|Oracle® Database Data Warehousing Guide
10g Release 1 (10.1)
Part Number B10736-01
This chapter introduces you to the use of materialized views, and discusses:
Typically, data flows from one or more online transaction processing (OLTP) database into a data warehouse on a monthly, weekly, or daily basis. The data is normally processed in a staging file before being added to the data warehouse. Data warehouses commonly range in size from tens of gigabytes to a few terabytes. Usually, the vast majority of the data is stored in a few very large fact tables.
One technique employed in data warehouses to improve performance is the creation of summaries. Summaries are special types of aggregate views that improve query execution times by precalculating expensive joins and aggregation operations prior to execution and storing the results in a table in the database. For example, you can create a table to contain the sums of sales by region and by product.
The summaries or aggregates that are referred to in this book and in literature on data warehousing are created in Oracle Database using a schema object called a materialized view. Materialized views can perform a number of roles, such as improving query performance or providing replicated data.
In the past, organizations using summaries spent a significant amount of time and effort creating summaries manually, identifying which summaries to create, indexing the summaries, updating them, and advising their users on which ones to use. The introduction of summary management eased the workload of the database administrator and meant the user no longer needed to be aware of the summaries that had been defined. The database administrator creates one or more materialized views, which are the equivalent of a summary. The end user queries the tables and views at the detail data level. The query rewrite mechanism in the Oracle server automatically rewrites the SQL query to use the summary tables. This mechanism reduces response time for returning results from the query. Materialized views within the data warehouse are transparent to the end user or to the database application.
Although materialized views are usually accessed through the query rewrite mechanism, an end user or database application can construct queries that directly access the materialized views. However, serious consideration should be given to whether users should be allowed to do this because any change to the materialized views will affect the queries that reference them.
In data warehouses, you can use materialized views to precompute and store aggregated data such as the sum of sales. Materialized views in these environments are often referred to as summaries, because they store summarized data. They can also be used to precompute joins with or without aggregations. A materialized view eliminates the overhead associated with expensive joins and aggregations for a large or important class of queries.
In distributed environments, you can use materialized views to replicate data at distributed sites and to synchronize updates done at those sites with conflict resolution methods. The materialized views as replicas provide local access to data that otherwise would have to be accessed from remote sites. Materialized views are also useful in remote data marts. See Oracle Database Advanced Replication and Oracle Database Heterogeneous Connectivity Administrator's Guide for details on distributed and mobile computing.
You can also use materialized views to download a subset of data from central servers to mobile clients, with periodic refreshes and updates between clients and the central servers.
This chapter focuses on the use of materialized views in data warehouses. See Oracle Database Advanced Replication and Oracle Database Heterogeneous Connectivity Administrator's Guide for details on distributed and mobile computing.
You can use materialized views to increase the speed of queries on very large databases. Queries to large databases often involve joins between tables, aggregations such as
SUM, or both. These operations are expensive in terms of time and processing power. The type of materialized view you create determines how the materialized view is refreshed and used by query rewrite.
Materialized views improve query performance by precalculating expensive join and aggregation operations on the database prior to execution and storing the results in the database. The query optimizer automatically recognizes when an existing materialized view can and should be used to satisfy a request. It then transparently rewrites the request to use the materialized view. Queries go directly to the materialized view and not to the underlying detail tables. In general, rewriting queries to use materialized views rather than detail tables improves response. Figure 8-1 illustrates how query rewrite works.
Figure 8-1 Transparent Query Rewrite
When using query rewrite, create materialized views that satisfy the largest number of queries. For example, if you identify 20 queries that are commonly applied to the detail or fact tables, then you might be able to satisfy them with five or six well-written materialized views. A materialized view definition can include any number of aggregations (
MAX). It can also include any number of joins. If you are unsure of which materialized views to create, Oracle provides the SQLAccess Advisor, which is a set of advisory procedures in the
DBMS_ADVISOR package to help in designing and evaluating materialized views for query rewrite. See Chapter 17, " SQLAccess Advisor" for further details.
If a materialized view is to be used by query rewrite, it must be stored in the same database as the detail tables on which it relies. A materialized view can be partitioned, and you can define a materialized view on a partitioned table. You can also define one or more indexes on the materialized view.
Unlike indexes, materialized views can be accessed directly using a
SELECT statement. However, it is recommended that you try to avoid writing SQL statements that directly reference the materialized view, because then it is difficult to change them without affecting the application. Instead, let query rewrite transparently rewrite your query to use the materialized view.
Note that the techniques shown in this chapter illustrate how to use materialized views in data warehouses. Materialized views can also be used by Oracle Replication. See Oracle Database Advanced Replication for further information.
Mechanisms to define materialized views and dimensions.
A refresh mechanism to ensure that all materialized views contain the latest data.
A query rewrite capability to transparently rewrite a query to use a materialized view.
The SQLAccess Advisor, which recommends materialized views and indexes to create. See Chapter 17, " SQLAccess Advisor" for more information.
TUNE_MVIEW, which shows you how to make your materialized view fast refreshable and use general query rewrite.
The use of summary management features imposes no schema restrictions, and can enable some existing DSS database applications to improve performance without the need to redesign the database or the application.
Figure 8-2 illustrates the use of summary management in the warehousing cycle. After the data has been transformed, staged, and loaded into the detail data in the warehouse, you can invoke the summary management process. First, use the SQLAccess Advisor to plan how you will use materialized views. Then, create materialized views and design how queries will be rewritten. If you are having problems trying to get your materialized views to work then use
TUNE_MVIEW to obtain an optimzed materialized view.
Figure 8-2 Overview of Summary Management
Understanding the summary management process during the earliest stages of data warehouse design can yield large dividends later in the form of higher performance, lower summary administration costs, and reduced storage requirements.
Some basic data warehousing terms are defined as follows:
Dimension tables describe the business entities of an enterprise, represented as hierarchical, categorical information such as time, departments, locations, and products. Dimension tables are sometimes called lookup or reference tables.
Dimension tables usually change slowly over time and are not modified on a periodic schedule. They are used in long-running decision support queries to aggregate the data returned from the query into appropriate levels of the dimension hierarchy.
Hierarchies describe the business relationships and common access patterns in the database. An analysis of the dimensions, combined with an understanding of the typical work load, can be used to create materialized views. See Chapter 10, " Dimensions" for more information.
The vast majority of data in a data warehouse is stored in a few very large fact tables that are updated periodically with data from one or more operational OLTP databases.
A simple measure is a numeric or character column of one table such as
A computed measure is an expression involving measures of one table, for example,
A multitable measure is a computed measure defined on multiple tables, for example,
Fact tables also contain one or more foreign keys that organize the business transactions by the relevant business entities such as time, product, and market. In most cases, these foreign keys are non-null, form a unique compound key of the fact table, and each foreign key joins with exactly one row of a dimension table.
A materialized view is a precomputed table comprising aggregated and joined data from fact and possibly from dimension tables. Among builders of data warehouses, a materialized view is also known as a summary.
Summary management can perform many useful functions, including query rewrite and materialized view refresh, even if your data warehouse design does not follow these guidelines. However, you will realize significantly greater query execution performance and materialized view refresh performance benefits and you will require fewer materialized views if your schema design complies with these guidelines.
A materialized view definition includes any number of aggregates, as well as any number of joins. In several ways, a materialized view behaves like an index:
The purpose of a materialized view is to increase query execution performance.
The existence of a materialized view is transparent to SQL applications, so that a database administrator can create or drop materialized views at any time without affecting the validity of SQL applications.
A materialized view consumes storage space.
The contents of the materialized view must be updated when the underlying detail tables are modified.
