The refresh approach enables you to keep a set of tables and the materialized views defined on them to be always in sync. It targets the common usage scenario in the data warehouse where both fact tables and their materialized views are partitioned in the same way or their partitions are related by a functional dependency. The DBMS_MVIEW package contains the APIs whose usage is described in this chapter. Similarly, when you request a FORCE method (method => '? For partitioned materialized views, if partition level change tracking is possible, and there are local indexes defined on the materialized view, the out-of-place method also builds the same local indexes on the outside tables. Rather than disallow the new sales transactions, you might choose to insert the sales transactions into the sales table. So an optional WHERE clause is added to the INSERT clause of the MERGE. About Refresh Modes for Materialized Views. end; If truncation and direct load are not feasible, you should use out-of-place refresh when the changes are relatively large. Atomic refresh cannot be guaranteed when refresh is performed on nested views. a bit late to the game, but I found a way to make the original syntax in this question work (I'm on Oracle 11g). To look at the progress of which jobs are on which queue, use: Three views are provided for checking the status of a materialized view: DBA_MVIEWS, ALL_MVIEWS, and USER_MVIEWS. All of the operations associated with data loading are occurring on a separate sales_01_2001 table. How you call those statements. rev2023.4.17.43393. However, the out-of-place refresh enables high materialized view availability during refresh, especially when refresh statements take a long time to finish. Comments. For example, the following specifies that cal_month_sales_mv be completely refreshed and fweek_pscat_sales_mv receive a fast refresh: If the refresh method is not specified, the default refresh method as specified in the materialized view definition is used. For insert operations, fast refresh is used for materialized views containing detailed percentiles. ETL (Extraction, Transformation and Loading) is done on a scheduled basis to reflect changes made to the original source system. PCT refresh recomputes rows in a materialized view corresponding to changed rows in the detail tables. Use Oracle's bulk loader utility or direct-path INSERT (INSERT with the APPEND hint for loads). For PCT to be available, the detail tables must be partitioned. Oracle Database Discussions Rebuild Read-only Materialized view refresh with rowid 735701 Jan 7 2010 edited Jan 7 2010 Hi, I have a 6gb table which there is no primary key. To maintain the materialized view after such operations used to require manual maintenance (see also CONSIDER FRESH) or complete refresh. Data is loaded daily. One approach to removing a large volume of data is to use parallel delete as shown in the following statement: This SQL statement spawns one parallel process for each partition. "About Partition Change Tracking" for more information regarding partition change tracking. For example, every night, week, or month, new data is brought into the data warehouse. Without any existing global indexes, this time window is a matter of a fraction to few seconds. You can verify which partitions are fresh and stale with views such as DBA_MVIEWS and DBA_MVIEW_DETAIL_PARTITION. If PCT refresh is possible, it occurs automatically and no user intervention is required in order for it to occur. In addition, it has the following restrictions: Only materialized join views and materialized aggregate views are allowed, No remote materialized views, cube materialized views, object materialized views are permitted, Not permitted if materialized view logs, triggers, or constraints (except NOT NULL) are defined on the materialized view, Not permitted if the materialized view contains the CLUSTERING clause, Not applied to complete refresh within a CREATE or ALTER MATERIALIZED VIEW session or an ALTER TABLE session, Atomic mode is not permitted. SQL> create materialized view emp1_mv 2 refresh fast 3 on demand 4 with rowid 5 as 6 This UPDATE-ELSE-INSERT operation is often called a merge. When using DBMS_MVIEW.REFRESH with JOB_QUEUES, remember to set atomic to FALSE. For example, suppose the changes have been received for the orders table but not for customer payments. To use the ON STATEMENT refresh mode, a materialized view must be fast refreshable. Thus, processing only the changes can result in a very fast refresh time. Therefore, if you defer refreshing your materialized views, you can either rely on your chosen rewrite integrity level to determine whether or not a stale materialized view can be used for query rewrite, or you can temporarily disable query rewrite with an ALTER SYSTEM SET QUERY_REWRITE_ENABLED = FALSE statement. In a data warehouse environment, referential integrity constraints are normally enabled with the NOVALIDATE or RELY options. The in-place refresh executes the refresh statements directly on the materialized view. In most cases, this can be neglected, because this part of the partitioned table should not be accessed too often. How to refresh Materialized view every workday? It is irrelevant how the compressed partitions are added to the partitioned table. end; Example 7-11 Conditional Inserts with MERGE Statements. However, fast refresh is able to perform significant optimizations in its processing if it detects that only inserts or deletes have been done to the tables, such as: Even more optimal is the separation of INSERT and DELETE. Create the materialized view. Why does the second bowl of popcorn pop better in the microwave? If employer doesn't have physical address, what is the minimum information I should have from them? Fast refresh of your materialized views is usually efficient, because instead of having to recompute the entire materialized view, the changes are applied to the existing data. The required parameters to use this procedure are: The comma-delimited list of materialized views to refresh, The refresh method: F-Fast, P-Fast_PCT, ?