The following example demonstrates INSERT-only with UPDATE-only functionality: The following statement illustrates an example of omitting an UPDATE: When the INSERT clause is omitted, Oracle Database performs a regular join of the source and the target tables. However, the data warehouse contains two years of data, so that partitioning by day might not be desired. To remove these jobs, use the DBMS_JOB.REMOVE procedure. Also adopting the out-of-place mechanism, a new refresh method called synchronous refresh is introduced in Oracle Database 12c, Release 1. If you specify atomic_refresh as TRUE and out_of_place as TRUE, an error is displayed. Each subpartition can now be loaded independently of each other (for each distinct channel) and added in a rolling window operation as discussed before. During loading, disable all constraints and re-enable when finished loading. Use INSERT to add the new data to an existing partition. About ON COMMIT Refresh for Materialized Views, About Manual Refresh Using the DBMS_MVIEW Package, Refreshing Specific Materialized Views with REFRESH, Refreshing All Materialized Views with REFRESH_ALL_MVIEWS, Refreshing Dependent Materialized Views with REFRESH_DEPENDENT. This would give us up to date indexes but would introduce extra complexity and would slow down updates. Table 7-1 details the refresh options. In this refresh method, the user does not directly modify the contents of the base tables but must use the APIs provided by the synchronous refresh package that will apply these changes to the base tables and materialized views at the same time to ensure their consistency. The DWA_ tables in the default Oracle Communications Data Model are this type of materialized view. Performing a refresh operation requires temporary space to rebuild the indexes and can require additional space for performing the refresh operation itself. Oracle Database applies PCT refresh if it can determine that the materialized view has sufficient information to support PCT for all the updated tables. 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. Refresh the materialized view without locking out concurrent selects on the materialized view. First, you can physically delete all data from the database by dropping the partition containing the old data, thus freeing the allocated space: Also, you can exchange the old partition with an empty table of the same structure; this empty table is created equivalent to steps 1 and 2 described in the load process. The basic difference between View and Materialized View is that Views are not stored physically on the disk. To make queues available, you must set the JOB_QUEUE_PROCESSES parameter. 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. A complete refresh occurs when the materialized view is initially defined as BUILD IMMEDIATE, unless the materialized view references a prebuilt table. 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. For example, a data warehouse may derive sales from an operational system that retrieves data directly from cash registers. Next, the oldest partition is dropped or truncated. In a data warehouse environment, referential integrity constraints are normally enabled with the NOVALIDATE or RELY options. Thus, you must have enough available tablespace or auto extend turned on. As a result, the INSERT operation only executes when a given condition is true. Views allow you to interact with the result of a query as if it were a table itself, but they do not provide a performance benefit, as the underlying query is still executed, perfect for sharing logic but still having real-time access to the source data. Refreshes by incrementally applying changes to the materialized view. For example, the following is not recommended: Also, try not to mix different types of conventional DML statements if possible. Refresh statistics can … If set to FALSE, then each of the materialized views is refreshed non-atomically in separate transactions. For PCT to be available, the detail tables must be partitioned. This can be a very time-consuming process, especially if there are huge amounts of data to be read and processed. This approach may be more efficient than a parallel delete. Quick intro to materialized views. Example 7-9 Conditional Inserts with MERGE Statements. Users can perform a complete refresh at any time after the materialized view is created. Since PostgreSQL 9.4 there is an CONCURRENTLY option for REFRESH MATERIALIZED VIEWS. In addition, it helps to avoid potential problems such as materialized view container tables becoming fragmented over time or intermediate refresh results being seen. Rather than disallow the new sales transactions, you might choose to insert the sales transactions into the sales table. When the UPDATE clause is omitted, Oracle Database performs an antijoin of the source and the target tables. Each has its own unique set of parameters. The partitioning scheme of the data warehouse is often crucial in determining the efficiency of refresh operations in the data warehouse load process. During a refresh of an materialized view the view is locked exclusively, preventing other queries from accessing the view. It is irrelevant how the compressed partitions are added to the partitioned table. Postgres 9.3 has introduced the first features related to materialized views. Example 7-11 Unconditional Inserts with MERGE Statements. For warehouse refresh, set them to FALSE, 0,0,0. Using a single INSERT statement (which can be parallelized), the product table can be altered to reflect the new products: Occasionally, it is necessary to remove large amounts of data from a data warehouse. 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. If set to TRUE, the number_of_failures output parameter is set to the number of refreshes that failed, and a generic error message indicates that failures occurred. These examples are a simplification of the data warehouse rolling window load scenario. Not all materialized views may be fast refreshable. 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. For unique constraints (such as the unique constraint on sales_transaction_id), you can use the UPDATE GLOBAL INDEXES clause, as shown previously. Refreshes by recalculating the defining query of the materialized view. See Synchronous Refresh for more information. 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. In data warehouses, materialized views normally contain aggregates. "About Partition Change Tracking" for details on enabling PCT for materialized views. This type of materialized view can also be fast refreshed if DML is performed on the detail table. And here comes VACUUM mechanism that is used to remove all dead rows from the table or materialized view. 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. When a materialized view is refreshed ON DEMAND, one of four refresh methods can be specified as shown in the following table. 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). Each of these materialized views gets rewritten against the one prior to it in the list). For fast refresh, create materialized view logs on all detail tables involved in a materialized view with the ROWID, SEQUENCE and INCLUDING NEW VALUES clauses. The refresh of the mview takes approximately 16 min. This is shown in "PCT Fast Refresh for Materialized Views: Scenario 2". This is possible because partitioning enables refresh to use parallel DML to update the materialized view. An important decision to make before performing a refresh operation is whether the refresh needs to be recoverable. 