In the case of normalized or partially normalized dimension tables (a dimension that is stored in more than one table), identify how these tables are joined. Note whether the joins between the dimension tables can guarantee that each child-side row joins with one and only one parent-side row. In the case of denormalized dimensions, determine whether the child-side columns uniquely determine the parent-side (or attribute) columns. These relationships can be enabled with constraints, using the
RELY options if the relationships represented by the constraints are guaranteed by other means. Note that if the joins between fact and dimension tables do not support the parent-child relationship described previously, you still gain significant performance advantages from defining the dimension with the
DIMENSION statement. Another alternative, subject to some restrictions, is to use outer joins in the materialized view definition (that is, in the
You must not create dimensions in any schema that does not satisfy these relationships. Incorrect results can be returned from queries otherwise.
Before starting to define and use the various components of summary management, you should review your schema design to abide by the following guidelines wherever possible.
Guidelines 1 and 2 are more important than guideline 3. If your schema design does not follow guidelines 1 and 2, it does not then matter whether it follows guideline 3. Guidelines 1, 2, and 3 affect both query rewrite performance and materialized view refresh performance.
Table 8-1 Schema Design Guidelines
|Dimensions should either be denormalized (each dimension contained in one table) or the joins between tables in a normalized or partially normalized dimension should guarantee that each child-side row joins with exactly one parent-side row. The benefits of maintaining this condition are described in "Creating Dimensions".
You can enforce this condition by adding
|If dimensions are denormalized or partially denormalized, hierarchical integrity must be maintained between the key columns of the dimension table. Each child key value must uniquely identify its parent key value, even if the dimension table is denormalized. Hierarchical integrity in a denormalized dimension can be verified by calling the |
|Fact and dimension tables should similarly guarantee that each fact table row joins with exactly one dimension table row. This condition must be declared, and optionally enforced, by adding |
|Incremental loads of your detail data should be done using the SQL*Loader direct-path option, or any bulk loader utility that uses Oracle's direct-path interface. This includes |
|Range/composite partition your tables by a monotonically increasing time column if possible (preferably of type |
|After each load and before refreshing your materialized view, use the |
|If a time dimension appears in the materialized view as a time column, partition and index the materialized view in the same manner as you have the fact tables.|
If you are concerned with the time required to enable constraints and whether any constraints might be violated, then use the
NOVALIDATE with the
RELY clause to turn on constraint checking without validating any of the existing constraints. The risk with this approach is that incorrect query results could occur if any constraints are broken. Therefore, as the designer, you must determine how clean the data is and whether the risk of incorrect results is too great.
A popular and efficient way to load data into a data warehouse or data mart is to use SQL*Loader with the
PARALLEL option, DataPump, or to use another loader tool that uses the Oracle direct-path API. See Oracle Database Utilities for the restrictions and considerations when using SQL*Loader with the
Loading strategies can be classified as one-phase or two-phase. In one-phase loading, data is loaded directly into the target table, quality assurance tests are performed, and errors are resolved by performing DML operations prior to refreshing materialized views. If a large number of deletions are possible, then storage utilization can be adversely affected, but temporary space requirements and load time are minimized.
In a two-phase loading process:
Data is first loaded into a temporary table in the warehouse.
Quality assurance procedures are applied to the data.
Referential integrity constraints on the target table are disabled, and the local index in the target partition is marked unusable.
The data is copied from the temporary area into the appropriate partition of the target table using
SELECT with the
APPEND hint. The temporary table is then dropped. Alternatively, if the target table is partitioned, you can create a new (empty) partition in the target table and use
ALTER TABLE ... EXCHANGE PARTITION to incorporate the temporary table into the target table. See Oracle Database SQL Reference for more information.
The constraints are enabled, usually with the
Immediately after loading the detail data and updating the indexes on the detail data, the database can be opened for operation, if desired. You can disable query rewrite at the system level by issuing an
FALSE statement until all the materialized views are refreshed.
QUERY_REWRITE_INTEGRITY is set to
STALE_TOLERATED, access to the materialized view can be allowed at the session level to any users who do not require the materialized views to reflect the data from the latest load by issuing an
TRUE statement. This scenario does not apply when
QUERY_REWRITE_INTEGRITY is either
TRUSTED because the system ensures in these modes that only materialized views with updated data participate in a query rewrite.
The motivation for using materialized views is to improve performance, but the overhead associated with materialized view management can become a significant system management problem. When reviewing or evaluating some of the necessary materialized view management activities, consider some of the following:
Identifying what materialized views to create initially.
Indexing the materialized views.
Ensuring that all materialized views and materialized view indexes are refreshed properly each time the database is updated.
Checking which materialized views have been used.
Determining how effective each materialized view has been on workload performance.
Measuring the space being used by materialized views.
Determining which new materialized views should be created.
Determining which existing materialized views should be dropped.
Archiving old detail and materialized view data that is no longer useful.
After the initial effort of creating and populating the data warehouse or data mart, the major administration overhead is the update process, which involves:
Periodic extraction of incremental changes from the operational systems.
Transforming the data.
Verifying that the incremental changes are correct, consistent, and complete.
Bulk-loading the data into the warehouse.
Refreshing indexes and materialized views so that they are consistent with the detail data.
The update process must generally be performed within a limited period of time known as the update window. The update window depends on the update frequency (such as daily or weekly) and the nature of the business. For a daily update frequency, an update window of two to six hours might be typical.
You need to know your update window for the following activities:
Loading the detail data
Updating or rebuilding the indexes on the detail data
Performing quality assurance tests on the data
Refreshing the materialized views
Updating the indexes on the materialized views
SELECT clause in the materialized view creation statement defines the data that the materialized view is to contain. Only a few restrictions limit what can be specified. Any number of tables can be joined together. However, they cannot be remote tables if you wish to take advantage of query rewrite. Besides tables, other elements such as views, inline views (subqueries in the
FROM clause of a
SELECT statement), subqueries, and materialized views can all be joined or referenced in the
SELECT clause. You cannot, however, define a materialized with a subquery in the select list of the defining query. You can, however, include subqueries elsewhere in the defining query, such as in the
The types of materialized views are:
In data warehouses, materialized views normally contain aggregates as shown in Example 8-1. For fast refresh to be possible, the
SELECT list must contain all of the
BY columns (if present), and there must be a
COUNT(*) and a
COUNT(column) on any aggregated columns. Also, materialized view logs must be present on all tables referenced in the query that defines the materialized view. The valid aggregate functions are:
MAX, and the expression to be aggregated can be any SQL value expression. See "Restrictions on Fast Refresh on Materialized Views with Aggregates".
Fast refresh for a materialized view containing joins and aggregates is possible after any type of DML to the base tables (direct load or conventional
DELETE). It can be defined to be refreshed
COMMIT materialized view will be refreshed automatically when a transaction that does DML to one of the materialized view's detail tables commits. The time taken to complete the commit may be slightly longer than usual when this method is chosen. This is because the refresh operation is performed as part of the commit process. Therefore, this method may not be suitable if many users are concurrently changing the tables upon which the materialized view is based.
Here are some examples of materialized views with aggregates. Note that materialized view logs are only created because this materialized view will be fast refreshed.
