The DBMS_AW PL/SQL package provides procedures and functions for interacting with analytic workspaces.
This appendix contains the following topics:
One reference topic for each DBMS_AW subprogram
To interact with Oracle OLAP, you must attach an analytic workspace to your session. When you have DBMS_AW PL/SQL package installed you can perform this task from within SQL*Plus. For example, you can use the following command to attach an analytic workspace with read-only access.
EXECUTE dbms_aw.aw_attach ('awname');
Each analytic workspace is associated with a list of analytic workspaces. The read-only workspace EXPRESS.AW, which contains the OLAP engine code, is always attached last in the list. When you create a workspace, it is attached first in the list by default.
You can reposition an analytic workspace within the list by using keywords such as FIRST and LAST. For example, the following commands show how to move an analytic workspace called MYAW.TEST2 from the second position to the first position on the list.
EXECUTE dbms_aw.execute ('AW LIST'); TEST1 R/O UNCHANGED GLOBAL.TEST1 TEST2 R/O UNCHANGED GLOBAL.TEST2 EXPRESS R/O UNCHANGED SYS.EXPRESS EXECUTE dbms_aw.aw_attach ('test2', FALSE, FALSE, 'FIRST'); EXECUTE dbms_aw.execute ('AW LIST'); TEST2 R/O UNCHANGED GLOBAL.TEST2 TEST1 R/O UNCHANGED GLOBAL.TEST1 EXPRESS R/O UNCHANGED SYS.EXPRESS
From within SQL*Plus, you can rename workspaces and make copies of workspaces. If you have an analytic workspace attached with read/write access, you can update the workspace and save your changes in the permanent database table where the workspace is stored. You must do a SQL COMMIT to save the workspace changes within the database.
The following commands make a copy of the objects and data in workspace test2 in a new workspace called test3, update test3, and commit the changes to the database.
EXECUTE dbms_aw.aw_copy('test2', 'test3'); EXECUTE dbms_aw.aw_update('test3'); COMMIT;
With the DBMS_AW package you can perform the full range of OLAP processing within analytic workspaces. You can import data from legacy workspaces, relational tables, or flat files. You can define OLAP objects and perform complex calculations.
Note:
If you use theDBMS_AW package to create analytic workspaces from scratch, you may not be able to use OLAP utilities, such as Analytic Workspace Manager and the DBMS_AW Aggregate Advisor, which require analytic workspaces of a particular structure.The DBMS_AW package provides several procedures for executing ad hoc OLAP DML commands. Using the EXECUTE or INTERP_SILENT procedures or the INTERP or INTERCLOB functions, you can execute a single OLAP DML command or a series of commands separated by semicolons.
Which procedures you use depends on how you want to direct output and on the size of the input and output buffers. For example, the EXECUTE procedure directs output to a printer buffer, the INTERP_SILENT procedure suppresses output, and the INTERP function returns the session log.
The DBMS_AW package also provides functions for evaluating OLAP expressions. The EVAL_TEXT function returns the result of a text expression, and EVAL_NUMBER returns the result of a numeric expression.
Note:
Do not confuse theDBMS_AW functions EVAL_NUMBER and EVAL_TEXT with the SQL function OLAP_EXPRESSION. See "OLAP_EXPRESSION" for more information.The SQL processor evaluates the embedded OLAP DML commands, either in whole or in part, before sending them to Oracle OLAP for processing. Follow these guidelines when formatting the OLAP DML commands in the olap-commands parameter of DBMS_AW procedures:
Wherever you would normally use a single quote (') in an OLAP DML command, use two single quotes (''). The SQL processor strips one of the single quotes before it sends the OLAP DML command to Oracle OLAP.
In the OLAP DML, a double quote (") indicates the beginning of a comment.
Data can be stored in several different forms in an analytic workspace, depending on whether it is dense, sparse, or very sparse. The Sparsity Advisor is a group of subprograms in DBMS_AW that you can use to analyze the relational source data and get recommendations for storing it in an analytic workspace.
Analytic workspaces analyze and manipulate data in a multidimensional format that allocates one cell for each combination of dimension members. The cell can contain a data value, or it can contain an NA (null). Regardless of its content, the cell size is defined by the data type, for example, every cell in a DECIMAL variable is 8 bytes.
Variables can be either dense (they contain 30% or more cells with data values) or sparse (less than 30% data values). Most variables are sparse and many are extremely sparse.
Although data can also be stored in the multidimensional format used for analysis, other methods are available for storing sparse variables that make more efficient use of disk space and improve performance. Sparse data can be stored in a variable defined with a composite dimension. A composite has as its members the dimension-value combinations (called tuples) for which there is data. When a data value is added to a variable dimensioned by a composite, that action triggers the creation of a composite tuple. A composite is an index into one or more sparse data variables, and is used to store sparse data in a compact form. Very sparse data can be stored in a variable defined with a compressed composite, which uses a different algorithm for data storage from regular composites.
In contrast to dimensional data, relational data is stored in tables in a very compact format, with rows only for actual data values. When designing an analytic workspace, you may have difficulty manually identifying sparsity in the source data and determining the best storage method. The Sparsity Advisor analyzes the source data in relational tables and recommends a storage method. The recommendations may include the definition of a composite and partitioning of the data variable.
The Sparsity Advisor consists of these procedures and functions:
The Sparsity Advisor also provides a public table type for storing information about the dimensions of the facts being analyzed. Three objects are used to define the table type:
DBMS_AW$_COLUMNLIST_TDBMS_AW$_DIMENSION_SOURCE_TDBMS_AW$_DIMENSION_SOURCES_TThe following SQL DESCRIBE statements show the object definitions.
DESCRIBE dbms_aw$_columnlist_t dbms_aw$_columnlist_t TABLE OF VARCHAR2(100) DESCRIBE dbms_aw$_dimension_source_t Name Null? Type ----------------------------------------- -------- ---------------------------- DIMNAME VARCHAR2(100) COLUMNNAME VARCHAR2(100) SOURCEVALUE VARCHAR2(32767) DIMTYPE NUMBER(3) HIERCOLS DBMS_AW$_COLUMNLIST_T PARTBY NUMBER(9) DESCRIBE dbms_aw$_dimension_sources_t dbms_aw$_dimension_sources_t TABLE OF DBMS_AW$_DIMENSION_SOURCE_T
Take these steps to use the Sparsity Advisor:
Call SPARSITY_ADVICE_TABLE to create a table for storing the evaluation of the Sparsity Advisor.
Call ADD_DIMENSION_SOURCE for each dimension related by one or more columns to the fact table being evaluated.
The information that you provide about these dimensions is stored in a DBMS_AW$_DIMENSION_SOURCES_T variable.
Call ADVISE_SPARSITY to evaluate the fact table.
Its recommendations are stored in the table created by SPARSITY_ADVICE_TABLE. You can use these recommendations to make your own judgements about defining variables in your analytic workspace, or you can continue with the following step.
Call the ADVISE_DIMENSIONALITY procedure to get the OLAP DML object definitions for the recommended composite, partitioning, and variable definitions.
or
Use the ADVISE_DIMENSIONALITY function to get the OLAP DML object definition for the recommended composite and the dimension order for the variable definitions for a specific partition.
Example B-1, "Sparsity Advisor Script for GLOBAL" provides a SQL script for evaluating the sparsity of the UNITS_HISTORY_FACT table in the GLOBAL schema. In the GLOBAL analytic workspace, UNITS_HISTORY_FACT defines the Units Cube and is the source for the UNITS variable. UNITS_HISTORY_FACT is a fact table with a primary key composed of foreign keys from four dimension tables. A fifth column contains the facts for Unit Sales.
