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OLAP DML Reference, 11g Release 1 (11.1)

AGGREGATION

AGGREGATIONWithin a model, the AGGREGATION function allows you to create a model that represents a custom … aggregate. Such an aggmap can be used for dynamic aggregation with the AGGREGATE function.

OLAP DML Reference, 11g Release 1 (11.1)

AGGREGATION

Note: Because the AGGREGATION function is intended only for dynamic aggregation, a model that contains…A list of one or more dimension values to include in the custom aggregation. The specified values … a variable. Examples Example 7-9 Using the AGGREGATION Function to Create a Custom Aggregate The … specification of the model using the AGGREGATION function. DEFINE mytime_custagg MODEL MODEL JOINLINES … ('DIMENSION time' 'My_Time

Database Concepts, 11g Release 1 (11.1)

Business Intelligence

SQL for AggregationAggregation is a fundamental part of data warehousing. To improve aggregation performance in your … aggregation, from the most detailed up to a grand total Calculate all possible combinations of aggregations … multidimensional requests: Show total sales across all products at increasing aggregation levels for a

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

Considerations when Using AggregationThis section discusses the following topics. Hierarchy Handling in ROLLUP and CUBE Column Capacity in ROLLUP and CUBE HAVING Clause Used with GROUP BY Extensions ORDER BY Clause Used with GROUP BY Extensions Using Other Aggregate Functions with ROLLUP and CUBE

Database Data Warehousing Guide, 11g Release 1 (11.1)

Glossary

aggregationaggregation is synonymous with summarization, and aggregate data is synonymous with summary data.

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

Aggregation Level Bit Vector GROUPING_IDa, b 0 0 0 a 0 1 1 b 1 0 2 Grand Total 1 1 3 GROUPING_ID clearly distinguishes groupings created by grouping set specification, and it is very useful during refresh and rewrite of materialized views.

OLAP User's Guide, 11g Release 1 (11.1)

Advanced Aggregations

Aggregation OperatorsAnalytic workspaces provide an extensive list of aggregation methods, including weighted, hierarchical, and weighted hierarchical methods.

OLAP DML Reference, 11g Release 1 (11.1)

What's New in the OLAP DML?

Aggregation ImprovementsIn Oracle11 g, the following changes have been made to enhance aggregation: Aggregation by

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

20 SQL for Aggregation in Data WarehousesThis chapter discusses aggregation of SQL, a basic aspect of data warehousing. It contains these … topics: Overview of SQL for Aggregation in Data Warehouses ROLLUP Extension to GROUP BY CUBE Extension … Considerations when Using Aggregation Computation Using the WITH Clause Working with Hierarchical Cubes in SQL

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

ORDER BY Clause Used with GROUP BY Extensions-aggregate columns. This requirement means that queries using ORDER BY along with aggregation

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

Using Other Aggregate Functions with ROLLUP and CUBEmost common type of aggregation, these extensions can also be used with all other functions available

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

ROLLUP Syntaxrounding. This query returns the following sets of rows: Regular aggregation rows that would be

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

GROUP_ID FunctionWhile the extensions to GROUP BY offer power and flexibility, they also allow complex result sets that can include duplicate groupings. The GROUP_ID function lets you distinguish among duplicate groupings. If there are multiple sets of rows calculated for a given level, GROUP_ID assigns the value of 0 to all the rows in the first set. All other sets of duplicate rows for a particular grouping are

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

GROUPING SETS SyntaxGROUPING SETS syntax lets you define multiple groupings in the same query. GROUP BY computes all the groupings specified and combines them with UNION ALL. For example, consider the following statement: GROUP BY GROUPING sets (channel_desc, calendar_month_desc, country_id ) This statement is equivalent to: GROUP BY channel_desc UNION ALL GROUP BY calendar_month_desc UNION ALL GROUP BY country_id Table

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

Composite Columnsgroupings. For example, in CUBE or ROLLUP, composite columns would mean skipping aggregation across certain … Columns You do not have full control over what aggregation levels you want with CUBE and ROLLUP. For

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

Working with Hierarchical Cubes in SQLThis section illustrates examples of working with hierarchical cubes.

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

Optimized PerformanceNot only multidimensional issues, but all types of processing can benefit from enhanced aggregation … details to higher levels will benefit from optimized aggregation performance. These extensions … provide aggregation features and bring many benefits, including: Simplified programming requiring less SQL … and network traffic

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

When to Use CUBEConsider Using CUBE in any situation requiring cross-tabular reports. The data needed for cross-tabular reports can be generated with a single SELECT using CUBE. Like ROLLUP, CUBE can be helpful in generating summary tables. Note that population of summary tables is even faster if the CUBE query executes in parallel. CUBE is typically most suitable in queries that use columns from multiple dimensions

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

Calculating Subtotals Without CUBEJust as for ROLLUP, multiple SELECT statements combined with UNION ALL statements could provide the same information gathered through CUBE. However, this might require many SELECT statements. For an n-dimensional cube, 2 to the n SELECT statements are needed. In the three-dimension example, this would mean issuing SELECT statements linked with UNION ALL. So many SELECT statements yield inefficient

Database Data Warehousing Guide, 11g Release 1 (11.1)

SQL for Aggregation in Data Warehouses

Column Capacity in ROLLUP and CUBECUBE, ROLLUP, and GROUPING SETS do not restrict the GROUP BY clause column capacity. The GROUP BY clause, with or without the extensions, can work with up to 255 columns. However, the combinatorial explosion of CUBE makes it unwise to specify a large number of columns with the CUBE extension. Consider that a 20-column list for CUBE would create 2 to the 20 combinations in the result set. A very large