Example 8-1 Example 1: Creating a Materialized View
CREATE MATERIALIZED VIEW LOG ON products WITH SEQUENCE, ROWID (prod_id, prod_name, prod_desc, prod_subcategory, prod_subcategory_desc, prod_category, prod_category_desc, prod_weight_class, prod_unit_of_measure, prod_pack_size, supplier_id, prod_status, prod_list_price, prod_min_price) INCLUDING NEW VALUES; CREATE MATERIALIZED VIEW LOG ON sales WITH SEQUENCE, ROWID (prod_id, cust_id, time_id, channel_id, promo_id, quantity_sold, amount_sold) INCLUDING NEW VALUES; CREATE MATERIALIZED VIEW product_sales_mv PCTFREE 0 TABLESPACE demo STORAGE (INITIAL 8k NEXT 8k PCTINCREASE 0) BUILD IMMEDIATE REFRESH FAST ENABLE QUERY REWRITE AS SELECT p.prod_name, SUM(s.amount_sold) AS dollar_sales, COUNT(*) AS cnt, COUNT(s.amount_sold) AS cnt_amt FROM sales s, products p WHERE s.prod_id = p.prod_id GROUP BY p.prod_name;
This example creates a materialized view
product_sales_mv that computes total number and value of sales for a product. It is derived by joining the tables
products on the column
prod_id. The materialized view is populated with data immediately because the build method is immediate and it is available for use by query rewrite. In this example, the default refresh method is
FAST, which is allowed because the appropriate materialized view logs have been created on tables
Example 8-2 Example 2: Creating a Materialized View
CREATE MATERIALIZED VIEW product_sales_mv PCTFREE 0 TABLESPACE demo STORAGE (INITIAL 16k NEXT 16k PCTINCREASE 0) BUILD DEFERRED REFRESH COMPLETE ON DEMAND ENABLE QUERY REWRITE AS SELECT p.prod_name, SUM(s.amount_sold) AS dollar_sales FROM sales s, products p WHERE s.prod_id = p.prod_id GROUP BY p.prod_name;
This example creates a materialized view
product_sales_mv that computes the sum of sales by
prod_name. It is derived by joining the tables
products on the column
prod_id. The materialized view does not initially contain any data, because the build method is
DEFERRED. A complete refresh is required for the first refresh of a build deferred materialized view. When it is refreshed and once populated, this materialized view can be used by query rewrite.
Example 8-3 Example 3: Creating a Materialized View
CREATE MATERIALIZED VIEW LOG ON sales WITH SEQUENCE, ROWID (prod_id, cust_id, time_id, channel_id, promo_id, quantity_sold, amount_sold) INCLUDING NEW VALUES; CREATE MATERIALIZED VIEW sum_sales PARALLEL BUILD IMMEDIATE REFRESH FAST ON COMMIT AS SELECT s.prod_id, s.time_id, COUNT(*) AS count_grp, SUM(s.amount_sold) AS sum_dollar_sales, COUNT(s.amount_sold) AS count_dollar_sales, SUM(s.quantity_sold) AS sum_quantity_sales, COUNT(s.quantity_sold) AS count_quantity_sales FROM sales s GROUP BY s.prod_id, s.time_id;
This example creates a materialized view that contains aggregates on a single table. Because the materialized view log has been created with all referenced columns in the materialized view's defining query, the materialized view is fast refreshable. If DML is applied against the
sales table, then the changes will be reflected in the materialized view when the commit is issued.
Table 8-2 illustrates the aggregate requirements for materialized views.
|If aggregate X is present, aggregate Y is required and aggregate Z is optional|
COUNT(*) must always be present to guarantee all types of fast refresh. Otherwise, you may be limited to fast refresh after inserts only. Oracle recommends that you include the optional aggregates in column
Z in the materialized view in order to obtain the most efficient and accurate fast refresh of the aggregates.
Some materialized views contain only joins and no aggregates, such as in Example 8-4, where a materialized view is created that joins the
sales table to the
customers tables. The advantage of creating this type of materialized view is that expensive joins will be precalculated.
Fast refresh for a materialized view containing only joins is possible after any type of DML to the base tables (direct-path or conventional
A materialized view containing only joins can be defined to be refreshed
ON COMMIT or
DEMAND. If it is
COMMIT, the refresh is performed at commit time of the transaction that does DML on the materialized view's detail table.
If you specify
FAST, Oracle performs further verification of the query definition to ensure that fast refresh can be performed if any of the detail tables change. These additional checks are:
A materialized view log must be present for each detail table and the ROWID column must be present in each materialized view log.
The rowids of all the detail tables must appear in the
SELECT list of the materialized view query definition.
If there are no outer joins, you may have arbitrary selections and joins in the
WHERE clause. However, if there are outer joins, the
WHERE clause cannot have any selections. Further, if there are outer joins, all the joins must be connected by
ANDs and must use the equality (=) operator.
If there are outer joins, unique constraints must exist on the join columns of the inner table. For example, if you are joining the fact table and a dimension table and the join is an outer join with the fact table being the outer table, there must exist unique constraints on the join columns of the dimension table.
If some of these restrictions are not met, you can create the materialized view as
FORCE to take advantage of fast refresh when it is possible. If one of the tables did not meet all of the criteria, but the other tables did, the materialized view would still be fast refreshable with respect to the other tables for which all the criteria are met.
If the materialized view contains only joins, the ROWID columns for each table (and each instance of a table that occurs multiple times in the
FROM list) must be present in the
SELECT list of the materialized view.
If the materialized view has remote tables in the
FROM clause, all tables in the
FROM clause must be located on that same site. Further,
COMMIT refresh is not supported for materialized view with remote tables. Materialized view logs must be present on the remote site for each detail table of the materialized view and
ROWID columns must be present in the
SELECT list of the materialized view.
To improve refresh performance, you should create indexes on the materialized view's columns that store the rowids of the fact table.
Example 8-4 Materialized View Containing Only Joins
CREATE MATERIALIZED VIEW LOG ON sales WITH ROWID; CREATE MATERIALIZED VIEW LOG ON times WITH ROWID; CREATE MATERIALIZED VIEW LOG ON customers WITH ROWID; CREATE MATERIALIZED VIEW detail_sales_mv PARALLEL BUILD IMMEDIATE REFRESH FAST AS SELECT s.rowid "sales_rid", t.rowid "times_rid", c.rowid "customers_rid", c.cust_id, c.cust_last_name, s.amount_sold, s.quantity_sold, s.time_id FROM sales s, times t, customers c WHERE s.cust_id = c.cust_id(+) AND s.time_id = t.time_id(+);
In this example, to perform a fast refresh,
UNIQUE constraints should exist on
t.time_id. You should also create indexes on the columns
customers_rid, as illustrated in the following. This will improve the refresh performance.
CREATE INDEX mv_ix_salesrid ON detail_sales_mv("sales_rid");
Alternatively, if the previous example did not include the columns
customers_rid, and if the refresh method was
FORCE, then this materialized view would be fast refreshable only if the sales table was updated but not if the tables
customers were updated.
CREATE MATERIALIZED VIEW detail_sales_mv PARALLEL BUILD IMMEDIATE REFRESH FORCE AS SELECT s.rowid "sales_rid", c.cust_id, c.cust_last_name, s.amount_sold, s.quantity_sold, s.time_id FROM sales s, times t, customers c WHERE s.cust_id = c.cust_id(+) AND s.time_id = t.time_id(+);
A nested materialized view is a materialized view whose definition is based on another materialized view. A nested materialized view can reference other relations in the database in addition to referencing materialized views.
In a data warehouse, you typically create many aggregate views on a single join (for example, rollups along different dimensions). Incrementally maintaining these distinct materialized aggregate views can take a long time, because the underlying join has to be performed many times.
Using nested materialized views, you can create multiple single-table materialized views based on a joins-only materialized view and the join is performed just once. In addition, optimizations can be performed for this class of single-table aggregate materialized view and thus refresh is very efficient.
Example 8-5 Nested Materialized View
You can create a nested materialized view on materialized views that contain joins only or joins and aggregates. All the underlying objects (materialized views or tables) on which the materialized view is defined must have a materialized view log. All the underlying objects are treated as if they were tables. In addition, you can use all the existing options for materialized views.
Using the tables and their columns from the
sh sample schema, the following materialized views illustrate how nested materialized views can be created.