The CHANNEL_DIM and CUSTOMER_DIM tables contain all of the information for the Channel and Customer dimensions in a basic star configuration. Three tables in a snowflake configuration provide data for the Time dimension: MONTH_DIM, QUARTER_DIM, and YEAR_DIM. The PRODUCT_CHILD_PARENT table is a parent-child table and defines the Product dimension.
Example B-1 Sparsity Advisor Script for GLOBAL
CONNECT global/global
SET ECHO ON
SET LINESIZE 300
SET PAGESIZE 300
SET SERVEROUT ON FORMAT WRAPPED
-- Define and initialize an advice table named AW_SPARSITY_ADVICE
BEGIN
dbms_aw.sparsity_advice_table();
EXCEPTION
WHEN OTHERS THEN NULL;
END;
/
TRUNCATE TABLE aw_sparsity_advice;
DECLARE
dimsources dbms_aw$_dimension_sources_t;
dimlist VARCHAR2(500);
sparsedim VARCHAR2(500);
defs CLOB;
BEGIN
-- Provide information about all dimensions in the cube
dbms_aw.add_dimension_source('channel', 'channel_id', dimsources,
'channel_dim', dbms_aw.hier_levels,
dbms_aw$_columnlist_t('channel_id', 'total_channel_id'));
dbms_aw.add_dimension_source('product', 'item_id', dimsources,
'product_child_parent', dbms_aw.hier_parentchild,
dbms_aw$_columnlist_t('product_id', 'parent_id'));
dbms_aw.add_dimension_source('customer', 'ship_to_id', dimsources,
'customer_dim', dbms_aw.hier_levels,
dbms_aw$_columnlist_t('ship_to_id', 'warehouse_id', 'region_id',
'total_customer_id'));
dbms_aw.add_dimension_source('time', 'month_id', dimsources,
'SELECT m.month_id, q.quarter_id, y.year_id
FROM time_month_dim m, time_quarter_dim q, time_year_dim y
WHERE m.parent=q.quarter_id AND q.parent=y.year_id',
dbms_aw.hier_levels,
dbms_aw$_columnlist_t('month_id', 'quarter_id', 'year_id'));
-- Analyze fact table and provide advice without partitioning
dbms_aw.advise_sparsity('units_history_fact', 'units_cube',
dimsources, dbms_aw.advice_default, dbms_aw.partby_none);
COMMIT;
-- Generate OLAP DML for composite and variable definitions
dimlist := dbms_aw.advise_dimensionality('units_cube', sparsedim,
'units_cube_composite');
dbms_output.put_line('Dimension list: ' || dimlist);
dbms_output.put_line('Sparse dimension: ' || sparsedim);
dbms_aw.advise_dimensionality(defs, 'units_cube');
dbms_output.put_line('Definitions: ');
dbms_aw.printlog(defs);
END;
/
The script in Example B-1, "Sparsity Advisor Script for GLOBAL" generates the following information.
Dimension list: <channel units_cube_composite<product customer time>> Sparse dimension: DEFINE units_cube_composite COMPOSITE <product customer time> Definitions: DEFINE units_cube.cp COMPOSITE <product customer time> DEFINE units_cube NUMBER VARIABLE <channel units_cube.cp<product customer time>> PL/SQL procedure successfully completed.
This SQL SELECT statement shows some columns from the AW_SPARSITY_ADVICE table, which is the basis for the recommended OLAP DML object definitions.
SELECT fact, dimension, dimcolumn, membercount nmem, leafcount nleaf,
advice, density
FROM aw_sparsity_advice
WHERE cubename='units_cube';
This query returns the following result set:
FACT DIMENSION DIMCOLUMN NMEM NLEAF ADVICE DENSITY -------------------- ------------ ------------ ----- ------ ------------ -------- units_history_fact channel channel_id 3 3 DENSE .46182 units_history_fact product item_id 48 36 SPARSE .94827 units_history_fact customer ship_to_id 61 61 SPARSE .97031 units_history_fact time month_id 96 79 SPARSE .97664
The management of aggregate data within analytic workspaces can have significant performance implications. To determine an optimal set of dimension member combinations to preaggregate, you can use the ADVISE_REL and ADVISE_CUBE procedures in the DBMS_AW package. These procedures are known together as the Aggregate Advisor.
Based on a percentage that you specify, ADVISE_REL suggests a set of dimension members to preaggregate. The ADVISE_CUBE procedure suggests a set of members for each dimension of a cube.
Instructions for storing aggregate data are specified in an analytic workspace object called an aggmap. The OLAP DML AGGREGATE command uses the aggmap to preaggregate the data. Any data that is not preaggregated is aggregated dynamically by the AGGREGATE function when the data is queried.
Choosing a balance between static and dynamic aggregation depends on many factors including disk space, available memory, and the nature and frequency of the queries that run against the data. After weighing these factors, you may arrive at a percentage of the data to preaggregate.
Once you have determined the percentage of the data to preaggregate, you can use the Aggregate Advisor. These procedures analyze the distribution of dimension members within hierarchies and identify an optimal set of dimension members to preaggregate.
Based on a precompute percentage that you specify, the ADVISE_REL procedure analyzes a family relation, which represents a dimension with all its hierarchical relationships, and returns a list of dimension members.
ADVISE_CUBE applies similar heuristics to each dimension in an aggmap for a cube.
See Also:
Example B-2 uses the following sample Customer dimension to illustrate the ADVISE_REL procedure.
Sample Dimension: Customer in the Global Analytic Workspace
The Customer dimension in GLOBAL_AW.GLOBAL has two hierarchies: SHIPMENTS_ROLLUP with four levels, and MARKET_ROLLUP with three levels. The dimension has 106 members. This number includes all members at each level and all level names.
The members of the Customer dimension are integer keys whose text values are defined in long and short descriptions.
The following OLAP DML commands show information about the representation of the Customer dimension, which is in database standard form.
SET serveroutput ON ---- Number of members of Customer dimension EXECUTE dbms_aw.execute('SHOW STATLEN(customer)') 106 ---- Hierarchies in Customer dimension; EXECUTE dbms_aw.execute('REPORT W 40 customer_hierlist'); CUSTOMER_HIERLIST ---------------------------------------- MARKET_ROLLUP SHIPMENTS_ROLLUP ---- Levels in Customer dimension EXECUTE dbms_aw.execute('REPORT W 40 customer_levellist'); CUSTOMER_LEVELLIST ---------------------------------------- TOTAL_CUSTOMER REGION WAREHOUSE TOTAL_MARKET MARKET_SEGMENT ACCOUNT SHIP_TO ---- Levels in each hierarchy from leaf to highest EXECUTE dbms_aw.execute('REPORT W 20 customer_hier_levels'); CUSTOMER_HIERL IST CUSTOMER_HIER_LEVELS -------------- -------------------- SHIPMENTS SHIP_TO WAREHOUSE REGION TOTAL_CUSTOMER MARKET_SEGMENT SHIP_TO ACCOUNT MARKET_SEGMENT TOTAL_MARKET ---- Parent relation showing parent-child relationships in the Customer dimension ---- Only show the last 20 members EXECUTE dbms_aw.execute('LIMIT customer TO LAST 20'); EXECUTE dbms_aw.execute('REPORT W 10 DOWN customer W 20 customer_parentrel'); -----------CUSTOMER_PARENTREL------------ ------------CUSTOMER_HIERLIST------------ CUSTOMER MARKET_ROLLUP SHIPMENTS_ROLLUP ---------- -------------------- -------------------- 103 44 21 104 45 21 105 45 21 106 45 21 7 NA NA 1 NA NA 8 NA 1 9 NA 1 10 NA 1 11 NA 8 12 NA 10 13 NA 9 14 NA 9 15 NA 8 16 NA 9 17 NA 8 18 NA 8 19 NA 9 20 NA 9 21 NA 10 ---- Show text descriptions for the same twenty dimension members EXECUTE dbms_aw.execute('REPORT W 15 DOWN customer W 35 ACROSS customer_hierlist: <customer_short_description>'); ALL_LANGUAGES: AMERICAN_AMERICA ---------------------------CUSTOMER_HIERLIST--------------------------- -----------MARKET_ROLLUP----------- ---------SHIPMENTS_ROLLUP---------- CUSTOMER CUSTOMER_SHORT_DESCRIPTION CUSTOMER_SHORT_DESCRIPTION --------------- ----------------------------------- ----------------------------------- 103 US Marine Svcs Washington US Marine Svcs Washington 104 Warren Systems New York Warren Systems New York 105 Warren Systems Philladelphia Warren Systems Philladelphia 106 Warren Systems Boston Warren Systems Boston 7 Total Market NA 1 NA All Customers 8 NA Asia Pacific 9 NA Europe 10 NA North America 11 NA Australia 12 NA Canada 13 NA France 14 NA Germany 15 NA Hong Kong 16 NA Italy 17 NA Japan 18 NA Singapore 19 NA Spain 20 NA United Kingdom 21 NA United States
Example B-2 ADVISE_REL: Suggested Preaggregation of the Customer Dimension
This example uses the GLOBAL Customer dimension described in Sample Dimension: Customer in the Global Analytic Workspace.