-Force, C-Complete. This parameter works with all existing refresh method (F, P, C, ?). Existing materialized view logs cannot be altered to add COMMIT SCN unless they are dropped and recreated. You therefore have to rebuild them: Alternatively, you can choose to create the new compressed table outside the partitioned table and exchange it back. This parameter is only effective when atomic_refresh is set to FALSE. Let us assume that a backup (partition) granularity is on a quarterly base for any quarter, where the oldest month is more than 36 months behind the most recent month. Query USER_MVIEW_DETAIL_SUBPARTITION to access PCT freshness information for subpartitions, as shown in the following: Very often you have multiple materialized views in the database. Oracle tries to balance the number of concurrent refreshes with the degree of parallelism of each refresh. I think you are executing it from php as sql statement. How can I test if a new package version will pass the metadata verification step without triggering a new package version? If any of the materialized views are defined as ON DEMAND refresh (irrespective of whether the refresh method is FAST, FORCE, or COMPLETE), you must refresh them in the correct order (taking into account the dependencies between the materialized views) because the nested materialized view are refreshed with respect to the current contents of the other materialized views (whether fresh or not). "PCT Fast Refresh for Materialized Views: Scenario 1" would also be appropriate if the materialized view was created using the PMARKER clause as illustrated in the following: In this scenario, the first three steps are the same as in "PCT Fast Refresh for Materialized Views: Scenario 1". When a materialized view is created on both base tables with timestamp-based materialized view logs and base tables with commit SCN-based materialized view logs, an error (ORA-32414) is raised stating that materialized view logs are not compatible with each other for fast refresh. If that is not possible, it does a complete refresh. Also adopting the out-of-place mechanism, a new refresh method called synchronous refresh is introduced in Oracle Database 12c, Release 1. Thus, although a given row of the destination table meets the delete condition, if it does not join under the ON clause condition, it is not deleted. Also, Oracle recommends that the refresh be invoked after each table is loaded, rather than load all the tables and then perform the refresh. If set to TRUE, refresh all the dependent materialized views of the specified set of tables based on a dependency order to ensure the materialized views are truly fresh with respect to the underlying base tables. Can a rotating object accelerate by changing shape? To avoid this occurring, Oracle recommends performing a fast refresh immediately after any partition maintenance operation on detail tables for which partition tracking fast refresh is available. Query USER_MVIEW_DETAIL_RELATIONS to access PCT detail table information, as shown in the following: Example 7-5 Verifying Which Partitions are Fresh. As in previous examples, assume that the new data for the sales table is staged in a separate table, new_sales. If there were only foreign-key constraints, the exchange operation would be instantaneous. In a data warehousing environment, assuming that the materialized view has a parallel clause, the following sequence of steps is recommended: An ALTER SESSION ENABLE PARALLEL DML statement. If REFRESH_DEPENDENT is applied to materialized view my_mv, then only materialized views that directly depend on my_mv are refreshed (that is, a materialized view that depends on a materialized view that depends on my_mv will not be refreshed) unless you specify nested => TRUE. PCT-based refresh on a materialized view is enabled only if all the conditions described in "About Partition Change Tracking" are satisfied. If set to FALSE, Oracle can optimize refresh by using parallel DML and truncate DDL on a materialized views. See "About Partition Change Tracking" for PCT requirements. However, the subpartitioning is a list based on the channel attribute. Many data warehouses maintain a rolling window of data. If set to TRUE, then all refreshes are done in one transaction. This parameter works with all existing refresh methods (F, P, C, ?). This section describes the following two typical scenarios where partitioning is used with refresh: Partitioning for Refreshing Data Warehouses: Scenario 1, Partitioning for Refreshing Data Warehouses: Scenario 2. When there have been some partition maintenance operations on the detail tables, this is the only method of fast refresh that can be used. For PCT refresh, if the materialized view is partitioned appropriately, this uses TRUNCATE PARTITION to delete rows in the affected partitions of the materialized view, which is faster than a delete. 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