CREATE MATERIALIZED VIEW LOG ON sales WITH ROWID; CREATE MATERIALIZED VIEW LOG ON customers WITH ROWID; CREATE MATERIALIZED VIEW LOG ON times WITH ROWID; /*create materialized view join_sales_cust_time as fast refreshable at COMMIT time */ CREATE MATERIALIZED VIEW join_sales_cust_time REFRESH FAST ON COMMIT AS SELECT c.cust_id, c.cust_last_name, s.amount_sold, t.time_id, t.day_number_in_week, s.rowid srid, t.rowid trid, c.rowid crid FROM sales s, customers c, times t WHERE s.time_id = t.time_id AND s.cust_id = c.cust_id;
To create a nested materialized view on the table
join_sales_cust_time, you would have to create a materialized view log on the table. Because this will be a single-table aggregate materialized view on
join_sales_cust_time, you need to log all the necessary columns and use the
/* create materialized view log on join_sales_cust_time */ CREATE MATERIALIZED VIEW LOG ON join_sales_cust_time WITH ROWID (cust_last_name, day_number_in_week, amount_sold) INCLUDING NEW VALUES; /* create the single-table aggregate materialized view sum_sales_cust_time on join_sales_cust_time as fast refreshable at COMMIT time */ CREATE MATERIALIZED VIEW sum_sales_cust_time REFRESH FAST ON COMMIT AS SELECT COUNT(*) cnt_all, SUM(amount_sold) sum_sales, COUNT(amount_sold) cnt_sales, cust_last_name, day_number_in_week FROM join_sales_cust_time GROUP BY cust_last_name, day_number_in_week;
Some types of nested materialized views cannot be fast refreshed. Use
EXPLAIN_MVIEW to identify those types of materialized views. You can refresh a tree of nested materialized views in the appropriate dependency order by specifying the
nested = TRUE parameter with the
DBMS_MVIEW. REFRESH parameter. For example, if you call
DBMS_MVIEW.REFRESH ('SUM_SALES_CUST_TIME', nested => TRUE), the
REFRESH procedure will first refresh the
join_sales_cust_time materialized view, and then refresh the
sum_sales_cust_time materialized view.
You should keep the following in mind when deciding whether to use nested materialized views:
If you want to use fast refresh, you should fast refresh all the materialized views along any chain.
If you want the highest level materialized view to be fresh with respect to the detail tables, you need to ensure that all materialized views in a tree are refreshed in the correct dependency order before refreshing the highest-level. You can automatically refesh intermediate materialized views in a nested hierarchy using the
nested = TRUE parameter, as described in "Nesting Materialized Views with Joins and Aggregates". If you do not specify
nested = TRUE and the materialzied views under the highest-level materialized view are stale, refreshing only the highest-level will succeed, but makes it fresh only with respect to its underlying materialized view, not the detail tables at the base of the tree.
When refreshing materialized views, you need to ensure that all materialized views in a tree are refreshed. If you only refresh the highest-level materialized view, the materialized views under it will be stale and you must explicitly refresh them. If you use the
REFRESH procedure with the
nested parameter value set to
TRUE, only specified materialized views and their child materialized views in the tree are refreshed, and not their top-level materialized views. Use the
REFRESH_DEPENDENT procedure with the nested parameter value set to
TRUE if you want to ensure that all materialized views in a tree are refreshed.
Freshness of a materialized view is calculated relative to the objects directly referenced by the materialized view. When a materialized view references another materialized view, the freshness of the topmost materialized view is calculated relative to changes in the materialized view it directly references, not relative to changes in the tables referenced by the materialized view it references.
You cannot create both a materialized view and a prebuilt materialized view on the same table. For example, If you have a table
costs with a materialized view
cost_mv based on it, you cannot then create a prebuilt materialized view on table
costs. The result would make
cost_mv a nested materialized view and this method of conversion is not supported.
A materialized view can be created with the
VIEW statement or using Enterprise Manager. Example 8-6 creates the materialized view
Example 8-6 Creating a Materialized View
CREATE MATERIALIZED VIEW cust_sales_mv PCTFREE 0 TABLESPACE demo STORAGE (INITIAL 16k NEXT 16k PCTINCREASE 0) PARALLEL BUILD IMMEDIATE REFRESH COMPLETE ENABLE QUERY REWRITE AS SELECT c.cust_last_name, SUM(amount_sold) AS sum_amount_sold FROM customers c, sales s WHERE s.cust_id = c.cust_id GROUP BY c.cust_last_name;
It is not uncommon in a data warehouse to have already created summary or aggregation tables, and you might not wish to repeat this work by building a new materialized view. In this case, the table that already exists in the database can be registered as a prebuilt materialized view. This technique is described in "Registering Existing Materialized Views".
Once you have selected the materialized views you want to create, follow these steps for each materialized view.
Design the materialized view. Existing user-defined materialized views do not require this step. If the materialized view contains many rows, then, if appropriate, the materialized view should be partitioned (if possible) and should match the partitioning of the largest or most frequently updated detail or fact table (if possible). Refresh performance benefits from partitioning, because it can take advantage of parallel DML capabilities and possible PCT-based refresh.
VIEW statement to create and, optionally, populate the materialized view. If a user-defined materialized view already exists, then use the
TABLE clause in the
VIEW statement. Otherwise, use the
IMMEDIATE clause to populate the materialized view immediately, or the
DEFERRED clause to populate the materialized view later. A
DEFERRED materialized view is disabled for use by query rewrite until the first
REFRESH, after which it will be automatically enabled, provided the
REWRITE clause has been specified.
See Also:Oracle Database SQL Reference for descriptions of the SQL statements
Currently, when a materialized view is created, if its defining query contains same-name columns in the
SELECT list, the name conflicts need to be resolved by specifying unique aliases for those columns. Otherwise, the
VIEW statement will fail with the error messages of columns ambiguously defined. However, the standard method of attaching aliases in the
SELECT clause for name resolution restricts the use of the full text match query rewrite and it will occur only when the text of the materialized view's defining query and the text of user input query are identical. Thus, if the user specifies select aliases in the materialized view's defining query while there is no alias in the query, the full text match comparison will fail. This is particularly a problem for queries from Discoverer, which makes extensive use of column aliases.
The following is an example of the problem.
sales_mv is created with column aliases in the
SELECT clause but the input query
Q1 does not have the aliases. The full text match rewrite will fail. The materialized view is as follows:
CREATE MATERIALIZED VIEW sales_mv ENABLE QUERY REWRITE AS SELECT s.time_id sales_tid, c.time_id costs_tid FROM sales s, products p, costs c WHERE s.prod_id = p.prod_id AND c.prod_id = p.prod_id AND p.prod_name IN (SELECT prod_name FROM products);
Input query statement
Q1 is as follows:
SELECT s.time_id, c.time_id FROM sales s, products p, costs c WHERE s.prod_id = p.prod_id AND c.prod_id = p.prod_id AND p.prod_name IN (SELECT prod_name FROM products);
Even though the materialized view's defining query is almost identical and logically equivalent to the user's input query, query rewrite does not happen because of the failure of full text match that is the only rewrite possibility for some queries (for example, a subquery in the
You can add a column alias list to a
VIEW statement. The column alias list explicitly resolves any column name conflict without attaching aliases in the
SELECT clause of the materialized view. The syntax of the materialized view column alias list is illustrated in the following example:
CREATE MATERIALIZED VIEW sales_mv (sales_tid, costs_tid) ENABLE QUERY REWRITE AS SELECT s.time_id, c.time_id FROM sales s, products p, costs c WHERE s.prod_id = p.prod_id AND c.prod_id = p.prod_id AND p.prod_name IN (SELECT prod_name FROM products);
In this example, the defining query of
sales_mv now matches exactly with the user query
Q1, so full text match rewrite will take place.
Note that when aliases are specified in both the
SELECT clause and the new alias list clause, the alias list clause supersedes the ones in the
The name of a materialized view must conform to standard Oracle naming conventions. However, if the materialized view is based on a user-defined prebuilt table, then the name of the materialized view must exactly match that table name.
