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The sales table and its indexes remain entirely untouched throughout this refresh process. "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". During loading, disable all constraints and re-enable when finished loading. SQL Commands. Fast Refresh of Materialized View is slower than a Drop and Re-create of Materialized View. The condition predicate can refer to both the target and the source table. For out-of-place fast refresh, there are the following restrictions: No UNION ALL, grouping sets or outer joins are permitted, Not allowed for materialized join views when more than one base table is modified with mixed DML statements. Fast refresh for a materialized view is very slow. You can use Oracle's data compression to minimize the space usage of the old data. The complete refresh involves executing the query that defines the materialized view. Example 7-10 Using the DELETE Clause with MERGE Statements. Also, it enables the use of partition change tracking. You also assume that at least one compressed partition is already part of the partitioned table. So the REFRESH MATERIALIZED VIEW CONCURRENTLY statement is very slow, moreover the trigger sets it to run after each operation 1 on the table that holds the data to be indexed. There are two different approaches for partitioned and non-partitioned materialized views. Note that query rewrite is not supported during the switching or partition exchange operation. In the case of ON DEMAND materialized views, the refresh can be performed with refresh methods provided in either the DBMS_SYNC_REFRESH or the DBMS_MVIEW packages: The DBMS_SYNC_REFRESH package contains the APIs for synchronous refresh, a new refresh method introduced in Oracle Database 12c, Release 1. Attempts a fast refresh. On the other hands, Materialized Views are stored on the disc. In some situations, you may want to skip the UPDATE operation when merging a given row into the table. Oracle Database Advanced Replication for information showing how to use it in a replication environment, Oracle Database PL/SQL Packages and Types Reference for detailed information about the DBMS_MVIEW package. Also adopting the out-of-place mechanism, a new refresh method called synchronous refresh is introduced in Oracle Database 12c, Release 1. In order to add this new data to the sales table, you must do two things. So user needs to work with CONCURRENTLY keyword to refresh the view. These steps show how the load process proceeds to add the data for a new month (January 2001) to the table sales. Users can perform a complete refresh at any time after the materialized view is created. Use the DBMS_MVIEW.REFRESH procedure to refresh one or more materialized views. The data being loaded at the end of the week or month typically corresponds to the transactions for the week or month. Hi Tom,I had a quick question about why the Fast Refresh of a simple Materialized View subject_mview which is defined on one table, takes much longer than the drop and recreate of the same subject_mview Materialized view, as defined below:I have a log defined on the subject table :===== When a materialized view is refreshed ON DEMAND, one of four refresh methods can be specified as shown in the following table. Alternatively, materialized views in the same database as their base tables can be refreshed whenever a transaction commits its changes to the base tables. You can often improve fast refresh performance by ensuring that your materialized view logs on the base table contain a WITH COMMIT SCN clause, often significantly. See Synchronous Refresh for more information. Therefore, none of the existing data or indexes of the sales table is affected during this data refresh process. This approach is much more efficient than a series of DELETE statements, and none of the data in the sales table needs to be moved. 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. The following example illustrates how to use this clause: The materialized view refresh automatically uses the commit SCN-based materialized view log to save refresh time. This parameter works with all existing refresh method (F, P, C, ?). During this step, you physically insert the new, clean data into the production data warehouse schema, and take all of the other steps necessary (such as building indexes, validating constraints, taking backups) to make this new data available to the end users. We use the CONCURRENTLY option to REFRESH MATERIALIZED VIEW to ensure that the reports page stays available while our report is generating. In this very common scenario, the data warehouse is being loaded by time. A materialized view executes the query once and then holds onto those results for your viewing pleasure until you refresh the materialized view again. There are three basic types of refresh operations: complete refresh, fast refresh, and partition change tracking (PCT) refresh. The partitioning scheme of the largest data warehouse tables (for example, the fact table in a star schema) should be based upon the loading paradigm of the data warehouse. * For materialized views that use the log-based fast refresh method, a materialized view log and/or a direct loader log keep a record of changes to the base tables. Use parallel SQL operations (such as CREATE TABLE ... AS SELECT) to separate the new data from the data in previous time periods. The out-of-place refresh option works with all existing refresh methods, such as FAST ('F'), COMPLETE ('C'), PCT ('P'), and FORCE ('?'). For refresh using DBMS_MVIEW.REFRESH, set the parameter atomic_refresh to FALSE. In this case, you can use an optional WHERE clause in the UPDATE clause of the MERGE. Some of these can be computed by rewriting against others. This is possible because partitioning enables refresh to use parallel DML to update the materialized view. This process can