Using Materialized Views in the Oracle Database with Oracle Business Intelligence

Learn how to export metadata from Oracle Business Intelligence into the SQL Access Advisor and create materialized views using the Oracle Database Metadata Generator.

This section contains the following topics:

About Using the SQL Access Advisor with Materialized Views

The SQL Access Advisor with Materialized Views enhances the data warehouse performance and functionality of a database.

It enables the SQL Access Advisor to store metadata about the logical relationships of the data that resides in the database. Additionally, it accelerates data warehouse queries by using more efficient Oracle materialized views. These materialized views preaggregate the relational data and improve query performance. Once the metadata is stored in the SQL Access Advisor, the database administrator can optimize the database objects and improve query performance.

When processing queries, Oracle Database routes queries to tables that hold materialized views when possible. Because these tables of materialized views are smaller than the underlying base tables and the data has been pre aggregated, the queries that are rerouted to them might run faster.

Oracle Database Metadata Generator works as a metadata bridge to convert the Oracle Business Intelligence proprietary metadata into a SQL file that contains PL/SQL commands to generate dimensions in the SQL Access Advisor. After converting metadata into a SQL file, you use a tool such as SQL*Plus to import the translated metadata into the SQL Access Advisor and store it in metadata catalog tables. After importing the metadata, you create materialized views, which are used by to optimize incoming application queries.

Deploying Metadata for Oracle Database

Become familiar with the Oracle Database and its tools before attempting to deploy metadata in the Oracle Database.

See "SQL Access Advisor" in Oracle Database Performance Tuning Guide.

Ensure that you complete the steps in Running the Generator before deploying metadata. To deploy cube metadata, perform the tasks described in the following sections:

Executing the SQL File for Oracle Database

Before executing the SQL file for importing into the SQL Access Advisor, ensure that you are familiar with Oracle Database import tools. See the Oracle Database documentation set for information.

Use a tool such as SQL*Plus to execute the SQL file that the Oracle Database Metadata Generator generated. You might see error messages if the dimensions already exist or if the database schema differs from that in the RPD file. When the script executes successfully, you can see the dimensions that were created by using the database web console or the Oracle Enterprise Manager Database Control. In the Oracle Enterprise Manager Database Control, expand the following nodes: Network, Databases, database-name, Warehouse, Summary Management, Dimensions, System.

After you execute the SQL file, be aware of the following:

  • No incremental metadata changes are allowed. Schema changes require that you manually delete cube model metadata in the Oracle Database and convert the Oracle Business Intelligence metadata again. For example, if you must make a change to a dimension in a cube in the Oracle BI repository, you must delete the cube model in the Oracle Database, regenerate the SQL file from the Oracle BI repository, and import it into the SQL Access Advisor.

  • You cannot delete metadata using the Oracle Database Metadata Generator. Instead, you must manually delete the cube model using the Oracle Enterprise Manager Database Control.

Defining Constraints for the Existence of Joins

You must ensure that Oracle Database knows about the joins between the dimension tables and the fact tables.

See your Oracle Database documentation.

To do so, you create constraints in SQL*Plus or the Oracle Enterprise Manager Database Control. In the Oracle Enterprise Manager Database Control, you select the table on which you must create a constraint, then select the Constraint tab.

You create a different type of constraint for each kind of table, as follows:

  • For dimension tables, create a UNIQUE key constraint.

  • For fact tables, create a FOREIGN key constraint and specify the referenced schema and referenced table. In the Constraint Definition area, include the foreign key columns in the fact table and the corresponding unique keys in the dimension table. An attempt to create a foreign key on a fact table can fail if the foreign key column data does not match the unique key column data on the dimension table.

Creating the Query Workload

A query workload is a sample set of physical queries to optimize.

See the Oracle Database documentation set for detailed information about creating the query workload.

Before you create the workload, you generate a Trace file with information on the slowest-running queries.