If you already have a naming convention for tables and indexes, you might consider extending this naming scheme to the materialized views so that they are easily identifiable. For example, instead of naming the materialized view
sum_of_sales, it could be called
sum_of_sales_mv to denote that this is a materialized view and not a table or view.
Unless the materialized view is based on a user-defined prebuilt table, it requires and occupies storage space inside the database. Therefore, the storage needs for the materialized view should be specified in terms of the tablespace where it is to reside and the size of the extents.
If you do not know how much space the materialized view will require, then the
DBMS_MVIEW.ESTIMATE_SIZE package can estimate the number of bytes required to store this uncompressed materialized view. This information can then assist the design team in determining the tablespace in which the materialized view should reside.
You should use table compression with highly redundant data, such as tables with many foreign keys. This is particularly useful for materialized views created with the
ROLLUP clause. Table compression reduces disk use and memory use (specifically, the buffer cache), often leading to a better scaleup for read-only operations. Table compression can also speed up query execution at the expense of update cost.
See Also:Oracle Database SQL Reference for a complete description of
Two build methods are available for creating the materialized view, as shown in Table 8-3. If you select
IMMEDIATE, the materialized view definition is added to the schema objects in the data dictionary, and then the fact or detail tables are scanned according to the
SELECT expression and the results are stored in the materialized view. Depending on the size of the tables to be scanned, this build process can take a considerable amount of time.
An alternative approach is to use the
DEFERRED clause, which creates the materialized view without data, thereby enabling it to be populated at a later date using the
DBMS_MVIEW.REFRESH package described in Chapter 15, " Maintaining the Data Warehouse".
Before creating a materialized view, you can verify what types of query rewrite are possible by calling the procedure
DBMS_MVIEW.EXPLAIN_MVIEW, or use
DBMS_ADVISOR.TUNE_MVIEW to optimize the materialized view so that a many types of query rewrite are possible. Once the materialized view has been created, you can use
DBMS_MVIEW.EXPLAIN_REWRITE to find out if (or why not) it will rewrite a specific query.
Even though a materialized view is defined, it will not automatically be used by the query rewrite facility. Even though query rewrite is enabled by default, you also must specify the
REWRITE clause if the materialized view is to be considered available for rewriting queries.
If this clause is omitted or specified as
REWRITE when the materialized view is created, the materialized view can subsequently be enabled for query rewrite with the
If you define a materialized view as
DEFERRED, it is not eligible for query rewrite until it is populated with data.
Query rewrite is not possible with all materialized views. If query rewrite is not occurring when expected,
DBMS_MVIEW.EXPLAIN_REWRITE can help provide reasons why a specific query is not eligible for rewrite. If this shows that not all types of query rewrite are possible, use the procedure
DBMS_ADVISOR.TUNE_MVIEW to see if the materialized view can be defined differently so that query rewrite is possible. Also, check to see if your materialized view satisfies all of the following conditions.
You should keep in mind the following restrictions:
The defining query of the materialized view cannot contain any non-repeatable expressions (
SYSDATE, non-repeatable PL/SQL functions, and so on).
The query cannot contain any references to
RAW datatypes or object
If the materialized view was registered as
PREBUILT, the precision of the columns must agree with the precision of the corresponding
SELECT expressions unless overridden by the
You should keep in mind the following restrictions:
If a query has both local and remote tables, only local tables will be considered for potential rewrite.
Neither the detail tables nor the materialized view can be owned by
If a column or expression is present in the
BY clause of the materialized view, it must also be present in the
Aggregate functions must occur only as the outermost part of the expression. That is, aggregates such as
AVG(x) are not allowed.
BY clauses are not allowed.
When you define a materialized view, you can specify three refresh options: how to refresh, what type of refresh, and can trusted constraints be used. If unspecified, the defaults are assumed as
ENFORCED constraints respectively.
The two refresh execution modes are
DEMAND. Depending on the materialized view you create, some of the options may not be available. Table 8-4 describes the refresh modes.
Table 8-4 Refresh Modes
||Refresh occurs automatically when a transaction that modified one of the materialized view's detail tables commits. This can be specified as long as the materialized view is fast refreshable (in other words, not complex). The |
||Refresh occurs when a user manually executes one of the available refresh procedures contained in the |
When a materialized view is maintained using the
COMMIT method, the time required to complete the commit may be slightly longer than usual. This is because the refresh operation is performed as part of the commit process. Therefore this method may not be suitable if many users are concurrently changing the tables upon which the materialized view is based.
If you anticipate performing insert, update or delete operations on tables referenced by a materialized view concurrently with the refresh of that materialized view, and that materialized view includes joins and aggregation, Oracle recommends you use
COMMIT fast refresh rather than
DEMAND fast refresh.
If you think the materialized view did not refresh, check the alert log or trace file.
If a materialized view fails during refresh at
COMMIT time, you must explicitly invoke the refresh procedure using the
DBMS_MVIEW package after addressing the errors specified in the trace files. Until this is done, the materialized view will no longer be refreshed automatically at commit time.
You can specify how you want your materialized views to be refreshed from the detail tables by selecting one of four options:
NEVER. Table 8-5 describes the refresh options.
Table 8-5 Refresh Options
||Refreshes by recalculating the materialized view's defining query.|
||Applies incremental changes to refresh the materialized view using the information logged in the materialized view logs, or from a SQL*Loader direct-path or a partition maintenance operation.|
||Indicates that the materialized view will not be refreshed with refresh mechanisms.|
Whether the fast refresh option is available depends upon the type of materialized view. You can call the procedure
DBMS_MVIEW.EXPLAIN_MVIEW to determine whether fast refresh is possible.
You can also specify if it is acceptable to use trusted constraints and
REWRITE_INTEGRITY = TRUSTED during refresh. Any nonvalidated
RELY constraint is a trusted constraint. For example, nonvalidated foreign key/primary key relationships, functional dependencies defined in dimensions or a materialized view in the
UNKNOWN state. If query rewrite is enabled during refresh, these can improve the performance of refresh by enabling more performant query rewrites. Any materialized view that can uses
TRUSTED constraints for refresh is left in a state of trusted freshness (the
UNKNOWN state) after refresh.
This is reflected in the column
STALENESS in the view
USER_MVIEWS. The column
UNKNOWN_TRUSTED_FD in the same view is also set to
Y, which means yes.
You can define this property of the materialized either during create time by specifying
CONSTRAINTS or by using
Table 8-6 Constraints
|Constraints to Use||Description|
|Refresh can use trusted constraints and |
|Refresh can use validated constraints and |
The defining query of the materialized view is restricted as follows:
The materialized view must not contain references to non-repeating expressions like
The materialized view must not contain references to
RAW data types.
Defining queries for materialized views with joins only and no aggregates have the following restrictions on fast refresh:
All restrictions from "General Restrictions on Fast Refresh".
They cannot have
BY clauses or aggregates.
WHERE clause of the query contains outer joins, then unique constraints must exist on the join columns of the inner join table.
If there are no outer joins, you can have arbitrary selections and joins in the
WHERE clause. However, if there are outer joins, the
WHERE clause cannot have any selections. Furthermore, if there are outer joins, all the joins must be connected by
ANDs and must use the equality (
Rowids of all the tables in the
FROM list must appear in the
SELECT list of the query.
Materialized view logs must exist with rowids for all the base tables in the
FROM list of the query.
Defining queries for materialized views with aggregates or joins have the following restrictions on fast refresh:
All restrictions from "General Restrictions on Fast Refresh".
Fast refresh is supported for both
DEMAND materialized views, however the following restrictions apply:
All tables in the materialized view must have materialized view logs, and the materialized view logs must:
Contain all columns from the table referenced in the materialized view.
SEQUENCE clause if the table is expected to have a mix of inserts/direct-loads, deletes, and updates.