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. So an optional WHERE clause is added to the INSERT clause of the MERGE. A common situation in a data warehouse is the use of rolling windows of data. Place the new data into a separate table, Create an intermediate table to hold the new merged information. it waits for locks, the refresh can hang potentially forever. Beginning with Oracle Database 12c Release 1, a new refresh option is available to improve materialized view refresh performance and availability. This rebuilding is additional overhead. 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. 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. In terms of availability, out-of-place refresh is always preferable. 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. 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. It’s the way how the view is bloated with tons of unnecessary data. About Types of Refresh for Materialized Views. To display partition information for the detail table a materialized view is based on. Instead, this new data set is a combination of new records as well as modified records. The out-of-place refresh creates one or more outside tables and executes the refresh statements on the outside tables and then switches the materialized view or affected materialized view partitions with the outside tables. See "About Partition Change Tracking" for PCT requirements. A complete refresh occurs when the materialized view is initially created when it is defined as BUILD IMMEDIATE, unless the materialized view references a prebuilt table or is defined as BUILD DEFERRED. The partitions are P1, P2, P3, and P4, while the subpartitions are SP1, SP2, and SP3. An incremental refresh eliminates the need to rebuild materialized views from scratch. Example 7-10 Using the DELETE Clause with MERGE Statements. ETL (Extraction, Transformation and Loading) is done on a scheduled basis to reflect changes made to the original source system. 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. The refresh approach enables you to keep a set of tables and the materialized views defined on them to be always in sync. It may also happen that you do not want to update but only insert new information. This parameter is only effective when atomic_refresh is set to FALSE. This would really only be an issue for large and frequently updated data sets. Alternatively, you can request the PCT method (method => 'P'), and Oracle uses the PCT method provided all PCT requirements are satisfied. Partitioning the materialized view also helps refresh performance as refresh can update the materialized view using parallel DML. REFRESH MATERIALIZED VIEW CONCURRENTLY view_name; Fast refresh automatically performs a PCT refresh as it is the only fast refresh possible in this scenario. 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 advantage of using this approach is you never have to remember to refresh the materialized view. ******************************************************************************** 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. While a job is running, you can query the V$SESSION_LONGOPS view to tell you the progress of each materialized view being refreshed. For example, suppose that most of data extracted from the OLTP systems will be new sales transactions. None of the indexes on the remaining 46 GB of data must be modified at all. 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. This is because Oracle Database can perform significant optimizations if it detects that only one type of change has been done. On the other hands, Materialized Views are stored on the disc. 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. A complete refresh may be requested at any time during the life of any materialized view. If then in turn the SQL query on the foreign database server hangs, e.g. In some data warehouse applications, it is not allowed to add new rows to historical information, but only to update them. Without any existing global indexes, this time window is a matter of a fraction to few seconds. A typical constraint would be: If the partitioned table sales has a primary or unique key that is enforced with a global index structure, ensure that the constraint on sales_pk_jan01 is validated without the creation of an index structure, as in the following: The creation of the constraint with ENABLE clause would cause the creation of a unique index, which does not match a local index structure of the partitioned table. In this case, the detail table and the materialized view may contain say the last 12 months of data. In the case of full refresh, this requires temporary sort space to rebuild all indexes during refresh. Partitioning is useful not only for adding new data but also for removing and archiving data. 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. In real life scenarios this is the big risk. An alternative to specifying the materialized views to refresh is to use the procedure DBMS_MVIEW.REFRESH_ALL_MVIEWS. 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: Fast refresh for a materialized view is very slow. The alert log for the instance gives details of refresh errors. This offers better availability than in-place PCT refresh. When there have been some partition maintenance operations on the detail tables, this is the only method of fast refresh that can be used. 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. Alternatively, materialized views in the same database as their base tables can be refreshed whenever a transaction commits its changes to the base tables. All of the operations associated with data loading are occurring on a separate sales_01_2001 table. If many changes happening and many queries running on master table simultaneously with refresh time,then again it will slow down the materialized view refresh The performance of source and target database and network utlization should also be checked If the materialized view is being refreshed currently, you can check the progress using There are three basic types of refresh operations: complete refresh, fast refresh, and partition change tracking (PCT) refresh. Use parallel SQL operations (such as CREATE TABLE ... AS SELECT) to separate the new data from the data in previous time periods. 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. This parameter works with all existing refresh methods (F, P, C, ?). Therefore, use the package DBMS_MVIEW.EXPLAIN_MVIEW to determine what refresh methods are available for a materialized view. Only the new month's worth of data must be indexed. In some data warehousing environments, you might want to insert new data into tables in order to guarantee referential integrity. Query USER_MVIEW_DETAIL_PARTITION to access PCT freshness information for partitions, as shown in the following: Example 7-4 Verifying Which Subpartitions are Fresh. Similarly, when you request a FORCE method (method => '? This section illustrates examples of determining the PCT and freshness information for materialized views and their detail tables. The best refresh method is chosen. And, if there are other fresh materialized views available at the time of refresh, it can go directly against them as opposed to going against the detail tables. This would again prevent using various optimizations during fast refresh. After you have performed a load or incremental load and rebuilt the detail table indexes, you must re-enable integrity constraints (if any) and refresh the materialized views and materialized view indexes that are derived from that detail data. The condition predicate can refer to both the target and the source table. Thus, processing only the changes can result in a very fast refresh time. Most data warehouses have periodic incremental updates to their detail data. For example, assume that the detail tables and materialized view are partitioned and have a parallel clause. It can be used for wrapping commonly used complex queries. 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.

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