the rows of a queried table or view into groups. In a query containing a GROUP BY clause, the elements of the select list can be aggregate functions, GROUP BY expressions, constants, or expressions involving one of these. Oracle applies the aggregate functions to each group of rows and returns a single result row for each group.

If you omit the GROUP BY clause, then Oracle applies aggregate functions in the select list to all the rows in the queried table or view. You use aggregate functions in the HAVING clause to eliminate groups from the output based on the results of the aggregate functions, rather than on the values of the individual rows of the queried table or view.

Analytic functions compute an aggregate value based on a group of rows. They differ from aggregate functions in that they return multiple rows for each group. The group of rows is called a ‘window’ and is defined by the analytic_clause. For each row, a sliding window of rows is defined. The window determines the range of rows used to perform the calculations for the current row. Window sizes can be based on either a physical number of rows or a logical interval such as time.

Analytic functions are the last set of operations performed in a query except for the final ORDER BY clause. All joins and all WHERE, GROUP BY, and HAVING clauses are completed before the analytic functions are processed. Therefore, analytic functions can appear only in the select list or ORDER BY clause.

The Oracle SQL aggregate and analytic function CUME_DIST calculates the cumulative distribution of a value in a group of values. The range of values returned by CUME_DIST is >0 to <=1. Tie values always evaluate to the same cumulative distribution value.

This function takes as arguments any numeric datatype or any nonnumeric datatype that can be implicitly converted to a numeric datatype. Oracle Database determines the argument with the highest numeric precedence, implicitly converts the remaining arguments to that datatype, makes the calculation, and returns NUMBER.

APPLIES TO: Oracle 9i, Oracle 10g, Oracle 11g

SYNTAX: CUME_DIST(value) OVER (partition_clause order_by_clause)

AGGREGATE EXAMPLE: The following example calculates the cumulative distribution of a hypothetical employee with a salary of $15,500 and commission rate of 5% among the employees in the sample table employees:

SELECT
 CUME_DIST(15500, .05) WITHIN GROUP (ORDER BY emp.salary,
emp.commission_pct) cume_dist
FROM
 employees emp;

ANALYTIC EXAMPLE: The following example calculates the salary percentile for each employee in the purchasing division. For example, 40% of clerks have salaries less than or equal to Himuro.

SELECT
 emp.job_id,
 emp.last_name,
 emp.salary,
 CUME_DIST() OVER (PARTITION BY emp.job_id ORDER BY emp.salary) AS cume_dist
FROM
 employees emp
WHERE
 upper(emp.job_id) LIKE ‘PU%’;

OVERVIEW: Aggregate functions return a single result row based on groups of rows, rather than on single rows. Aggregate functions can appear in select lists and in ORDER BY and HAVING clauses. They are commonly used with the GROUP BY clause in a SELECT statement, where Oracle Database divides the rows of a queried table or view into groups. In a query containing a GROUP BY clause, the elements of the select list can be aggregate functions, GROUP BY expressions, constants, or expressions involving one of these. Oracle applies the aggregate functions to each group of rows and returns a single result row for each group.

If you omit the GROUP BY clause, then Oracle applies aggregate functions in the select list to all the rows in the queried table or view. You use aggregate functions in the HAVING clause to eliminate groups from the output based on the results of the aggregate functions, rather than on the values of the individual rows of the queried table or view.

Analytic functions compute an aggregate value based on a group of rows. They differ from aggregate functions in that they return multiple rows for each group. The group of rows is called a ‘window’ and is defined by the analytic_clause. For each row, a sliding window of rows is defined. The window determines the range of rows used to perform the calculations for the current row. Window sizes can be based on either a physical number of rows or a logical interval such as time.

Analytic functions are the last set of operations performed in a query except for the final ORDER BY clause. All joins and all WHERE, GROUP BY, and HAVING clauses are completed before the analytic functions are processed. Therefore, analytic functions can appear only in the select list or ORDER BY clause.

The Oracle SQL aggregate and analytic function DENSE_RANK computes the rank of a row in an ordered group of rows and returns the rank as a NUMBER. The ranks are consecutive integers beginning with 1.

The largest rank value is the number of unique values returned by the query. Rank values are not skipped in the event of ties. Rows with equal values for the ranking criteria receive the same rank. This function is useful for top-N and bottom-N reporting.

This function accepts as arguments any numeric datatype and returns NUMBER.

APPLIES TO: Oracle 9i, Oracle 10g, Oracle 11g

SYNTAX: DENSE_RANK() OVER (query_partition_clause order_by_clause)

AGGREGATE EXAMPLE: The following example computes the ranking of a hypothetical employee with the salary $15,500 and a commission of 5% in the sample table employees:

SELECT
 DENSE_RANK(15500, .05) WITHIN GROUP (ORDER BY emp.salary DESC,
emp.commission_pct) dense_rank
FROM
 employees emp;

ANALYTIC EXAMPLE: The following statement selects the department name, employee name, and salary of all employees who work in the human resources or purchasing department, and then computes a rank for each unique salary in each of the two departments. The salaries that are equal receive the same rank. Compare this example with the example for RANK.