The following PL/SQL statements assume that you want to preaggregate 25% of the Customer dimension. ADVISE_REL returns the suggested set of members in a valueset.
SET serveroutput ON
EXECUTE dbms_aw.execute('AW ATTACH global_aw.global');
EXECUTE dbms_aw.execute('DEFINE customer_preagg VALUESET customer');
EXECUTE dbms_aw.advise_rel('customer_parentrel', 'customer_preagg', 25);
EXECUTE dbms_aw.execute('SHOW VALUES(customer_preagg)');
31
2
4
5
6
7
1
8
9
20
21
The returned Customer members with their text descriptions, related levels, and related hierarchies, are shown as follows.
| Customer Member | Description | Hierarchy | Level |
|---|---|---|---|
31 |
Kosh Enterprises |
MARKET_ROLLUP |
ACCOUNT |
2 |
Consulting |
MARKET_ROLLUP |
MARKET_SEGMENT |
4 |
Government |
MARKET_ROLLUP |
MARKET_SEGMENT |
5 |
Manufacturing |
MARKET_ROLLUP |
MARKET_SEGMENT |
6 |
Reseller |
MARKET_ROLLUP |
MARKET_SEGMENT |
7 |
TOTAL_MARKET |
MARKET_ROLLUP |
TOTAL_MARKET |
1 |
TOTAL_CUSTOMER |
SHIPMENTS_ROLLUP |
TOTAL_CUSTOMER |
8 |
Asia Pacific |
SHIPMENTS_ROLLUP |
REGION |
9 |
Europe |
SHIPMENTS_ROLLUP |
REGION |
20 |
United Kingdom |
SHIPMENTS_ROLLUP |
WAREHOUSE |
21 |
United States |
SHIPMENTS_ROLLUP |
WAREHOUSE |
The following table describes the subprograms provided in DBMS_AW.
| Subprogram | Description |
|---|---|
|
Populates a table type named |
|
|
Suggests how to preaggregate a cube, based on a specified percentage of the cube's data. |
|
|
Returns a recommended composite definition for the cube and a recommended dimension order. |
|
|
Generates the OLAP DML commands for defining the recommended composite and measures in a cube. |
|
|
Identifies the dimension that the Sparsity Advisor partitioned over. |
|
|
Returns the level used by the Sparsity Advisor for partitioning over a dimension. |
|
|
Suggests how to preaggregate a dimension, based on a specified percentage of the dimension's members. |
|
|
Analyzes a fact table for sparsity and populates a table with the results of its analysis. |
|
|
Attaches an analytic workspace to a session. |
|
|
Creates a new analytic workspace and populates it with the object definitions and data from another analytic workspace. |
|
|
Creates a new, empty analytic workspace. |
|
|
Deletes an analytic workspace |
|
|
Detaches an analytic workspace from a session. |
|
|
Changes the name of an analytic workspace. |
|
|
Returns the name of the tablespace in which a particular analytic workspace is stored. |
|
|
Saves changes made to an analytic workspace. |
|
|
Converts an analytic workspace from 9i to 10g storage format. |
|
|
Returns the result of a numeric expression in an analytic workspace. |
|
|
Returns the result of a text expression in an analytic workspace. |
|
|
Executes one or more OLAP DML commands. Input and output is limited to 4K. Typically used in an interactive session using an analytic workspace. |
|
|
Returns the session log from the last execution of the |
|
|
Executes the OLAP DML commands specified in a file. |
|
|
Executes one or more OLAP DML commands. Input is limited to 4K and output to 4G. Typically used in applications when the 4K limit on output for the |
|
|
Executes one or more OLAP DML commands. Input and output are limited to 4G. Typically used in applications when the 4K input limit of the |
|
|
Executes one or more OLAP DML commands and suppresses the output. Input is limited to 4K and output to 4G. |
|
|
Returns a boolean indicating whether or not the OLAP option is installed in the database. |
|
|
Returns a boolean indicating whether or not the OLAP option has been initialized in the current session. |
|
|
Prints a session log returned by the |
|
|
Executes one or more OLAP DML commands. |
|
|
Shuts down the current OLAP session. |
|
|
Creates a table which the |
|
|
Starts an OLAP session without attaching a user-defined analytic workspace. |
The ADD_DIMENSION_SOURCE procedure populates a table type named DBMS_AW$_DIMENSION_SOURCES_T with information about the dimensions of a cube. This information is analyzed by the ADVISE_SPARSITY procedure.
See Also:
"Using the Sparsity Advisor"Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.
ADD_DIMENSION_SOURCE (
dimname IN VARCHAR2,
colname IN VARCHAR2,
sources IN OUT dbms_aw$_dimension_sources_t,
srcval IN VARCHAR2 DEFAULT NULL,
dimtype IN NUMBER DEFAULT NO_HIER,
hiercols IN columnlist_t DEFAULT NULL,
partby IN NUMBER DEFAULT PARTBY_DEFAULT);
Table B-2 ADD_DIMENSION_SOURCE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
A name for the dimension. For clarity, use the logical name of the dimension in the analytic workspace. |
|
|
The name of the column in the fact table that maps to the dimension members for dimname. |
|
|
The name of an object (such as a PL/SQL variable) defined with a data type of |
|
|
The name of a dimension table, or a SQL statement that returns the columns that define the dimension. If this parameter is omitted, then colname is used. |
|
|
One of the following hierarchy types: DBMS_AW.HIER_LEVELS Level-based hierarchyDBMS_AW.HIER_PARENTCHILD Parent-child hierarchyDBMS_AW.MEASURE Measure dimensionDBMS_AW.NO_HIER No hierarchy |
|
|
The names of the columns that define a hierarchy. For level-based hierarchies, list the base-level column first and the topmost-level column last. If the dimension has multiple hierarchies, choose the one you predict will be used the most frequently; only list the columns that define the levels of this one hierarchy. For parent-child hierarchies, list the child column first, then the parent column. For measure dimensions, list the columns in the fact table that becomes dimension members. |
|
|
A keyword that controls partitioning. Use one of the following values:
|
The following PL/SQL program fragment provides information about the TIME dimension for use by the Sparsity Advisor. The source data for the dimension is stored in a dimension table named TIME_DIM. Its primary key is named MONTH_ID, and the foreign key column in the fact table is also named MONTH_ID. The dimension hierarchy is level based as defined by the columns MONTH_ID, QUARTER_ID, and YEAR_ID.
