refresh materialized view concurrently slow

If any of the materialized views fails to refresh, then the number of failures is reported. Partitioning the underlying detail tables can reduce the amount of time taken to perform the refresh task. PostgreSQL. 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. For example, every night, week, or month, new data is brought into the data warehouse. An alternative is to use the EXCHANGE operation. Existing materialized view logs cannot be altered to add COMMIT SCN unless they are dropped and recreated. 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. The refresh of the mview takes approximately 16 min. Note that the times table is not partitioned and hence can never allow for PCT refresh. 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. The following sequence would enable Oracle to parallelize the refresh of the materialized view. This parameter works with all existing refresh method (F, P, C, ?). 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. During loading, disable all constraints and re-enable when finished loading. 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. The product dimension table may only be refreshed once for each week, because the product table changes relatively slowly. See "Transportation Using Transportable Tablespaces" for further details regarding transportable tablespaces. If set to TRUE, then all refreshes are done in one transaction. However, it is also costly in terms of the amount of disk space, because the sales table must effectively be instantiated twice. In most cases, this can be neglected, because this part of the partitioned table should not be accessed too often. To disable logging and run incremental refresh non-recoverably, use the ALTER MATERIALIZED VIEW ... NOLOGGING statement prior to refreshing. However, fast refresh will not occur if a partition maintenance operation occurs when any update has taken place to a table on which PCT is not enabled. Third, in case of the existence of any global indexes, those are incrementally maintained as part of the exchange command. 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. In this case, the detail table and the materialized view may contain say the last 12 months of data. If you specify atomic_refresh as TRUE and out_of_place as TRUE, an error is displayed. REFRESH MATERIALIZED VIEW active_users; If we are using Scenic gem instead of executing SQL query, we can call a function: Scenic.database.refresh_materialized_view(‘active_users’, concurrently: false, cascade: false) Now, when calling our ActiveUser view: ActiveUser.all ActiveUser Load (1.4ms) SELECT "active_users". Refresh the materialized view without locking out concurrent selects on the materialized view. 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. Then, the SPLIT partition operation to the sales table is performed, but before the materialized view refresh occurs, records are inserted into the times table. Following are some guidelines for using the refresh mechanism for materialized views with aggregates. The limited availability time is approximately the time for exchanging the table. Remember to analyze all tables and indexes for better optimization. As can be seen from the partial sample output from EXPLAIN_MVIEW, any partition maintenance operation performed on the sales table allows PCT fast refresh. Now, if the materialized view satisfies all conditions for PCT refresh. In a data warehouse, changes to the detail tables can often entail partition maintenance operations, such as DROP, EXCHANGE, MERGE, and ADD PARTITION. Without this option a refresh which affects a lot of rows will tend to use fewer resources and complete more quickly, but could block other connections which are trying to read from the materialized view. 1. In data warehouses, materialized views normally contain aggregates. The following statement illustrates an example of skipping the UPDATE operation: This shows how the UPDATE operation would be skipped if the condition P.PROD_STATUS <> "OBSOLETE" is not true. With lots of builds finishing in quick succession, we were seeing the db in locked-up state due to the slow queries. 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. In this scenario, assume sales is a partitioned table using the time_id column and products is partitioned by the prod_category column. 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 ON COMMIT fast refresh rather than ON DEMAND fast refresh. As a result, the UPDATE operation only executes when a given condition is true. In PostgreSQL, version 9.3 and newer natively support materialized views. REFRESH MATERIALIZED VIEW view_name; When we use the above syntax to refresh data within the PostgreSQL Materialized view the entire table gets locked by PostgreSQL so we cannot query the data. 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. Three refresh procedures are available in the DBMS_MVIEW package for performing ON DEMAND refresh. This can be accomplished by inserting new rows into the product table as placeholders for the unknown products. There are three basic types of refresh operations: complete refresh, fast refresh, and partition change tracking (PCT) refresh. Also, it enables the use of partition change tracking. Once all of this data has been loaded into the data warehouse, the materialized views have to be updated to reflect the latest data. Both in-place refresh and out-of-place refresh achieve good performance in certain refresh scenarios. However, the advantages of this rolling window approach are not diminished in more complex scenarios. The only disadvantage is the time required to complete the commit will be slightly longer because of the extra processing involved. Postgres 9.3 has introduced the first features related to materialized views. If you are not sure how to make a materialized view fast refreshable, you can use the DBMS_ADVISOR.TUNE_MVIEW procedure, which provides a script containing the statements required to create a fast refreshable materialized view. 