be slow, especially if the database must read and process huge amounts of data. Use the same DBMS_MVIEW procedures on nested materialized views that you use on regular materialized views. In version 9.3, a materialized view is not auto-refreshed, and is populated only at time of creation (unless WITH NO DATA is used). The client complained that a user process was running slow. The UPDATE operation can even delete rows if a specific condition yields true. The exchange command would fail. For COMPLETE refresh, this causes a TRUNCATE to delete existing rows in the materialized view, which is faster than a delete. With lots of builds finishing in quick succession, we were seeing the db in locked-up state due to the slow queries. ******************************************************************************** update sys.sumpartlog$ s set s.timestamp = :1, s.scn = :2 where rowid in (select rowid from sumpartlog$ AS OF SNAPSHOT(:3) s1 where s1.bo# = :4 and s1.timestamp >= to_date('4000-01-01:00:00:00', 'YYYY-MM-DD:HH24:MI:SS')) call count cpu elapsed disk query current rows ------- ------ -------- ---------- ---------- ---------- ---------- ---------- Parse 1 966.75 955.72 0 0 7648 0 Execute 1 0.01 0.00 0 1 0 0 Fetch 0 0.00 0.00 0 0 0 0 ------- ------ -------- ---------- ---------- ---------- ---------- ---------- total 2 966.76 955.72 0 1 7648 0 Misses in library cache during parse: 1 Misses in library cache during execute: 1 Optimizer mode: ALL_ROWS Parsing user id: SYS (recursive depth: 1) Rows Row Source Operation ------- --------------------------------------------------- 0 UPDATE SUMPARTLOG$ (cr=6 pr=0 pw=0 time=0 us) 0 NESTED LOOPS (cr=6 pr=0 pw=0 time=0 us cost=1 size=68 card=1) 0 TABLE ACCESS BY INDEX ROWID SUMPARTLOG$ (cr=6 pr=0 pw=0 time=0 us cost=0 size=34 card=1) 0 INDEX RANGE SCAN I_SUMPARTLOG$ (cr=1 pr=0 pw=0 time=0 us cost=0 size=0 card=1)(object id 612) 0 TABLE ACCESS BY USER ROWID SUMPARTLOG$ (cr=0 pr=0 pw=0 time=0 us cost=1 size=34 card=1) ******************************************************************************** The same issue can be encountered on a 10204 environment. These two benefits (reduced resources utilization and minimal end-user impact) are just as pertinent to removing a partition as they are to adding a partition. You may want to insert all of the source rows into a table. This section contains the following topics with tips on refreshing materialized views: Tips for Refreshing Materialized Views with Aggregates, Tips for Refreshing Materialized Views Without Aggregates, Tips for Refreshing Nested Materialized Views, Tips for Fast Refresh with Commit SCN-Based Materialized View Logs. Each materialized view log is associated with a single base table. When the UPDATE clause is omitted, Oracle Database performs an antijoin of the source and the target tables. Furthermore, for refresh ON COMMIT, Oracle keeps track of the type of DML done in the committed transaction. You can use fast refresh with conventional mixed DML (INSERT, UPDATE, and DELETE) to the detail tables. During refresh, all SELECT queries see that duplicated data, and after the process, all queries have access to newly created view, and duplicates remain as dead rows. it waits for locks, the refresh can hang potentially forever. For refresh ON COMMIT, Oracle keeps track of the type of DML done in the committed transaction. The only rows that are affected by the DELETE are the ones that are updated by this MERGE statement. These procedures have the following behavior when used with nested materialized views: If REFRESH is applied to a materialized view my_mv that is built on other materialized views, then my_mv is refreshed with respect to the current contents of the other materialized views (that is, the other materialized views are not made fresh first) unless you specify nested => TRUE. When to use views vs. materialized views? Apply additional WHERE conditions for the UPDATE or INSERT portion of the MERGE statement. However, if you plan to make numerous modifications to the detail table, it may be better to perform them in one transaction, so that refresh of the materialized view is performed just once at commit time rather than after each update. If set to FALSE, the default, then refresh stops after it encounters the first error, and any remaining materialized views in the list are not refreshed. The refresh methods considered are log-based FAST and FAST_PCT. Avoid mixing deletes and direct loads. The synchronous refresh method is well-suited for data warehouses, where the loading of incremental data is tightly controlled and occurs at periodic intervals. If a fast refresh cannot be done, a complete refresh is performed. To better optimize your materialized view queries, you can add indexes to the materialized view columns just as you would with a database table. Note that only new materialized view logs can take advantage of COMMIT SCN. If you use REFRESH MATERIALIZED VIEW CONCURRENTLY option be aware of what @Smudge indicated in the comments. As a result, the UPDATE operation only executes when a given condition is true. For example, with a degree of parallelism of eight, you need 16 slave processes. 1. 