The program declares a PL/SQL variable named DIMSOURCES with a table type of DBMS_AW$_DIMENSION_SOURCES_T to store the information.
DECLARE
dimsources dbms_aw$_dimension_sources_t;
BEGIN
dbms_aw.add_dimension_source('time', 'month_id', dimsources,
'time_dim', dbms_aw.hier_levels,
dbms_aw$_columnlist_t('month_id', 'quarter_id', 'year_id'));
.
.
.
END;
/
The ADVISE_CUBE procedure helps you determine how to preaggregate a cube in an analytic workspace. When you specify a percentage of the cube's data to preaggregate, ADVISE_CUBE recommends a set of members to preaggregate from each of the cube's dimensions.
The ADVISE_CUBE procedure takes an aggmap and a precompute percentage as input. The aggmap must have a precompute clause in each of its RELATION statements. The precompute clause must consist of a valueset. Based on the precompute percentage that you specify, ADVISE_CUBE returns a set of dimension members in each valueset.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.See Also:
"Using the Aggregate Advisor"
ADVISE_CUBE (
aggmap_name IN VARCHAR2,
precompute_percentage IN INTEGER DEFAULT 20,
compressed IN BOOLEAN DEFAULT FALSE);
Table B-3 ADVISE_CUBE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of an aggmap associated with the cube. Each |
|
|
A percentage of the cube's data to preaggregate. The default is 20%. |
|
|
Controls whether the advice is for a regular composite ( |
This example illustrates the ADVISE_CUBE procedure with a cube called UNITS dimensioned by PRODUCT and TIME. ADVISE_CUBE returns the dimension combinations to include if you want to preaggregate 40% of the cube's data.
SET SERVEROUTPUT ON
--- View valuesets
EXECUTE dbms_aw.execute('describe prodvals');
DEFINE PRODVALS VALUESET PRODUCT
EXECUTE dbms_aw.execute('describe timevals');
DEFINE TIMEVALS VALUESET TIME
--- View aggmap
EXECUTE dbms_aw.execute ('describe units_agg');
DEFINE UNITS_AGG AGGMAP
RELATION product_parentrel PRECOMPUTE (prodvals)
RELATION time_parentrel PRECOMPUTE (timevals)
EXECUTE dbms_aw.advise_cube ('units_agg', 40);
---- The results are returned in the prodvals and timevals valuesets
The ADVISE_DIMENSIONALITY function returns an OLAP DML definition of a composite dimension and the dimension order for variables in the cube, based on the sparsity recommendations generated by the ADVISE_SPARSITY procedure for a particular partition.
Note:
You cannot execute this function from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.See Also:
"Using the Sparsity Advisor"
ADVISE_DIMENSIONALITY (
cubename IN VARCHAR2,
sparsedfn OUT VARCHAR2
sparsename IN VARCHAR2 DEFAULT NULL,
partnum IN NUMBER DEFAULT 1,
advtable IN VARCHAR2 DEFAULT NULL)
RETURN VARCHAR2;
Table B-4 ADVISE_DIMENSIONALITY Function Parameters
| Parameter | Description |
|---|---|
|
|
The same cubename value provided in the call to |
|
|
The name of an object (such as a PL/SQL variable) in which the definition of the composite dimension is stored. |
|
|
An object name for the composite. The default value is |
|
|
The number of a partition. By default, you see only the definition of the first partition. |
|
|
The name of a table created by the |
The following PL/SQL program fragment defines two variables to store the recommendations returned by the ADVISE_DIMENSIONALITY function. SPARSEDIM stores the definition of the recommended composite, and DIMLIST stores the recommended dimension order of the cube.
DECLARE
sparsedim VARCHAR2(500);
dimlist VARCHAR2(500);
BEGIN
-- Calls to ADD_DIMENSION_SOURCE and ADVISE_SPARSITY omitted here
.
.
.
dimlist := dbms_aw.advise_dimensionality('units_cube', sparsedim);
dbms_output.put_line('Sparse dimension: ' || sparsedim);
dbms_output.put_line('Dimension list: ' || dimlist);
END;
/
The program uses DBMS_OUTPUT.PUT_LINE to display the results of the analysis. The Sparsity Advisor recommends a composite dimension for the sparse dimensions, which are PRODUCT, CUSTOMER, and TIME. The recommended dimension order for UNITS_CUBE is CHANNEL followed by this composite.
Sparse dimension: DEFINE units_cube.cp COMPOSITE <product customer time> Dimension list: channel units_cube.cp<product customer time>
The next example uses the Sparsity Advisor to evaluate the SALES table in the Sales History sample schema. A WHILE loop displays the recommendations for all partitions.
DECLARE
dimlist VARCHAR2(500);
sparsedim VARCHAR2(500);
counter NUMBER(2) := 1;
maxpart NUMBER(2);
BEGIN
-- Calls to ADD_DIMENSION_SOURCE and ADVISE_SPARSITY omitted here
.
.
.
SELECT MAX(partnum) INTO maxpart FROM sh_sparsity_advice;
WHILE counter <= maxpart LOOP
dimlist := dbms_aw.advise_dimensionality('sales_cube', sparsedim,
'sales_cube_composite', counter, 'sh_sparsity_advice');
dbms_output.put_line('Dimension list: ' || dimlist);
dbms_output.put_line('Sparse dimension: ' || sparsedim);
counter := counter+1;
END LOOP;
dbms_aw.advise_dimensionality(defs,'sales_cube', 'sales_cube_composite',
'DECIMAL', 'sh_sparsity_advice');
dbms_output.put_line('Definitions: ');
dbms_aw.printlog(defs);
END;
/
The Sparsity Advisor recommends 11 partitions; the first ten use the same composite. The last partition uses a different composite. (The SH_SPARSITY_ADVICE table shows that TIME_ID is dense in the last partition, whereas it is very sparse in the other partitions.)
Dimension list: sales_cube_composite<time channel product promotion customer>
Sparse dimension: DEFINE sales_cube_composite COMPOSITE COMPRESSED <time channel product promotion customer>
Dimension list: sales_cube_composite<time channel product promotion customer>
Sparse dimension: DEFINE sales_cube_composite COMPOSITE COMPRESSED <time channel product promotion customer>
.
.
.
Dimension list: time sales_cube_composite<channel product promotion customer>
Sparse dimension: DEFINE sales_cube_composite COMPOSITE COMPRESSED <channel product promotion customer>
The ADVISE_DIMENSIONALITY procedure evaluates the information provided by the ADVISE_SPARSITY procedure and generates the OLAP DML commands for defining a composite and a variable in the analytic workspace.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.See Also:
"Using the Sparsity Advisor"
ADVISE_DIMENSIONALITY (
output OUT CLOB,
cubename IN VARCHAR2,
sparsename IN VARCHAR2 DEFAULT NULL,
dtype IN VARCHAR2 DEFAULT 'NUMBER',
advtable IN VARCHAR2 DEFAULT NULL);
Table B-5 ADVISE_DIMENSIONALITY Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of an object (such as a PL/SQL variable) in which the recommendations of the procedure is stored. |
|
|
The same cubename value provided in the call to |
|
|
An object name for the sample composite. The default value is |
|
|
The OLAP DML data type of the sample variable. |
|
|
The name of the table created by the |
The following PL/SQL program fragment defines a variable named DEFS to store the recommended definitions.
DECLARE
defs CLOB;
BEGIN
-- Calls to ADD_DIMENSION_SOURCE and ADVISE_SPARSITY omitted here
.