You can generate the Trace file of the slowest-running queries using a tool that is appropriate to your database version, as described in the following list:

  • Usage Tracking: Use this capability in Oracle Business Intelligence to log queries and how long they take to run. Long-running Oracle Business Intelligence queries can then be executed as a script and used with the Trace feature in the Oracle Database to capture the Oracle Database SQL code for these queries.

  • Oracle Database Trace: Use this tool to identify the slowest physical query. You can enable the Trace feature either within Oracle Enterprise Manager Database Control or by entering SQL commands with the DBMS_MONITOR package. Once you enable the Trace feature, you use a script to create a Trace file to capture the SQL code for queries in a query workload table.

  • Oracle Enterprise Manager: Use this tool to track slow-running queries.

    Note:

    The capabilities that are described in the following sections are available in Oracle Database, rather than as part of Oracle Business Intelligence.

  1. Use the following guidelines when reviewing the Trace file:
    • When you have traced many statements at once, such as in batch processes, quickly discard any statements that have acceptable query execution times. Focus on those statements that take the longest times to execute.

    • Check the Query column for block visits for read consistency, including all query and subquery processing. Inefficient statements are often associated with a large number of block visits. The Current column indicates visits not related to read consistency, including segment headers and blocks that will be updated.

    • Check the Disk column for the number of blocks that were read from disk. Because disk reads are slower than memory reads, the value will likely be significantly lower than the sum of the Query and Current columns. If it is not, check for issues with the buffer cache.

    • Locking problems and inefficient PL/SQL loops can lead to high CPU time values even when the number of block visits is low.

    • Watch for multiple parse calls for a single statement, because this indicates a library cache issue.

  2. After identifying the problem statements in the file, check the execution plan to learn why each problem statement occurred.

To load queries into the workload:

  • After you use the Trace utility to learn the names of the slowest physical queries, insert them into the USER_WORKLOAD table.

    The table describes the columns of the USER_WORKLOAD table.

  • Use INSERT statements to populate the QUERY column with the SQL statements for the slowest physical queries and the OWNER column with the appropriate owner names.

Column Data Type Required Description

QUERY

Any LONG or VARCHAR type (all character types)

YES

SQL statement for the query.

OWNER

VARCHAR2 (30)

YES

User who last executed the query.

APPLICATION

VARCHAR2 (30)

NO

Application name for the query.

FREQUENCY

NUMBER

NO

Number of times that the query was executed.

LASTUSE

DATE

NO

Last date on which the query was executed.

PRIORITY

NUMBER

NO

User-supplied ranking of the query.

RESPONSETIME

NUMBER

NO

Execution time of the query in seconds.

RESULTSIZE

NUMBER

NO

Total number of bytes that the query selected.

SQL_ADDR

NUMBER

NO

Cache address of the query.

SQL_HASH

NUMBER

NO

Cache hash value of the query.

Creating Materialized Views

After you populate the query workload table, use the appropriate tool for the Oracle Database version to create materialized views.

In Oracle Database 10g, use the SQL Access Advisor in the Oracle Enterprise Manager Database Control and specify the query workload table that you created.

The SQL Access Advisor generates recommendations on improving the performance of the fact tables that you specify. The SQL Access Advisor displays the SQL code with which it will create the appropriate materialized views. Before indicating that the SQL Access Advisor should create the materialized views, review the following tips:

  • The creation of a materialized view can fail if the SQL code includes a CAST statement.

  • Ensure that the CREATE MATERIALIZED VIEW statement does not specify the same query that you provided as a workload table. If the statement does specify the same query, then the materialized views will likely not reflect the true performance gain. However, if the query is executed frequently, then creating a materialized view might still be worthwhile.

  • Add a forward slash (/) to the end of the CREATE MATERIALIZED VIEW statement after the SQL statement. Otherwise, the SQL*Plus worksheet will not recognize it as a valid statement.

    Note:

    The SQL Access Advisor can also help determine appropriate indexing schemes.