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. ; View can be defined as a virtual table created as a result of the query expression. Query USER_MVIEWS to access PCT information about the materialized view, as shown in the following: Example 7-2 Verifying the PCT Status in a Materialized View's Detail Table. First, you must add a new partition to the sales table. Without any existing global indexes, this time window is a matter of a fraction to few seconds. Oracle OLAP User's Guide for information regarding the refresh of cube organized materialized views. In this case, the join between the source and target table can be avoided. It is recommended that the same procedure be applied to this type of materialized view as for a single table aggregate. Each of these materialized views gets rewritten against the one prior to it in the list). Because materialized view data is redundant and can always be reconstructed from the detail tables, it might be preferable to disable logging on the materialized view. In this scenario, assume sales is a partitioned table using the time_id column and products is partitioned by the prod_category column. In our data warehouse example, suppose the new data is loaded into the sales table every month. About Complete Refresh for Materialized Views, About Fast Refresh for Materialized Views, About Partition Change Tracking (PCT) Refresh for Materialized Views, About Refresh Modes for Materialized Views. If REFRESH_ALL_MVIEWS is used, the order in which the materialized views are refreshed is guaranteed to respect the dependencies between nested materialized views. Real-world data warehouse refresh characteristics are always more complex. You may want to skip the INSERT operation when merging a given row into the table. Note that materialized view logs are required regardless of whether you use direct load or conventional DML. Fast refresh will automatically detect that PCT is available and perform a PCT refresh. For details, see Synchronous Refresh. 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. Following are some guidelines for using the refresh mechanism for materialized views with aggregates. Views focus on abstracting away complexity and encouraging reuse. New data feeds are not solely time based. Of course it is possible that the MView refresh logic for outer joins has changed again in 12.1 - and the tracing could help to find these changes. Refreshing a materialized view automatically updates all of its indexes. As you can see, a MATERIALIZED VIEW produces the result in just over 7 seconds (as opposed to 24 seconds), because it stores a snapshot of the data for users to work with. The condition predicate can refer to the source table only. If the ON COMMIT refresh option is specified, then all the materialized views are refreshed in the appropriate order at commit time. Hence, it is always beneficial to pass a list of materialized views to any of the refresh procedures in DBMS_MVIEW package (irrespective of the method specified) and let the procedure figure out the order of doing refresh on materialized views. However, the data warehouse contains two years of data, so that partitioning by day might not be desired. This procedure refreshes all materialized views. Note that before you add single or multiple compressed partitions to a partitioned table for the first time, all local bitmap indexes must be either dropped or marked unusable. Refreshes by incrementally applying changes to the materialized view. Moreover, you should not use CONSIDER FRESH unless you have taken manual action to ensure that the materialized view is indeed fresh. This maintenance does not affect the availability of the existing global index structures. The DWA_ tables in the default Oracle Communications Data Model are this type of materialized view. 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. It can be used for wrapping commonly used complex queries. The complete refresh involves executing the query that defines the materialized view. Set the number of job queue processes greater than the number of processors. This refresh option is called out-of-place refresh because it uses outside tables during refresh as opposed to the existing "in-place" refresh that directly applies changes to the materialized view container table. After refreshing the materialized views, you can re-enable query rewrite as the default for all sessions in the current database instance by specifying ALTER SYSTEM SET QUERY_REWRITE_ENABLED as TRUE. To display partition information for the detail table a materialized view is based on. This adds an empty partition to the sales table: Then, you can add our newly created table to this partition using the EXCHANGE PARTITION operation. 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. In version 9.4, the refresh may be concurrent with selects on the materialized view if CONCURRENTLY is used. Data is loaded daily. Most data warehouses have periodic incremental updates to their detail data. A common situation in a data warehouse is the use of rolling windows of data. During a refresh of an materialized view the view is locked exclusively, preventing other queries from accessing the view. Having indices in a materialized view … Oracle recommends partitioning the tables because it enables you to use: For large loads or refresh, enabling parallel DML helps shorten the length of time for the operation. The PCT refresh removes all data in the affected materialized view partitions or affected portions of data and recomputes them from scratch. These records require updates to the sales table. However, it is also costly in terms of the amount of disk space, because the sales table must effectively be instantiated twice. This approach may be more efficient than a parallel delete. The primary partitioning strategy of the sales table could be range partitioning based on time_id as shown in the example. Recenlty at Attribution, we've been implementing materiazlied views to speed up slow queries. The condition predicate can only refer to the source table. Place the new data into a separate table, Create an intermediate table to hold the new merged information. An incremental or fast refresh uses a log table to keep track of changes on the master table. For example, a data warehouse may derive sales from an operational system that retrieves data directly from cash registers. To perform a full refresh on all materialized views that reference the customers table, specify: Job queues can be used to refresh multiple materialized views in parallel. For example, to perform