.
.
dbms_aw.advise_dimensionality(defs, 'units_cube_measure_stored',
'units_cube_composite', 'DECIMAL');
dbms_output.put_line('Definitions: ');
dbms_aw.printlog(defs);
END;
/
The program uses the DBMS_OUTPUT.PUT_LINE and DBMS_AW.PRINTLOG procedures to display the recommended object definitions.
Definitions: DEFINE units_cube.cp COMPOSITE <product customer time> DEFINE units_cube NUMBER VARIABLE <channel units_cube.cp<product customer time>>
In contrast to the Global schema, which is small and dense, the Sales cube in the Sales History sample schema is large and very sparse, and the Sparsity Advisor recommends 11 partitions. The following excerpt shows some additional OLAP DML definitions for defining a partition template and moving the TIME dimension members to the various partitions.
Definitions:
DEFINE sales_cube_composite_p1 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p2 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p3 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p4 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p5 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p6 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p7 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p8 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p9 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p10 COMPOSITE COMPRESSED <time channel product promotion customer>
DEFINE sales_cube_composite_p11 COMPOSITE <channel product promotion customer>
DEFINE sales_cube_pt PARTITION TEMPLATE <time channel product promotion customer> -
PARTITION BY LIST (time) -
(PARTITION p1 VALUES () <sales_cube_composite_p1<>> -
PARTITION p2 VALUES () <sales_cube_composite_p2<>> -
PARTITION p3 VALUES () <sales_cube_composite_p3<>> -
PARTITION p4 VALUES () <sales_cube_composite_p4<>> -
PARTITION p5 VALUES () <sales_cube_composite_p5<>> -
PARTITION p6 VALUES () <sales_cube_composite_p6<>> -
PARTITION p7 VALUES () <sales_cube_composite_p7<>> -
PARTITION p8 VALUES () <sales_cube_composite_p8<>> -
PARTITION p9 VALUES () <sales_cube_composite_p9<>> -
PARTITION p10 VALUES () <sales_cube_composite_p10<>> -
PARTITION p11 VALUES () <time sales_cube_composite_p11<>>)
MAINTAIN sales_cube_pt MOVE TO PARTITION p1 -
'06-JAN-98', '07-JAN-98', '14-JAN-98', '21-JAN-98', -
'24-JAN-98', '28-JAN-98', '06-FEB-98', '07-FEB-98', -
'08-FEB-98', '16-FEB-98', '21-FEB-98', '08-MAR-98', -
'20-MAR-98', '03-JAN-98', '26-JAN-98', '27-JAN-98'
MAINTAIN sales_cube_pt MOVE TO PARTITION p1 -
'31-JAN-98', '11-FEB-98', '12-FEB-98', '13-FEB-98', -
'15-FEB-98', '17-FEB-98', '14-MAR-98', '18-MAR-98', -
'26-MAR-98', '30-MAR-98', '05-JAN-98', '08-JAN-98', -
'10-JAN-98', '16-JAN-98', '23-JAN-98', '01-FEB-98'
MAINTAIN sales_cube_pt MOVE TO PARTITION p1 -
'14-FEB-98', '28-FEB-98', '05-MAR-98', '07-MAR-98', -
'15-MAR-98', '19-MAR-98', '17-JAN-98', '18-JAN-98', -
'22-JAN-98', '25-JAN-98', '03-FEB-98', '10-FEB-98', -
'19-FEB-98', '22-FEB-98', '23-FEB-98', '26-FEB-98'
.
.
.
The ADVISE_PARTITIONING_DIMENSION function identifies the dimension that the Sparsity Advisor partitioned over, if any. It returns NULL when the Sparsity Advisor did not partition the cube.
Note:
You cannot execute this function from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.See Also:
"Using the Sparsity Advisor"
ADVISE_PARTITIONING_DIMENSION (
cubename IN VARCHAR2,
sources IN dbms_aw$_dimension_sources_t,
advtable IN VARCHAR2 DEFAULT NULL)
RETURN VARCHAR2;
Table B-6 ADVISE_PARTITIONING_DIMENSION Function Parameters
| Parameter | Description |
|---|---|
|
|
The same cubename value provided in the call to |
|
|
The name of an object (such as a PL/SQL variable) defined with a data type of |
|
|
The name of a table created by the |
The following program fragment shows the ADVISE_PARTITIONING_DIMENSION function being used to query the results after using the Sparsity Advisor.
DECLARE
dimsources dbms_aw$_dimension_sources_t;
BEGIN
-- Calls to ADD_DIMENSION_SOURCE and ADVISE_SPARSITY omitted here
.
.
.
dbms_output.put_line('Partitioning Dimension: ' ||
dbms_aw.advise_partitioning_dimension('units_cube', dimsources,
'aw_sparsity_advice'));
END;
/
The program uses DBMS_OUTPUT to display the partitioning dimension, which in this case is the TIME dimension.
Partitioning Dimension: time
The ADVISE_PARTITIONING_LEVEL function returns the level used by the Sparsity Advisor for partitioning over a dimension. It returns NULL if the Sparsity Advisor did not partition the cube, and raises an exception if the dimension hierarchy is not level-based.
Note:
You cannot execute this function from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.See Also:
"Using the Sparsity Advisor"
ADVISE_PARTITIONING_LEVEL (
cubename IN VARCHAR2,
sources IN dbms_aw$_dimension_sources_t,
advtable IN VARCHAR2 DEFAULT NULL)
RETURN VARCHAR2;
Table B-7 ADVISE_PARTITIONING_LEVEL Function Parameters
| Parameter | Description |
|---|---|
|
|
The same cubename value provided in the call to |
|
|
The name of an object (such as a PL/SQL variable) defined with a data type of |
|
|
The name of a table created by the |
The following program fragment shows the ADVISE_PARTITIONING_LEVEL function being used to query the results after using the Sparsity Advisor.
DECLARE
dimsources dbms_aw$_dimension_sources_t;
BEGIN
-- Calls to ADD_DIMENSION_SOURCE and ADVISE_SPARSITY omitted here
.
.
.
dbms_output.put_line('Partitioning Level: ' ||
dbms_aw.advise_partitioning_level('units_cube', dimsources,
'aw_sparsity_advice'));
END;
/
The program uses DBMS_OUTPUT to display the partitioning level, which in this case is YEAR.
Partitioning Level: year
The ADVISE_REL procedure helps you determine how to preaggregate a dimension in an analytic workspace. When you specify a percentage of the dimension to preaggregate, ADVISE_REL recommends a set of dimension members.
The ADVISE_REL procedure takes a family relation, a valueset, and a precompute percentage as input. The family relation is an object that specifies the hierarchical relationships between the members of a dimension. The valueset must be defined from the dimension to be analyzed. Based on the precompute percentage that you specify, ADVISE_REL returns a set of dimension members in the valueset.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.See Also:
"Using the Aggregate Advisor"
ADVISE_REL (
family_relation_name IN VARCHAR2,
valueset_name IN VARCHAR2,
precompute_percentage IN INTEGER DEFAULT 20,
compressed IN BOOLEAN DEFAULT FALSE);
Table B-8 ADVISE_REL Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of a family relation, which specifies a dimension and the hierarchical relationships between the dimension members. |
|
|
The name of a valueset to contain the results of the procedure. The valueset must be defined from the dimension in the family relation. If the valueset is not empty, |
|
|
A percentage of the dimension to preaggregate. The default is 20%. |
|
|
Controls whether the advice is for a regular composite ( |
The ADVISE_SPARSITY procedure analyzes a fact table for sparsity using information about its dimensions provided by the ADD_DIMENSION_SOURCE procedure. It populates a table created by the SPARSITY_ADVICE_TABLE procedure with the results of its analysis.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.See Also:
"Using the Sparsity Advisor"Table B-9 describes the information generated by ADVISE_SPARSITY.