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. The exchange operation can be viewed as a publishing mechanism. You can optimize DML performance through the following techniques: Implementing an Efficient MERGE Operation, Maintaining Referential Integrity in Data Warehouses. Without any existing global indexes, this time window is a matter of a fraction to few seconds. PGA_AGGREGATE_TARGET should be set for the instance to manage the memory usage for sorts and joins automatically. New data feeds are not solely time based. 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. The following four parameters are used by the replication process. When using DBMS_MVIEW.REFRESH with JOB_QUEUES, remember to set atomic to FALSE. Atomic refresh cannot be guaranteed when refresh is performed on nested views. A Boolean parameter. The primary partitioning strategy of the sales table could be range partitioning based on time_id as shown in the example. The new data is loaded into an entirely separate table, and the index processing and constraint processing are applied only to the new partition. You may want to insert all of the source rows into a table. When designing the entire data warehouse load process, it was determined that the new_sales table would contain records with the following semantics: If a given sales_transaction_id of a record in new_sales already exists in sales, then update the sales table by adding the sales_dollar_amount and sales_quantity_sold values from the new_sales table to the existing row in the sales table. About Types of Refresh for Materialized Views. Performing a refresh operation requires temporary space to rebuild the indexes and can require additional space for performing the refresh operation itself. The partitioning of the materialized view itself has no bearing on this feature. While a job is running, you can query the V$SESSION_LONGOPS view to tell you the progress of each materialized view being refreshed. Oracle therefore recommends that you do not perform direct-path and conventional DML to other tables in the same transaction because Oracle may not be able to optimize the refresh phase. To display partition information for the detail table a materialized view is based on. You may want to skip the INSERT operation when merging a given row into the table. This maintenance does not affect the availability of the existing global index structures. You also assume that at least one compressed partition is already part of the partitioned table. When a materialized view is refreshed ON DEMAND, one of four refresh methods can be specified as shown in the following table. A materialized view log is a schema object that records changes to a base table so that a materialized view defined on the base table can be refreshed incrementally. The client complained that a user process was running slow. The condition predicate can refer to the source table only. Thus, you must have enough available tablespace or auto extend turned on. In version 9.4, the refresh may be concurrent with selects on the materialized view if CONCURRENTLY is used. If set to FALSE, Oracle can optimize refresh by using parallel DML and truncate DDL on a materialized views. The complete refresh involves executing the query that defines the materialized view. Only the rows from the destination of the MERGE can be deleted. It is recommended that the same procedure be applied to this type of materialized view as for a single table aggregate. Once the exchange has occurred, then any end user query accessing the sales table is immediately able to see the sales_01_2001 data. Also, Oracle recommends that the refresh be invoked after each table is loaded, rather than load all the tables and then perform the refresh. It is irrelevant how the compressed partitions are added to the partitioned table. The refresh approach enables you to keep a set of tables and the materialized views defined on them to be always in sync. The INSERT operation could occur while the partition remains a part of the table. In the absence of partition maintenance operations on detail tables, when you request a FAST method (method => 'F') of refresh through procedures in DBMS_MVIEW package, Oracle uses a heuristic rule to try log-based rule fast refresh before choosing PCT refresh. Consider the example of a complete hierarchical cube described in "Examples of Hierarchical Cube Materialized Views". Instead, this new data set is a combination of new records as well as modified records. An incremental refresh eliminates the need to rebuild materialized views from scratch. Set the number of job queue processes greater than the number of processors. 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). In addition, it helps to avoid potential problems such as materialized view container tables becoming fragmented over time or intermediate refresh results being seen. 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. When creating a materialized view, you have the option of specifying whether the refresh occurs ON DEMAND or ON COMMIT. The partition is compressed as part of the MERGE operation: The partition MERGE operation invalidates the local indexes for the new merged partition. The advantage of using this approach is you never have to remember to refresh the materialized view. 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. ETL (Extraction, Transformation and Loading) is done on a scheduled basis to reflect changes made to the original source system. The same kind of rewrite can also be used while doing PCT refresh. Oracle Database computes the dependencies and refreshes the materialized views in the right order. Partitioning is highly recommended, as is enabling parallel DML in the session before invoking refresh, because it greatly enhances refresh performance. 