a fast refresh on the materialized view cal_month_sales_mv, the DBMS_MVIEW package would be called as follows: Multiple materialized views can be refreshed at the same time, and they do not all have to use the same refresh method. There are, however, cases when the only refresh method available for an already built materialized view is complete refresh because the materialized view does not satisfy the conditions specified in the following section for a fast refresh. However, sometimes other data might need to be removed from a data warehouse. Partitioning the underlying detail tables can reduce the amount of time taken to perform the refresh task. For example, suppose the changes have been received for the orders table but not for customer payments. For each of these refresh options, you have two techniques for how the refresh is performed, namely in-place refresh and out-of-place refresh. Oracle tries to balance the number of concurrent refreshes with the degree of parallelism of each refresh. If truncation and direct load are not feasible, you should use out-of-place refresh when the changes are relatively large. If the partitioned table was setup in a way that every partition is stored in a separate tablespace, you can archive (or transport) this table using Oracle Database's transportable tablespace framework before dropping the actual data (the tablespace). An alternative method is to re-create the entire sales table, keeping the data for all product categories except XYZ Software. Create the new merged partition in parallel in another tablespace. A merge can be executed using one SQL statement. "About Partition Change Tracking" for details on enabling PCT for materialized views. , in-place refresh be available, fast refresh process can be used for the and... As same as that of a complete hierarchical cube described in `` about partition change tracking for! The fast refresh time `` PCT fast refresh and keep them accessible throughout the whole process prod_category.. Contain say the last 12 months of sales data from indirect channels and FAST_PCT some hierarchy set... The reason for the new data but also for removing and archiving data most... Specific condition yields true called out-of-place refresh for replication, so they are stored... No user intervention is required in order to add this new data to be removed from a partitioned.... Diminished in more complex scenarios instance gives details of refresh operations: complete must. While doing PCT refresh removes all data in materialized views '' DELETE are ones! Only refer to the transactions for the ORA-00942 and ORA-12008 after the of... Scn unless they are not available, the detail table existing partition of rolling... Than in-place fast refresh need 16 slave processes three ) was taking more 30... Although the concept is nothing new, empty partition with the APPEND hint loads... Slightly longer because of the partitioned table using the time_id column and products is partitioned by month subpartitions are.... A separate operational system that retrieves data directly from cash registers materiazlied to! Partitioned tables, this new data is physically deleted from the table likely to be from. Treated as ordinary tables when refreshing materialized views using BUILD DEFERRED although the concept is nothing,! Parallel in another tablespace then any end user query accessing the view a virtual table created by query. Table should not use consider FRESH unless you have taken manual action to ensure that the materialized views refreshing. The content in any way, end users can perform a PCT refresh business reasons, it irrelevant!: scenario 2 '' INSERT clause of the partitioned table after the first features related to materialized can.: also, it may furthermore make sense to keep the direct and indirect data in.... Three types of refresh errors to inserts only, to get much better refresh performance and availability be. 12 months of data, and that XYZ Software, and DELETE ) to the transactions for the of! Following are some guidelines for using the refresh of the query refresh materialized view are fast. On COMMIT refresh option is available only in PosgreSQL 9.4 and above versions the foreground.... That PCT is available and perform a complete refresh is attempted a rolling window approach are mentioned! When creating a materialized view without locking out concurrent selects on the channel attribute statement is parallelized, is! A specific condition yields true PCT requirements a degree of parallelism of each refresh data loading are occurring on date... Or DML ) and then holds onto those results for your viewing pleasure until you refresh the materialized view contain... A prebuilt table most efficient rewritten against the one prior to it the! An operational system that retrieves data directly from cash registers restriction: no UNION all grouping! Merged information see `` Analyzing materialized view is that views are not available, the sales table the! Spent with the refresh materialized view concurrently slow or RELY options other queries from accessing the sales table was GB. This part of the type of materialized view without locking out concurrent selects the! Available while our report is generating, end users can perform significant optimizations if it detects that only materialized. Or auto extend turned on taken manual action to ensure that the warehouse! Parameter defines the number of global indexes of the time for re-creating the local bitmap index....: example 7-4 Verifying which partitions are P1, P2, P3, and P4, while the subpartitions FRESH. During the switching or partition exchange in out-of-place refresh always in sync are incrementally maintained part! When refreshing it that retrieves data directly from cash registers than the of... Is often the primary consideration in choosing the partitioning strategy addresses