Table B-9 Output Column Descriptions
| Column | Data Type | NULL | Description |
|---|---|---|---|
|
|
|
|
The values of cubename in calls to |
|
|
|
|
The values of fact in calls to |
|
|
|
|
The logical names of the cube's dimensions; the dimensions described in calls to |
|
|
|
The names of dimension columns in fact (the source fact table), which relate to a dimension table. |
|
|
|
|
The names of the dimension tables. |
|
|
|
|
The total number of dimension members at all levels. |
|
|
|
|
The number of dimension members at the leaf (or least aggregate) level. |
|
|
|
|
|
The sparsity evaluation of the dimension: |
|
|
|
|
The recommended order of the dimensions. |
|
|
|
A number that provides an indication of sparsity relative to the other dimensions. The larger the number, the more sparse the dimension. |
|
|
|
|
|
The number of the partition described in the |
|
|
|
A list of all dimension members that should be stored in this partition. This list is truncated in SQL*Plus unless you significantly increase the size of the |
|
|
|
|
A list of top-level dimension members for this partition. |
ADVISE_SPARSITY (
fact IN VARCHAR2,
cubename IN VARCHAR2,
dimsources IN dbms_aw$_dimension_sources_t,
advmode IN BINARY_INTEGER DEFAULT ADVICE_DEFAULT,
partby IN BINARY_INTEGER DEFAULT PARTBY_DEFAULT,
advtable IN VARCHAR2 DEFAULT NULL);
Table B-10 ADVISE_SPARSITY Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of the source fact table. |
|
|
A name for the facts being analyzed, such as the name of the logical cube in the analytic workspace. |
|
|
The name of the object type where the |
|
|
The level of advise you want to see. Select one of the following values: DBMS_AW.ADVICE_DEFAULTDBMS_AW.ADVICE_FASTDBMS_AW.ADVICE_FULL |
|
|
A keyword that controls partitioning. Use one of the following values:
|
|
|
The name of a table created by the procedure for storing the results of analysis. |
The following PL/SQL program fragment analyzes the sparsity characteristics of the UNITS_HISTORY_FACT table.
DECLARE
dimsources dbms_aw$_dimension_sources_t;
BEGIN
-- Calls to ADD_DIMENSION_SOURCE for each dimension in the cube
.
.
.
dbms_aw.advise_sparsity('units_history_fact', 'units_cube', dimsources,
dbms_aw.advice_default);
END;
/
The following SELECT command displays the results of the analysis, which indicate that there is one denser dimension (CHANNEL) and three comparatively sparse dimensions (PRODUCT, CUSTOMER, and TIME).
SELECT fact, dimension, dimcolumn, membercount nmem, leafcount nleaf, advice, density
FROM aw_sparsity_advice
WHERE cubename='units_cube';
FACT DIMENSION DIMCOLUMN NMEM NLEAF ADVICE DENSITY
-------------------- ------------ ------------ ----- ------ ------------ ----------
units_history_fact channel channel_id 3 3 DENSE .86545382
units_history_fact product item_id 36 36 SPARSE .98706809
units_history_fact customer ship_to_id 61 62 SPARSE .99257713
units_history_fact time month_id 96 80 SPARSE .99415964
The AW_ATTACH procedure attaches an analytic workspace to your SQL session so that you can access its contents. The analytic workspace remains attached until you explicitly detach it, or you end your session.
AW_ATTACH can also be used to create an analytic workspace, but the AW_CREATE procedure is provided specifically for that purpose.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.See Also:
"Managing Analytic Workspaces"
AW_ATTACH (
awname IN VARCHAR2,
forwrite IN BOOLEAN DEFAULT FALSE,
createaw IN BOOLEAN DEFAULT FALSE,
attargs IN VARCHAR2 DEFAULT NULL,
tablespace IN VARCHAR2 DEFAULT NULL);
AW_ATTACH (
schema IN VARCHAR2,
awname IN VARCHAR2,
forwrite IN BOOLEAN DEFAULT FALSE,
createaw IN BOOLEAN DEFAULT FALSE,
attargs IN VARCHAR2 DEFAULT NULL,
tablespace IN VARCHAR2 DEFAULT NULL);
Table B-11 AW_ATTACH Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The schema that owns awname. |
|
|
The name of an existing analytic workspace, unless createaw is specified as |
|
|
|
|
|
|
|
|
Keywords for attaching an analytic workspace, such as |
The following commands create an analytic workspace named GLOBAL_TRACKING and copies the contents of GLOBAL into it. The workspace is stored in a table named AW$GLOBAL_TRACKING, which has three partitions and is stored in the user's default tablespace.
EXECUTE dbms_aw.aw_attach('global');
EXECUTE dbms_aw.aw_copy('global', 'global_tracking', NULL, 3);
The AW_COPY procedure copies the object definitions and data from one analytic workspace into a new analytic workspace.
AW_COPY detaches the original workspace and attaches the new workspace first with read/write access.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.See Also:
"Managing Analytic Workspaces"
AW_COPY (
oldname IN VARCHAR2,
newname IN VARCHAR2,
tablespace IN VARCHAR2 DEFAULT NULL,
partnum IN NUMBER DEFAULT 8);
Table B-12 AW_COPY Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of an existing analytic workspace that contains object definitions. The workspace cannot be empty. |
|
|
A name for the new analytic workspace that is a copy of oldname. |
|
|
The name of a tablespace in which newname is stored. If this parameter is omitted, then the analytic workspace is created in the user's default tablespace. |
|
|
The number of partitions that are created for the |
The following commands create an analytic workspace named GLOBAL_TRACKING and copies the contents of GLOBAL into it. The workspace is stored in a table named AW$GLOBAL_TRACKING, which has three partitions and is stored in the user's default tablespace.
EXECUTE dbms_aw.aw_attach('global');
EXECUTE dbms_aw.aw_copy('global', 'global_tracking', NULL, 3);
The AW_CREATE procedure creates a new, empty analytic workspace and makes it the current workspace in your session.
The current workspace is first in the list of attached workspaces.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.
AW_CREATE (
awname IN VARCHAR2 ,
tablespace IN VARCHAR2 DEFAULT NULL ,
partnum IN NUMBER DEFAULT 8 );
AW_CREATE (
schema IN VARCHAR2 ,
awname IN VARCHAR2 ,
tablespace IN VARCHAR2 DEFAULT NULL);
Table B-13 AW_CREATE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The schema that owns awname. |
|
|
The name of a new analytic workspace. The name must comply with the naming requirements for a table in Oracle Database. This procedure creates a table named AW$awname, in which the analytic workspace is stored. |
|
|
The tablespace in which the analytic workspace is created. If you omit this parameter, the analytic workspace is created in your default tablespace. |
|
|
The number of partitions that are created for the |
The following command creates a new, empty analytic workspace named GLOBAL_FINANCE. The new analytic workspace is stored in a table named AW$GLOBAL_FINANCE with eight partitions in the user's default tablespace.
EXECUTE dbms_aw.aw_create('global_finance');
The next command creates an analytic workspace named DEMO in the GLOBAL schema. AW$DEMO has two partitions and is stored in the GLOBAL tablespace.
EXECUTE dbms_aw.aw_create('global.demo', 'global', 2);
The AW_DELETE procedure deletes an existing analytic workspace.