MAX are supported for fast refresh.
COUNT(*) must be specified.
For each aggregate such as
AVG(expr), the corresponding
COUNT(expr) must be present.
STDDEV(expr) is specified,
SUM(expr) must be specified. Oracle recommends that
SUM(expr *expr) be specified. See Table 8-2 for further details.
SELECT list must contain all
If the materialized view has one of the following, then fast refresh is supported only on conventional DML inserts and direct loads.
Materialized views with
Materialized views which have
SUM(expr) but no
Materialized views without
Such a materialized view is called an insert-only materialized view.
A materialized view with
MIN is fast refreshable after delete or mixed DML statements if it does not have a
Materialized views with named views or subqueries in the
FROM clause can be fast refreshed provided the views can be completely merged. For information on which views will merge, refer to the Oracle Database Performance Tuning Guide.
If there are no outer joins, you may have arbitrary selections and joins in the
Materialized aggregate views with outer joins are fast refreshable after conventional DML and direct loads, provided only the outer table has been modified. Also, unique constraints must exist on the join columns of the inner join table. If there are outer joins, all the joins must be connected by
ANDs and must use the equality (
For materialized views with
ROLLUP, grouping sets, or concatenation of them, the following restrictions apply:
SELECT list should contain grouping distinguisher that can either be a
GROUPING_ID function on all
BY expressions or
GROUPING functions one for each
BY expression. For example, if the
BY clause of the materialized view is "
CUBE(a, b)", then the
SELECT list should contain either "
GROUPING_ID(a, b)" or "
GROUPING(b)" for the materialized view to be fast refreshable.
BY should not result in any duplicate groupings. For example, "
GROUP BY a, ROLLUP(a, b)" is not fast refreshable because it results in duplicate groupings "
(a), (a, b), AND (a)".
Materialized views with the
ALL set operator support the
FAST option if the following conditions are satisfied:
The defining query must have the
ALL operator at the top level.
ALL operator cannot be embedded inside a subquery, with one exception: The
ALL can be in a subquery in the
FROM clause provided the defining query is of the form
SELECT * FROM (view or subquery with
ALL) as in the following example:
CREATE VIEW view_with_unionall_mv AS (SELECT c.rowid crid, c.cust_id, 2 umarker FROM customers c WHERE c.cust_last_name = 'Smith' UNION ALL SELECT c.rowid crid, c.cust_id, 3 umarker FROM customers c WHERE c.cust_last_name = 'Jones'); CREATE MATERIALIZED VIEW unionall_inside_view_mv REFRESH FAST ON DEMAND AS SELECT * FROM view_with_unionall;
Note that the view
view_with_unionall_mv satisfies all requirements for fast refresh.
Each query block in the
ALL query must satisfy the requirements of a fast refreshable materialized view with aggregates or a fast refreshable materialized view with joins.
The appropriate materialized view logs must be created on the tables as required for the corresponding type of fast refreshable materialized view.
Note that the Oracle Database also allows the special case of a single table materialized view with joins only provided the
ROWID column has been included in the
SELECT list and in the materialized view log. This is shown in the defining query of the view
SELECT list of each query must include a maintenance column, called a
ALL marker. The
ALL column must have a distinct constant numeric or string value in each
ALL branch. Further, the marker column must appear in the same ordinal position in the
SELECT list of each query block.
Some features such as outer joins, insert-only aggregate materialized view queries and remote tables are not supported for materialized views with
PCT-based refresh is not supported for
ALL materialized views.
The compatibility initialization parameter must be set to 9.2.0 or higher to create a fast refreshable materialized view with
In addition to the
EXPLAIN_MVIEW procedure, which is discussed throughout this chapter, you can use the
DBMS_ADVISOR.TUNE_MVIEW procedure to optimize a
VIEW statement to achieve
REWRITE goals. The procedure is described in "Tuning Materialized Views for Fast Refresh and Query Rewrite".
A nested materialized view is considered to be fresh as long as its data is synchronized with the data in its detail tables, even if some of its detail tables could be stale materialized views.
You can refresh nested materialized views in two ways:
DBMS_MVIEW.REFRESH with the
nested flag set to
REFRESH_DEPENDENT with the
nested flag set to
TRUE on the base tables. If you use
DBMS_MVIEW.REFRESH, the entire materialized view chain is refreshed from the top down. With
DBMS_MVIEW.REFRESH_DEPENDENT, the entire chain is refreshed from the bottom up.
Example 8-7 Example of Refreshing a Nested Materialized View
The following statement shows an example of refreshing a nested materialized view:
DBMS_MVIEW.REFRESH('SALES_MV,COST_MV', nested => TRUE);
This statement will first refresh all child materialized views of
cost_mv based on the dependency analysis and then refresh the two specified materialized views.
You can query the
STALE_SINCE column in the
*_MVIEWS views to find out when a materialized view became stale.
To improve the performance of queries against large materialized views, store the rows in the materialized view in the order specified in the
BY clause. This initial ordering provides physical clustering of the data. If indexes are built on the columns by which the materialized view is ordered, accessing the rows of the materialized view using the index often reduces the time for disk I/O due to the physical clustering.
BY clause is not considered part of the materialized view definition. As a result, there is no difference in the manner in which Oracle Database detects the various types of materialized views (for example, materialized join views with no aggregates). For the same reason, query rewrite is not affected by the
BY clause. This feature is similar to the
Materialized view logs are required if you want to use fast refresh, with the exception of PCT refresh,where there a few situations where they are not necessary. As a general rule, though, you should create materialized view logs if you want to use fast refresh. Materialized view logs are defined using a
LOG statement on the base table that is to be changed. They are not created on the materialized view. For fast refresh of materialized views, the definition of the materialized view logs must normally specify the
ROWID clause. In addition, for aggregate materialized views, it must also contain every column in the table referenced in the materialized view, the
VALUES clause and the
An example of a materialized view log is shown as follows where one is created on the table
CREATE MATERIALIZED VIEW LOG ON sales WITH ROWID (prod_id, cust_id, time_id, channel_id, promo_id, quantity_sold, amount_sold) INCLUDING NEW VALUES;
Alternatively, a materialized view log can be amended to include the rowid, as in the following:
ALTER MATERIALIZED VIEW LOG ON sales ADD ROWID (prod_id, cust_id, time_id, channel_id, promo_id, quantity_sold, amount_sold) INCLUDING NEW VALUES;
Oracle recommends that the keyword
SEQUENCE be included in your materialized view log statement unless you are sure that you will never perform a mixed DML operation (a combination of
DELETE operations on multiple tables). The
SEQUENCE column is required in the materialized view log to support fast refresh with a combination of
DELETE statements on multiple tables. You can, however, add the
SEQUENCE number to the materialized view log after it has been created.
The boundary of a mixed DML operation is determined by whether the materialized view is
COMMIT, the mixed DML statements occur within the same transaction because the refresh of the materialized view will occur upon commit of this transaction.
DEMAND, the mixed DML statements occur between refreshes. The following example of a materialized view log illustrates where one is created on the table
sales that includes the
CREATE MATERIALIZED VIEW LOG ON sales WITH SEQUENCE, ROWID (prod_id, cust_id, time_id, channel_id, promo_id, quantity_sold, amount_sold) INCLUDING NEW VALUES;
If you specify
FORCE and any items specified with the
ADD clause have already been specified for the materialized view log, Oracle does not return an error, but silently ignores the existing elements and adds to the materialized view log any items that do not already exist in the log. For example, if you used a filter column such as
cust_id and this column already existed, Oracle Database ignores the redundancy and does not return an error.
A materialized view can also be created using Enterprise Manager by selecting the materialized view object type. There is no difference in the information required if this approach is used. See Oracle Enterprise Manager Advanced Configuration for further information.