SELECT
 dep.department_id,
 emp.last_name,
 emp.salary,
 DENSE_RANK() OVER (PARTITION BY emp.department_id ORDER BY emp.salary) as dense_rank
FROM
 employees emp,
 departments dep
WHERE
 emp.department_id = dep.department_id
 AND dep.department_id IN (’60′, ’90′);

OVERVIEW: Aggregate functions return a single result row based on groups of rows, rather than on single rows. Aggregate functions can appear in select lists and in ORDER BY and HAVING clauses. They are commonly used with the GROUP BY clause in a SELECT statement, where Oracle Database divides the rows of a queried table or view into groups. In a query containing a GROUP BY clause, the elements of the select list can be aggregate functions, GROUP BY expressions, constants, or expressions involving one of these. Oracle applies the aggregate functions to each group of rows and returns a single result row for each group.

If you omit the GROUP BY clause, then Oracle applies aggregate functions in the select list to all the rows in the queried table or view. You use aggregate functions in the HAVING clause to eliminate groups from the output based on the results of the aggregate functions, rather than on the values of the individual rows of the queried table or view.

Analytic functions compute an aggregate value based on a group of rows. They differ from aggregate functions in that they return multiple rows for each group. The group of rows is called a ‘window’ and is defined by the analytic_clause. For each row, a sliding window of rows is defined. The window determines the range of rows used to perform the calculations for the current row. Window sizes can be based on either a physical number of rows or a logical interval such as time.

Analytic functions are the last set of operations performed in a query except for the final ORDER BY clause. All joins and all WHERE, GROUP BY, and HAVING clauses are completed before the analytic functions are processed. Therefore, analytic functions can appear only in the select list or ORDER BY clause.

The Oracle SQL analytical function FIRST_VALUE returns the first value in an ordered set of values. If the first value in the set is null, then the function returns NULL unless you specify IGNORE NULLS. This setting is useful for data densification. If you specify IGNORE NULLS, then FIRST_VALUE returns the fist non-null value in the set, or NULL if all values are null.

You cannot use FIRST_VALUE or any other analytic function for expr. That is, you cannot nest analytic functions, but you can use other built-in function expressions for expr.

APPLIES TO: Oracle 9i, Oracle 10g, Oracle 11g

SYNTAX: FIRST_VALUE(expr [IGNORE NULLS]) OVER (analytic clause)

EXAMPLE: The following example selects, for each employee in Department 20 and 30, the name of the employee with the lowest salary.

SELECT
 emp.department_id,
 emp.last_name,
 emp.salary,
 FIRST_VALUE(emp.last_name) OVER (PARTITION BY emp.department_id ORDER BY
salary ASC ) AS lowest_salary
FROM
 employees emp
WHERE
 emp.department_id in (20, 30);

OVERVIEW: Analytic functions compute an aggregate value based on a group of rows. They differ from aggregate functions in that they return multiple rows for each group. The group of rows is called a ‘window’ and is defined by the analytic_clause. For each row, a sliding window of rows is defined. The window determines the range of rows used to perform the calculations for the current row. Window sizes can be based on either a physical number of rows or a logical interval such as time.

Analytic functions are the last set of operations performed in a query except for the final ORDER BY clause. All joins and all WHERE, GROUP BY, and HAVING clauses are completed before the analytic functions are processed. Therefore, analytic functions can appear only in the select list or ORDER BY clause.

Building upon the generous contributions of the Oracle community, this database trigger was designed to provide companies with SOX and ICE related information regarding any 3rd party tool’s access to a given database.

The trigger is designed to restrict access to only the ‘allowable’ programmes, and then validates the session information against specified Windows/Linux/Unix accounts. Additionally, if the executable is renamed in an attempt to disguise the programme, the trigger will not be able to identify the executable and immediately terminate the user’s session. If the database account has ‘admin’ options, the trigger will not terminate the session, but will record the session in an audit table, along with broadcasting an email with the connection information.

• All standard executables have an ‘A’ flag status and allows the programme to run unchecked
• All ‘C’ flagged programmes are checked against the user’s Windows/Linux account to validate if this user is authorized to connect with an identified programme

The database trigger basically identifies the session’s programme executable, and then validates the value against a list of values that resides within the OMON_TOOLPRIV_HDR and OMON_TOOLPRIV_DTL tables respectively.

• If the session’s programme is allowed, no action is taken
• If the session’s programme is to be validated, it checks the session information against maintained information (programme and Window/Linux account)
• If the checked programme is not allowed, it performs the following:
• Records the session information in an audit table
• Sends an email to identified recipients, with the session information and action taken
• Records the attempt and session information in the Oracle Alertlog
• Immediately terminates the user’s session
• If the checked programme is validated and allowed, it performs the following:
• Records the session information in an audit table
• Sends an email to identified recipients, with the session information and action taken
• Records the attempt and session information in the Oracle Alertlog

The rollout of this trigger and the account security maintenance is very simplistic, and is designed to reduce it’s footprint on the database by keeping most of the objects in a separate tablespace.

Step 1: Create a tablespace for the table and index objects to reside. All of the objects can be created with the SYSDBA account, as the only the trigger is recommended to reside in the SYS schema.

Step 2: Create the Email header and detail tables for the recipients

Step 3: Create the Tool Privilege header and detail tables for the executables and accounts that are authorized to run the executables

Step 4: Create the audit table for recording all ‘validated’ or offending programmes

Step 5: Create the database trigger that will perform all the needed tasks. It is preferred that this trigger is created and managed by the SYSDBA account.