Table B-14 AW_DELETE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The schema that owns awname. |
|
|
The name of an existing analytic workspace that you want to delete along with all of its contents. You must be the owner of awname or have DBA rights to delete it, and it cannot currently be attached to your session. The AW$awname file is deleted from the database. |
The AW_DETACH procedure detaches an analytic workspace from your session so that its contents are no longer accessible. All changes that you have made since the last update are discarded. Refer to "AW_UPDATE Procedure" for information about saving changes to an analytic workspace.
The AW_RENAME procedure changes the name of an analytic workspace.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.The AW_TABLESPACE function returns the name of the tablespace in which a particular analytic workspace is stored.
Note:
You cannot execute this function from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.
AW_TABLESPACE (
schema IN VARCHAR2,
awname IN VARCHAR2)
RETURN VARCHAR2;
The following example shows the tablespace in which the GLOBAL analytic workspace is stored.
SET serveroutput ON
EXECUTE dbms_output.put_line('Sales History is stored in tablespace ' ||
dbms_aw.aw_tablespace('sh_aw', 'sales_history'));
This command generates the following statement:
Sales History is stored in tablespace SH_AW
The AW_UPDATE procedure saves the changes made to an analytic workspace in its permanent database table. For the updated version of this table to be saved in the database, you must issue a SQL COMMIT statement before ending your session.
If you do not specify an analytic workspace to update, AW_UPDATE updates all the user-defined workspaces that are currently attached with read/write access.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.See Also:
"Managing Analytic Workspaces"
AW_UPDATE (
awname IN VARCHAR2 DEFAULT NULL);
AW_UPDATE (
schema IN VARCHAR2 DEFAULT NULL,
awname IN VARCHAR2 DEFAULT NULL);
The CONVERT procedure converts an analytic workspace in 9i storage format to to 10g storage format. Note that you cannot execute this procedure from within the OLAP Worksheet; you must execute it in a SQL tool such as SQL*Plus.
Note:
Issuing thedbms_aw.convert procedure is only one small step in upgrading Oracle 9i analytic workspaces to Oracle 10g workspaces. For the complete procedure for upgrading Oracle 9i analytic workspaces, see Oracle OLAP Application Developer's Guide, 10g Release 2 (10.2).See Also:
Oracle OLAP User's Guide for information on converting an analytic workspace to Oracle 11g storage format
CONVERT (
original_aw IN VARCHAR2);
CONVERT (
original_aw IN VARCHAR2,
converted_aw IN VARCHAR2,
tablespace IN NUMBER DEFAULT);
Table B-19 CONVERT Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The analytic workspace you want to convert. |
|
|
The converted analytic workspace. |
|
|
The name of a tablespace in which the converted workspace is stored. If this parameter is omitted, then the analytic workspace is created in the user's default tablespace. |
This example performs the conversion in a single step, using the analytic workspace as both the source and the target of the conversion.
EXECUTE dbms_aw.convert('global');
The next example performs the conversion in several steps. The converted workspace must have the same name as the original workspace, because the fully qualified names of objects in the workspace include the workspace name.
EXECUTE dbms_aw.rename('global', 'global_temp');
EXECUTE dbms_aw.convert('global_temp', 'global');
EXECUTE dbms_aw.delete('global_temp');
The EVAL_NUMBER function evaluates a numeric expression in an analytic workspace and returns the resulting number.
You can specify the EVAL_NUMBER function in a SELECT from DUAL statement to return a numeric constant defined in an analytic workspace. For more information, see "Selecting from the DUAL Table" in Oracle Database SQL Language Reference.
Note:
You cannot execute this function from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.Table B-20 EVAL_NUMBER Function Parameters
| Parameter | Description |
|---|---|
|
|
An OLAP DML expression that evaluates to a number. Refer to Chapter 2, "OLAP DML Expressions". |
The following example returns the value of the DECIMALS option in the current analytic workspace. The DECIMALS option controls the number of decimal places that are shown in numeric output. In this example, the value of DECIMALS is 2, which is the default.
SET serveroutput ON
SELECT dbms_aw.eval_number('decimals') "Decimals" FROM dual;
Decimals
----------
2
The EVAL_TEXT function evaluates a text expression in an analytic workspace and returns the resulting character string.
You can specify the EVAL_TEXT function in a SELECT from DUAL statement to return a character constant defined in an analytic workspace. For more information, see "Selecting from the DUAL Table" in Oracle Database SQL Language Reference.
Note:
You cannot execute this function from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.Table B-21 EVAL_TEXT Function Parameters
| Parameter | Description |
|---|---|
|
|
An OLAP DML expression that evaluates to a character string. Refer to Chapter 2, "OLAP DML Expressions". |
The following example returns the value of the NLS_LANGUAGE option, which specifies the current language of the session.
SET serveroutput ON
SELECT dbms_aw.eval_text('nls_language') "NLS Language" FROM dual;
The value of NLS_LANGUAGE in this example is AMERICAN.
NLS Language --------------- AMERICAN
The EXECUTE procedure executes one or more OLAP DML commands and directs the output to a printer buffer. It is typically used to manipulate analytic workspace data within an interactive SQL session. In contrast to the RUN Procedure, EXECUTE continues to process commands after it gets an error.
When you are using SQL*Plus, you can direct the printer buffer to the screen by issuing the following command:
SET SERVEROUT ON
If you are using a different program, refer to its documentation for the equivalent setting.
Input and output is limited to 4K. For larger values, refer to the INTERP and INTERPCLOB functions in this package.
This procedure does not print the output of the DML commands when you have redirected the output by using the OLAP DML OUTFILE command.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.Table B-22 EXECUTE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
One or more OLAP DML commands separated by semicolons. See "Guidelines for Using Quotation Marks in OLAP DML Commands". |
|
|
Output from the OLAP engine in response to the OLAP commands. |
The following example attaches the GLOBAL analytic workspace and shows the object definition of TIME.
EXECUTE dbms_aw.aw_attach('global'); EXECUTE dbms_aw.execute('DESCRIBE time'); DEFINE TIME DIMENSION TEXT
The next example shows how EXECUTE continues to process commands after encountering an error:
EXECUTE dbms_aw.execute('SHOW DECIMALS'); 2 EXECUTE dbms_aw.execute('CALL nothing; DECIMALS=0'); BEGIN dbms_aw.execute('CALL nothing; DECIMALS=0'); END; * ERROR at line 1: ORA-34492: Analytic workspace object NOTHING does not exist. ORA-06512: at "SYS.DBMS_AW", line 93 ORA-06512: at "SYS.DBMS_AW", line 122 ORA-06512: at line 1 EXECUTE dbms_aw.execute('SHOW DECIMALS'); 0
The next example show how EXECUTE continues to process commands after encountering an error:
SQL> execute dbms_aw.execute('call nothing; colwidth=20');
BEGIN dbms_aw.execute('call nothing; colwidth=20'); END;
*
ERROR at line 1:
ORA-34492: Analytic workspace object NOTHING does not exist.
ORA-06512: at "SYS.DBMS_AW", line 90
ORA-06512: at "SYS.DBMS_AW", line 119
ORA-06512: at line 1
SQL> execute dbms_aw.execute('show colwidth');
20
PL/SQL procedure successfully completed.
This function returns the session log from the last execution of the INTERP or INTERPCLOB functions in this package.
To print the session log returned by this function, use the DBMS_AW.PRINTLOG procedure.
Note:
You cannot execute this function from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.The following example shows the session log returned by a call to INTERP, then shows the identical session log returned by GETLOG.
EXECUTE dbms_aw.printlog(dbms_aw.interp('AW ATTACH global; REPORT units_cube')); UNITS_CUBE -------------- TIME CUSTOMER PRODUCT CHANNEL EXECUTE dbms_aw.printlog(dbms_aw.getlog()); UNITS_CUBE -------------- TIME CUSTOMER PRODUCT CHANNEL
The INFILE procedure evaluates the OLAP DML commands in the specified file and executes them in the current analytic workspace.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.The INTERP function executes one or more OLAP DML commands and returns the session log in which the commands are executed. It is typically used in applications when the 4K limit on output for the EXECUTE procedure may be too restrictive.