When using certain materialized views, you must ensure that your NLS parameters are the same as when you created the materialized view. Materialized views with this restriction are as follows:
Expressions that may return different values, depending on NLS parameter settings. For example, (date > "01/02/03") or (rate <= "2.150") are NLS parameter dependent expressions.
Equijoins where one side of the join is character data. The result of this equijoin depends on collation and this can change on a session basis, giving an incorrect result in the case of query rewrite or an inconsistent materialized view after a refresh operation.
Expressions that generate internal conversion to character data in the
SELECT list of a materialized view, or inside an aggregate of a materialized aggregate view. This restriction does not apply to expressions that involve only numeric data, for example,
b are numeric fields.
You can add a comment to a materialized view. For example, the following statement adds a comment to data dictionary views for the existing materialized view:
COMMENT ON MATERIALIZED VIEW sales_mv IS 'sales materialized view';
To view the comment after the preceding statement execution, the user can query the catalog views,
ALL_MVIEW_COMMENTS. For example:
SELECT MVIEW_NAME, COMMENTS FROM USER_MVIEW_COMMENTS WHERE MVIEW_NAME = 'SALES_MV';
The output will resemble the following:
MVIEW_NAME COMMENTS ----------- ----------------------- SALES_MV sales materialized view
Note: If the compatibility is set to 10.0.1 or higher,
TABLE will not be allowed for the materialized view container table. The following error message will be thrown if it is issued.
ORA-12098: cannot comment on the materialized view.
In the case of a prebuilt table, if it has an existing comment, the comment will be inherited by the materialized view after it has been created. The existing comment will be prefixed with
'(from table)'. For example, table
sales_summary was created to contain sales summary information. An existing comment
'Sales summary data' was associated with the table. A materialized view of the same name is created to use the prebuilt table as its container table. After the materialized view creation, the comment becomes
'(from table) Sales summary data'.
However, if the prebuilt table,
sales_summary, does not have any comment, the following comment is added:
'Sales summary data'. Then, if we drop the materialized view, the comment will be passed to the prebuilt table with the comment:
'(from materialized view) Sales summary data'.
Provide query rewrite to all SQL applications.
Enable materialized views defined in one application to be transparently accessed in another application.
Generally support fast parallel or fast materialized view refresh.
Because of these limitations, and because existing materialized views can be extremely large and expensive to rebuild, you should register your existing materialized view tables whenever possible. You can register a user-defined materialized view with the
TABLE statement. Once registered, the materialized view can be used for query rewrites or maintained by one of the refresh methods, or both.
The contents of the table must reflect the materialization of the defining query at the time you register it as a materialized view, and each column in the defining query must correspond to a column in the table that has a matching datatype. However, you can specify
PRECISION to allow the precision of columns in the defining query to be different from that of the table columns.
The table and the materialized view must have the same name, but the table retains its identity as a table and can contain columns that are not referenced in the defining query of the materialized view. These extra columns are known as unmanaged columns. If rows are inserted during a refresh operation, each unmanaged column of the row is set to its default value. Therefore, the unmanaged columns cannot have
NULL constraints unless they also have default values.
Materialized views based on prebuilt tables are eligible for selection by query rewrite provided the parameter
QUERY_REWRITE_INTEGRITY is set to
TRUSTED. See Chapter 18, " Query Rewrite" for details about integrity levels.
The following example illustrates the two steps required to register a user-defined table. First, the table is created, then the materialized view is defined using exactly the same name as the table. This materialized view
sum_sales_tab is eligible for use in query rewrite.
CREATE TABLE sum_sales_tab PCTFREE 0 TABLESPACE demo STORAGE (INITIAL 16k NEXT 16k PCTINCREASE 0) AS SELECT s.prod_id, SUM(amount_sold) AS dollar_sales, SUM(quantity_sold) AS unit_sales FROM sales s GROUP BY s.prod_id; CREATE MATERIALIZED VIEW sum_sales_tab ON PREBUILT TABLE WITHOUT REDUCED PRECISION ENABLE QUERY REWRITE AS SELECT s.prod_id, SUM(amount_sold) AS dollar_sales, SUM(quantity_sold) AS unit_sales FROM sales s GROUP BY s.prod_id;
You could have compressed this table to save space. See "Storage And Table Compression" for details regarding table compression.
In some cases, user-defined materialized views are refreshed on a schedule that is longer than the update cycle. For example, a monthly materialized view might be updated only at the end of each month, and the materialized view values always refer to complete time periods. Reports written directly against these materialized views implicitly select only data that is not in the current (incomplete) time period. If a user-defined materialized view already contains a time dimension:
It should be registered and then fast refreshed each update cycle.
You can create a view that selects the complete time period of interest.
The reports should be modified to refer to the view instead of referring directly to the user-defined materialized view.
If the user-defined materialized view does not contain a time dimension, then:
Create a new materialized view that does include the time dimension (if possible).
The view should aggregate over the time column in the new materialized view.
The two most common operations on a materialized view are query execution and fast refresh, and each operation has different performance requirements. Query execution might need to access any subset of the materialized view key columns, and might need to join and aggregate over a subset of those columns. Consequently, query execution usually performs best if a single-column bitmap index is defined on each materialized view key column.
In the case of materialized views containing only joins using fast refresh, Oracle recommends that indexes be created on the columns that contain the rowids to improve the performance of the refresh operation.
If a materialized view using aggregates is fast refreshable, then an index appropriate for the fast refresh procedure is created unless
INDEX is specified in the
See Chapter 17, " SQLAccess Advisor" for information on using the SQLAccess Advisor to determine what indexes are appropriate for your materialized view.
DROP MATERIALIZED VIEW sales_sum_mv;
This statement drops the materialized view
sales_sum_mv. If the materialized view was prebuilt on a table, then the table is not dropped, but it can no longer be maintained with the refresh mechanism or used by query rewrite. Alternatively, you can drop a materialized view using Oracle Enterprise Manager.
You can use the
EXPLAIN_MVIEW procedure to learn what is possible with a materialized view or potential materialized view. In particular, this procedure enables you to determine:
If a materialized view is fast refreshable
What types of query rewrite you can perform with this materialized view
Whether PCT refresh is possible
Using this procedure is straightforward. You simply call
DBMS_MVIEW.EXPLAIN_MVIEW, passing in as a single parameter the schema and materialized view name for an existing materialized view. Alternatively, you can specify the
SELECT string for a potential materialized view or the complete
VIEW statement. The materialized view or potential materialized view is then analyzed and the results are written into either a table called
MV_CAPABILITIES_TABLE, which is the default, or to an array called
Note that you must run the
utlxmv.sql script prior to calling
EXPLAIN_MVIEW except when you are placing the results in
MSG_ARRAY. The script is found in the
admin directory. It is to create the
MV_CAPABILITIES_TABLE in the current schema. An explanation of the various capabilities is in Table 8-7, and all the possible messages are listed in Table 8-8.
An optional parameter. A client-supplied unique identifier to associate output rows with specific invocations of
The name of an existing materialized view or the query definition or the entire
VIEW statement of a potential materialized view you want to analyze.
The PL/SQL varray that receives the output.
EXPLAIN_MVIEW analyzes the specified materialized view in terms of its refresh and rewrite capabilities and inserts its results (in the form of multiple rows) into
See Also:PL/SQL Packages and Types Reference for further information about the
The following PL/SQL declarations that are made for you in the
DBMS_MVIEW package show the order and datatypes of these parameters for explaining an existing materialized view and a potential materialized view with output to a table and to a VARRAY.