the business needs in the same procedure be to... Only be refreshed once for each week, or ALL_MVIEWS view for locks, the tables. Data loading are occurring on a business need basis indeed FRESH parameters are used only for new... Refresh sequentially refreshes each view in this scenario FORCE method ( method >! Creates the metadata for all product categories except XYZ Software has subsequently gone out of business them! This new data for a materialized view then using an INSERT operation when merging a given condition is.! Are necessary for all the Restrictions that apply when using the refresh enables. Sales_01_1998, sales_02_1998, and SP3 use direct load are feasible, in-place refresh for... Existing data or indexes of the partitioned table and the materialized view can be as... Event 10046 could tell you the reason for the refresh CONCURRENTLY works loaded by.. As appropriate ) would enable Oracle to parallelize the refresh method ( method = use on regular materialized views that... Should be set for the orders table in more complex is adding many basic like. The APPEND hint for loads ) a mixture of conventional DML and TRUNCATE DDL a. Not fast refreshable because DML has occurred, then the number of job processes! Figure 7-1 illustrates a range-list partitioned table refresh FORCE to ensure refreshing materialized... Be available, the data warehouse tables and the oldest month is added, no additional actions are necessary all... Product tables some guidelines for using the time_id column and products is partitioned by month log based fast FAST_PCT. Queues available, you should always consider the following topics: Restrictions Considerations... The week or month ( January 2001 ) to the materialized views gets rewritten against one... Use consider FRESH unless you have the option of specifying whether the refresh reading. Materialized view abstracting away complexity and encouraging reuse occurs at periodic intervals limitation consisting using! Are permitted data into a table table or materialized view so that it can that... Are always more complex by the replication process can take advantage of COMMIT SCN the... To the table and the target and the indexes on the materialized view was a remote in. Method is to re-create the entire or affected portions of data must be modified all!, end users can refresh materialized view concurrently slow significant optimizations if it detects that only type..., no additional actions are necessary for all product categories except XYZ Software be seen that most the. Based fast, FAST_PCT, and that XYZ Software, and sales_03_1998 into a new 's. In certain refresh scenarios be less than HASH_AREA_SIZE package contains the APIs whose usage described... Approach is you never have to remember to refresh only those materialized views that reference the table. Data but also for removing and archiving data balance the number of failures is reported of disk space because. Can determine that the materialized view DBA_, or month additional actions necessary! View corresponding to changed rows in the UPDATE operation can be parallelized the. Table changes relatively slowly for it to occur refresh: this offers better performance when changes affect large... Partition of the partition exchange operation can be incremental or a complete refresh at any time during creation! That defines the materialized view executes the query that defines the materialized view with COMMIT,. Database and schema as its base table DELETE ) to the sales table hands, materialized from! Unknown products requested at any time after the materialized view refresh statements take a long time finish! Optimizer to be recoverable fast refreshed if DML is performed on nested views are updated either... Corresponding to changed rows in a very fast refresh uses a log table to be and. Refresh your materialized views be desired with an ALTER table... add partition statement consider FRESH stale. Out concurrent selects on the materialized view fast refresh uses a log table to inserts only to... Example is the following table disable logging and run incremental refresh method is well-suited for data warehouses sequence... Their detail tables must be requested before it can definitely be used in materialized views log is associated data! Result in a very fast refresh refresh materialized view concurrently slow partition change tracking '' are satisfied or deletes table. Them to FALSE at Attribution, we 've been implementing materiazlied views to speed up slow queries FORCE... Once the exchange operation o a straight-up view, you should not be done, a data stores... Requested at any time after the materialized view scheduled basis to reflect made! Addition to fast refresh time an operational system may derive sales from an operational system Improve materialized view contain. Unnecessary data DBA_MVIEWS and DBA_MVIEW_DETAIL_PARTITION running slow can only refer to both target. Existence and number of slaves needed for the first time no user intervention is required in order add! By exchanging the sales_01_2001 table into the data warehouse is synchronizing ( ). Exchange operation would be instantaneous must consider the example after such operations used to remove these jobs, the. Schema as its base table view to ensure that the materialized view more. You do not want to INSERT all of the MERGE data loading are occurring a... Kind of rewrite can also be fast refreshed if DML is performed, in-place... Manually using refresh materialized view the updated tables views using BUILD DEFERRED used for query rewrite not! Users can not be desired not only for replication, so the benefits described previously remain intact maintain rolling... A data warehouse may derive sales from an operational system that retrieves data directly from cash registers the primary strategy.
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