Input to the INTERP function is limited to 4K. For larger input values, refer to the INTERPCLOB function of this package.
This function does not return the output of the DML commands when you have redirected the output by using the OLAP DML OUTFILE command.
You can use the INTERP function as an argument to the PRINTLOG procedure in this package to view the session log. See the example.
Note:
You cannot execute this function from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.Table B-24 INTERP Function Parameters
| Parameter | Description |
|---|---|
|
|
One or more OLAP DML commands separated by semi-colons. See "Guidelines for Using Quotation Marks in OLAP DML Commands". |
The INTERPCLOB function executes one or more OLAP DML commands and returns the session log in which the commands are executed. It is typically used in applications when the 4K limit on input for the INTERP function may be too restrictive.
This function does not return the output of the OLAP DML commands when you have redirected the output by using the OLAP DML OUTFILE command.
You can use the INTERPCLOB function as an argument to the PRINTLOG procedure in this package to view the session log. See the example.
Table B-25 INTERPCLOB Function Parameters
| Parameter | Description |
|---|---|
|
|
One or more OLAP DML commands separated by semi-colons. See "Guidelines for Using Quotation Marks in OLAP DML Commands". |
The following sample SQL*Plus session creates an analytic workspace named ELECTRONICS, imports its contents from an EIF file stored in the dbs directory object, and displays the contents of the analytic workspace.
SET serverout ON size 1000000 EXECUTE dbms_aw.printlog(dbms_aw.interpclob('AW ATTACH global; DESCRIBE')); DEFINE GEN_OBJ_ROLES DIMENSION TEXT DEFINE GEN_AW_OBJS VARIABLE TEXT <GEN_OBJ_ROLES> DEFINE ALL_DIMENSIONS DIMENSION TEXT DEFINE DIM_OBJ_LIST DIMENSION TEXT DEFINE DIM_AW_OBJS VARIABLE TEXT <ALL_DIMENSIONS DIM_OBJ_LIST> . . .
The INTERP_SILENT procedure executes one or more OLAP DML commands and suppresses all output from them. It does not suppress error messages from the OLAP command interpreter.
Input to the INTERP_SILENT function is limited to 4K. To display the output of the OLAP DML commands, use the EXECUTE procedure, or the INTERP or INTERPCLOB functions.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.Table B-26 INTERP_SILENT Function Parameters
| Parameter | Description |
|---|---|
|
|
One or more OLAP DML commands separated by semi-colons. See "Guidelines for Using Quotation Marks in OLAP DML Commands". |
The following commands show the difference in message handling between EXECUTE and INTERP_SILENT. Both commands attach the GLOBAL analytic workspace in read-only mode. However, EXECUTE displays a warning message, while INTERP_SILENT does not.
EXECUTE dbms_aw.execute('AW ATTACH global'); IMPORTANT: Analytic workspace GLOBAL is read-only. Therefore, you will not be able to use the UPDATE command to save changes to it. EXECUTE dbms_aw.interp_silent('AW ATTACH global');
The OLAP_ON function returns a boolean indicating whether or not the OLAP option is installed in the database.
Note:
You cannot execute this function from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.The OLAP_RUNNING function returns a boolean indicating whether or not the OLAP option has been initialized in the current session. Initialization occurs when you execute an OLAP DML command (either directly or by using an OLAP PL/SQL or Java package), query an analytic workspace, or execute the STARTUP Procedure.
Note:
You cannot execute this function from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.The following PL/SQL script tests whether the OLAP environment has been initialized, and starts it if not.
BEGIN
IF dbms_aw.olap_running() THEN
dbms_output.put_line('OLAP is already running');
ELSE
dbms_aw.startup;
IF dbms_aw.olap_running() THEN
dbms_output.put_line('OLAP started successfully');
ELSE
dbms_output.put_line('OLAP did not start. Is it installed?');
END IF;
END IF;
END;
/
OLAP started successfully
This procedure sends a session log returned by the INTERP, INTERPCLOB, or GETLOG functions of this package to the print buffer, using the DBMS_OUTPUT package in PL/SQL.
When you are using SQL*Plus, you can direct the printer buffer to the screen by issuing the following command:
SET SERVEROUT ON SIZE 1000000
The SIZE clause increases the buffer from its default size of 4K.
If you are using a different program, refer to its documentation for the equivalent setting.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.The RUN procedure executes one or more OLAP DML commands and directs the output to a printer buffer. It is typically used to manipulate analytic workspace data within an interactive SQL session. In contrast to the EXECUTE Procedure, RUN stops processing commands when it gets an error.
When you are using SQL*Plus, you can direct the printer buffer to the screen by issuing the following command:
SET SERVEROUT ON
If you are using a different program, refer to its documentation for the equivalent setting.
This procedure does not print the output of the DML commands when you have redirected the output by using the OLAP DML OUTFILE command.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.
RUN (
olap_commands IN STRING,
silent IN BOOLEAN DEFAULT FALSE);
RUN (
olap_commands IN CLOB,
silent IN BOOLEAN DEFAULT FALSE);
RUN (
olap_commands IN STRING,
output OUT STRING);
RUN (
olap_commands IN STRING,
output IN OUT CLOB);
RUN (
olap_commands IN CLOB,
output OUT STRING);
RUN (
olap_commands IN CLOB,
output IN OUT CLOB);
Table B-28 EXECUTE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
One or more OLAP DML commands separated by semicolons. See "Guidelines for Using Quotation Marks in OLAP DML Commands". |
|
|
A boolean value that signals whether the output from the OLAP DML commands should be suppressed. (Error messages from the OLAP engine are never suppressed, regardless of this setting.) |
|
|
Output from the OLAP engine in response to the OLAP commands. |
The following sample SQL*Plus session attaches an analytic workspace named XADEMO, creates a formula named COST_PP in XADEMO, and displays the new formula definition.
EXECUTE dbms_aw.run('DESCRIBE time');
DEFINE TIME DIMENSION TEXT
The next example shows how RUN stops executing commands after encountering an error.
EXECUTE dbms_aw.run('SHOW DECIMALS'); 0 EXECUTE dbms_aw.run('CALL nothing; DECIMALS=4'); BEGIN dbms_aw.run('CALL nothing; DECIMALS=4'); END; * ERROR at line 1: ORA-34492: Analytic workspace object NOTHING does not exist. ORA-06512: at "SYS.DBMS_AW", line 58 ORA-06512: at "SYS.DBMS_AW", line 134 ORA-06512: at line 1 EXECUTE dbms_aw.run('SHOW DECIMALS'); 0
The SHUTDOWN procedure terminates the current OLAP session.
By default, the SHUTDOWN procedure terminates the session only if there are no outstanding changes to any of the attached read/write workspaces. To terminate the session without updating the workspaces, specify the force parameter.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.The SPARSITY_ADVICE_TABLE procedure creates a table for storing the advice generated by the ADVISE_SPARSITY procedure.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.See Also:
"Using the Sparsity Advisor"Table B-30 SPARSITY_ADVICE_TABLE Procedure Parameters
| Parameter | Description |
|---|---|
|
|
The name of the table. The default name is |
The STARTUP procedure starts an OLAP session without attaching any user-defined workspaces.
STARTUP initializes the OLAP processing environment and attaches the read-only EXPRESS workspace, which contains the program code for the OLAP engine.
Note:
You cannot execute this procedure from within the OLAP Worksheet. You must execute it in a SQL tool such as SQL*Plus.