Explain an existing or potential materialized view with output to
DBMS_MVIEW.EXPLAIN_MVIEW (mv IN VARCHAR2, stmt_id IN VARCHAR2:= NULL);
Explain an existing or potential materialized view with output to a VARRAY:
DBMS_MVIEW.EXPLAIN_MVIEW (mv IN VARCHAR2, msg_array OUT SYS.ExplainMVArrayType);
CREATE TABLE MV_CAPABILITIES_TABLE (STMT_ID VARCHAR(30), -- client-supplied unique statement identifier MV VARCHAR(30), -- NULL for SELECT based EXPLAIN_MVIEW CAPABILITY_NAME VARCHAR(30), -- A descriptive name of particular -- capabilities, such as REWRITE. -- See Table 8-7 POSSIBLE CHARACTER(1), -- Y = capability is possible -- N = capability is not possible RELATED_TEXT VARCHAR(2000), -- owner.table.column, and so on related to -- this message RELATED_NUM NUMBER, -- When there is a numeric value -- associated with a row, it goes here. MSGNO INTEGER, -- When available, message # explaining -- why disabled or more details when -- enabled. MSGTXT VARCHAR(2000), -- Text associated with MSGNO SEQ NUMBER); -- Useful in ORDER BY clause when -- selecting from this table.
You can use the
utlxmv.sql script found in the
admin directory to create
Example 8-8 DBMS_MVIEW.EXPLAIN_MVIEW
First, create the materialized view. Alternatively, you can use
EXPLAIN_MVIEW on a potential materialized view using its
SELECT statement or the complete
CREATE MATERIALIZED VIEW cal_month_sales_mv BUILD IMMEDIATE REFRESH FORCE ENABLE QUERY REWRITE AS SELECT t.calendar_month_desc, SUM(s.amount_sold) AS dollars FROM sales s, times t WHERE s.time_id = t.time_id GROUP BY t.calendar_month_desc;
Then, you invoke
EXPLAIN_MVIEW with the materialized view to explain. You need to use the
SEQ column in an
BY clause so the rows will display in a logical order. If a capability is not possible,
N will appear in the
P column and an explanation in the
MSGTXT column. If a capability is not possible for more than one reason, a row is displayed for each reason.
EXECUTE DBMS_MVIEW.EXPLAIN_MVIEW ('SH.CAL_MONTH_SALES_MV'); SELECT capability_name, possible, SUBSTR(related_text,1,8) AS rel_text, SUBSTR(msgtxt,1,60) AS msgtxt FROM MV_CAPABILITIES_TABLE ORDER BY seq;
CAPABILITY_NAME P REL_TEXT MSGTXT --------------- - -------- ------ PCT N REFRESH_COMPLETE Y REFRESH_FAST N REWRITE Y PCT_TABLE N SALES no partition key or PMARKER in select list PCT_TABLE N TIMES relation is not a partitioned table REFRESH_FAST_AFTER_INSERT N SH.TIMES mv log must have new values REFRESH_FAST_AFTER_INSERT N SH.TIMES mv log must have ROWID REFRESH_FAST_AFTER_INSERT N SH.TIMES mv log does not have all necessary columns REFRESH_FAST_AFTER_INSERT N SH.SALES mv log must have new values REFRESH_FAST_AFTER_INSERT N SH.SALES mv log must have ROWID REFRESH_FAST_AFTER_INSERT N SH.SALES mv log does not have all necessary columns REFRESH_FAST_AFTER_ONETAB_DML N DOLLARS SUM(expr) without COUNT(expr) REFRESH_FAST_AFTER_ONETAB_DML N see the reason why REFRESH_FAST_AFTER_INSERT is disabled REFRESH_FAST_AFTER_ONETAB_DML N COUNT(*) is not present in the select list REFRESH_FAST_AFTER_ONETAB_DML N SUM(expr) without COUNT(expr) REFRESH_FAST_AFTER_ANY_DML N see the reason why REFRESH_FAST_AFTER_ONETAB_DML is disabled REFRESH_FAST_AFTER_ANY_DML N SH.TIMES mv log must have sequence REFRESH_FAST_AFTER_ANY_DML N SH.SALES mv log must have sequence REFRESH_PCT N PCT is not possible on any of the detail tables in the materialized view REWRITE_FULL_TEXT_MATCH Y REWRITE_PARTIAL_TEXT_MATCH Y REWRITE_GENERAL Y REWRITE_PCT N PCT is not possible on any detail tables
Table 8-7 lists explanations for values in the
Table 8-7 CAPABILITY_NAME Column Details
||If this capability is possible, Partition Change Tracking (PCT) is possible on at least one detail relation. If this capability is not possible, PCT is not possible with any detail relation referenced by the materialized view.|
||If this capability is possible, complete refresh of the materialized view is possible.|
||If this capability is possible, fast refresh is possible at least under certain circumstances.|
||If this capability is possible, at least full text match query rewrite is possible. If this capability is not possible, no form of query rewrite is possible.|
||If this capability is possible, it is possible with respect to a particular partitioned table in the top level |
PCT is needed to support fast fresh after partition maintenance operations on the table named in the
PCT may also support fast refresh with regard to updates to the table named in the
PCT is also needed to support query rewrite in the presence of partial staleness of the materialized view with regard to the table named in the
When disabled, PCT does not apply to the table named in the
||If this capability is possible, it is possible with respect to a particular partitioned table in the top level |
This capability is needed to support query rewrite against this materialized view in partial stale state with regard to the table named in the
When disabled, query rewrite cannot be supported if this materialized view is in partial stale state with regard to the table named in the
||If this capability is possible, fast refresh from a materialized view log is possible at least in the case where the updates are restricted to |
||If this capability is possible, fast refresh from a materialized view log is possible regardless of the type of update operation, provided all update operations are performed on a single table. If this capability is not possible, fast refresh from a materialized view log may not be possible when the update operations are performed on multiple tables.|
||If this capability is possible, fast refresh from a materialized view log is possible regardless of the type of update operation or the number of tables updated. If this capability is not possible, fast refresh from a materialized view log may not be possible when the update operations (other than |
||If this capability is possible, fast refresh using PCT is possible. Generally, this means that refresh is possible after partition maintenance operations on those detail tables where PCT is indicated as possible.|
||If this capability is possible, full text match query rewrite is possible. If this capability is not possible, full text match query rewrite is not possible.|
||If this capability is possible, at least full and partial text match query rewrite are possible. If this capability is not possible, at least partial text match query rewrite and general query rewrite are not possible.|
||If this capability is possible, all query rewrite capabilities are possible, including general query rewrite and full and partial text match query rewrite. If this capability is not possible, at least general query rewrite is not possible.|
||If this capability is possible, query rewrite can use a partially stale materialized view even in |
Table 8-8 lists the semantics for
Table 8-8 MV_CAPABILITIES_TABLE Column Details
||For PCT capability only: |
|2066||This statement resulted in an Oracle error||Oracle error number that occurred|
|2067||No partition key or
|2068||Relation is not partitioned|
|2069||PCT not supported with multicolumn partition key|
|2070||PCT not supported with this type of partitioning|
|2071||Internal error: undefined PCT failure code||The unrecognized numeric PCT failure code|
|2072||Requirements not satisfied for fast refresh of nested mv|
|2077||Mv log is newer than last full refresh|
|2078||Mv log must have new values|
|2079||Mv log must have
|2080||Mv log must have primary key|
|2081||Mv log does not have all necessary columns|
|2082||Problem with mv log|
|2099||Mv references a remote table or view in the
||Offset from the
|2126||Multiple master sites||Name of the first different node, or |
|2129||Join or filter condition(s) are complex|
|2130||Expression not supported for fast refresh||Offset from the
||The alias name in the select list of the expression in question|
|2150||Select lists must be identical across the
||Offset from the
||The alias name of the first different select item in the |
|2182||PCT is enabled through a join dependency|
|2183||Expression to enable PCT not in
||The unrecognized numeric PCT failure code|
|2184||Expression to enable PCT cannot be rolled up|
|2185||No partition key or
|2187||materialized view on external table|