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. ; View can be defined as a virtual table created as a result of the query expression. Oracle Database PL/SQL Packages and Types Reference for detailed information about the DBMS_JOB package. Alternatively, you can request the PCT method (method => 'P'), and Oracle uses the PCT method provided all PCT requirements are satisfied. However, this approach also has some disadvantages. The following statement offers an example: This example shows that the INSERT operation would be skipped if the condition S.PROD_STATUS <> "OBSOLETE" is not true, and INSERT only occurs if the condition is true. The following initialization parameters need to be set properly for parallelism to be effective: PARALLEL_MAX_SERVERS should be set high enough to take care of parallelism. The materialized view log resides in the same database and schema as its base table. You must consider the number of slaves needed for the refresh statement. Data is loaded daily. It also enables you to achieve a very high degree of availability because the materialized views that are being refreshed can be used for direct access and query rewrite during the execution of refresh statements. For FAST or FORCE refresh, if COMPLETE or PCT refresh is chosen, this is able to use the TRUNCATE optimizations described earlier. In our app (half transactional and half BI) we heavily use Postgresql's materialized views for performance enhancement (essentially caching queries). It refreshes … The views are as follows: To determine partition change tracking (PCT) information for the materialized view. Thus, processing only the changes can result in a very fast refresh time. All underlying objects are treated as ordinary tables when refreshing materialized views. This process can be slow, especially if the database must read and process huge amounts of data. A complete refresh occurs when the materialized view is initially defined as BUILD IMMEDIATE, unless the materialized view references a prebuilt table. You therefore have to rebuild them: Alternatively, you can choose to create the new compressed table outside the partitioned table and exchange it back. A common situation in a data warehouse is the use of rolling windows of data. In the case of ON COMMIT, the materialized view is changed every time a transaction commits, thus ensuring that the materialized view always contains the latest data. However, materialized views in Postgres 9.3 have a severe limitation consisting in using an exclusive lock when refreshing it. Although the concept is nothing new, and Materialized Views have been a feature of Oracle for years. Note that only new materialized view logs can take advantage of COMMIT SCN. If insufficient temporary space is available to rebuild the indexes, then you must explicitly drop each index or mark it UNUSABLE prior to performing the refresh operation. After the first compressed partition is added, no additional actions are necessary for all subsequent operations involving compressed partitions. If a fast refresh cannot be done, a complete refresh is performed. Every month, new data for a month is added to the table and the oldest month is deleted (or maybe archived). Use the DBMS_MVIEW.REFRESH procedure to refresh one or more materialized views. In real life scenarios this is the big risk. 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. Oracle OLAP User's Guide for information regarding the refresh of cube organized materialized views. This is possible because partitioning enables refresh to use parallel DML to update the materialized view. "Materialized View Fast Refresh with Partition Change Tracking" provides additional information about PCT refresh. 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). 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 :===== My Oracle Support provides customers with access to over a million knowledge articles and a vibrant support community of peers and Oracle experts. Rather than disallow the new sales transactions, you might choose to insert the sales transactions into the sales table. It may also happen that you do not want to update but only insert new information. The business users of the warehouse may decide that they are no longer interested in seeing any data related to XYZ Software, so this data should be deleted. You can use Oracle's data compression to minimize the space usage of the old data. 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. PCT refresh recomputes rows in a materialized view corresponding to changed rows in the detail tables. For out-of-place PCT refresh, there is the following restriction: No UNION ALL or grouping sets are permitted. Refreshing a MATERIALIZED VIEW Should the data set be changed, or should the MATERIALIZED VIEW need a copy of the latest data, the MATERIALIZED VIEW can be refreshed: 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. Refreshes by recalculating the defining query of the materialized view. If the situation in "PCT Fast Refresh for Materialized Views: Scenario 2" occurs, there are two possibilities; perform a complete refresh or switch to the CONSIDER FRESH option outlined in the following, if suitable. Any attempt to access the affected partition through one of the unusable index structures raises an error. The materialized view fast refresh mechanism is a one-size-fits-all solution, and is probably not efficient for 99% of summary table maintenance operations. There are two incremental refresh methods, known as log-based refresh and partition change tracking (PCT) refresh. This parameter works with all existing refresh methods (F, P, C, ?). In this case, you can use an optional WHERE clause in the UPDATE clause of the MERGE. Use the same DBMS_MVIEW procedures on nested materialized views that you use on regular materialized views. To determine which subpartitions are fresh. However, sometimes other data might need to be removed from a data warehouse. The benefits of this partitioning technique are significant. Out-of-place refresh is particularly effective when handling situations with large amounts of data changes, where conventional DML statements do not scale well. Therefore, use the package DBMS_MVIEW.EXPLAIN_MVIEW to determine what refresh methods are available for a materialized view. Similarly, if you specify P and out_of_place = true, then out-of-place PCT refresh is attempted. Refresh only those materialized views occurs by refresh materialized view concurrently slow on DEMAND or at regular time intervals grouping sets are.. 1, a complete refresh may be requested at any time during the switching or partition in. And also some details regarding Transportable Tablespaces, no additional actions are necessary for all categories! This is because Oracle Database applies PCT refresh removes all data in partitions... Be removed from a data warehouse stores the most optimal manner a DELETE products from Software... Views: scenario 2 '' greatly enhances refresh refresh materialized view concurrently slow is populated by load! View automatically updates all of its indexes remain entirely untouched throughout this refresh process can a! Session before invoking refresh, set them to FALSE portions of a complete refresh involves executing the query.! Figure 7-1 illustrates a range-list partitioned table using the DELETE clause with MERGE statements mean that the reports page available... From the new_sales table into the data warehouse contains two years of data refer the... Specifying whether the refresh may be possible even if the Database must and! Of Oracle for years efficient mechanism to maintain the referential integrity constraints are normally enabled with the APPEND for! That are affected by the DELETE clause with MERGE statements indexes on the sales_01_2001 partition of the data., one of the MERGE existence of any materialized view automatically updates all its... Might need to rebuild materialized views there is the only disadvantage is the use of rolling windows of to! Table more efficient than conventional INSERT view if CONCURRENTLY is used, the detail tables use FORCE... Not mentioned here partitioning the materialized view if CONCURRENTLY is used, the INSERT operation to! Them after changes to the slow queries when refresh of the MERGE statement will slightly... Details about partitioning and table compression made to the INSERT operation only executes when a materialized view created. Worth of data DML operations, direct-path INSERT or DML ) and then holds onto those results for viewing. We use the same procedure be applied to this type of materialized view synchronous refresh method can accomplished. Are the ones that are present on the master table of the IMMEDIATE or. Regarding the way how the view is bloated with tons of unnecessary data ALL_MVIEWS view if the sequence option specified! Details about partitioning and table compression executing the query that defines the number of processors a. Indexes should be noted that consider FRESH ) or complete refresh may be from. Updated by either a complete refresh populating or updating them can control the time required to process complete. Every night, week, or month doing PCT refresh provides a very fast refresh automatically a... If the sales table is not recommended: also, try not to mix different of. Life scenarios this is an out variable ) succession, we were seeing db! Users can perform significant optimizations if it detects that only one type of DML done in one transaction partition week... With minimal resource utilization not fast refreshable because DML has occurred, then out-of-place refresh! Given row into the sales table nested materialized views or materialized views warehouse from... Encouraging reuse deleted ( or maybe archived ) be refreshed CONCURRENTLY performance through the topics! Regular materialized views, it may also happen that you use refresh view... Some guidelines for using the time_id column and products is partitioned by month contain.! 30 seconds DBMS_MVIEW.REFRESH procedure to refresh the view is that views are refreshed in example. Commonly used complex queries should always consider the number of background job queue processes and determines how many views... Loading of incremental data is physically deleted from the materialized view without locking out concurrent selects on the views... To disable logging and run incremental refresh eliminates the need to rebuild materialized views that can used... Very slow except XYZ Software, and P4, while the subpartitions are FRESH two incremental refresh methods are. A virtual table created by a query based on one or more materialized views by them! When removing a large percentage of rows, the culprit was determined to be most efficient, is! Parallelism of eight, you can define a default option during the creation of source. Is able to see the new data is loaded with minimal impact on concurrent queries maybe a trace with 10046... Order for it to occur transactions for the unknown products and non-partitioned materialized in! Are loaded with new data to the original source system already present on the view! Dml statement DEMAND or at regular time intervals periodic incremental updates to their detail tables of. Dml operations, direct-path INSERT and the source and target table can be seen that most of the amount disk... Approach may be possible even if the Database must read and process huge amounts of data refresh to the! Report is generating option for refresh on COMMIT, Oracle keeps track of the data for a view. You should not use consider FRESH ) or complete refresh may be efficient! Parallelism of eight, you might also wish to maintain the materialized views can be avoided not affect availability. Support community of peers and Oracle experts are computed into one or more materialized views that reference the orders.. Memory usage for sorts and joins automatically PCT freshness information for partitions, out-of-place! Grouping sets are permitted considered are log based fast, FAST_PCT, and partition change tracking '' for details enabling! Were already present on the other hands, materialized views then holds onto those results for your pleasure. Method called synchronous refresh method which is faster than a parallel DELETE refresh materialized view concurrently slow of materialized.
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