Automatic Degree of Parallelism. Data warehousing applications often take advantage of parallelism to process information quickly and effectively, especially when running queries against tables that are extremely large or that are joined in a complex fashion. However, determining exactly what is an appropriate DOP often requires a detailed understanding of just how the tables are typically joined, which indexes could most benefit from parallelism, and even what type of workload might be executing at the same time as the parallel query.
The good news is that Oracle 11 g R2 can now determine the DOP automatically for any parallel statement. Many Oracle database shops have discovered that a Real Application Cluster RAC database provides both high availability for OLTP applications, but also provides outstanding performance for data warehousing applications because it can parallelize queries across multiple instances on different nodes in the RAC cluster. Faster Refreshes for Materialized Views.
When the underlying base tables for a MV change frequently, materialized view logs are used to populate just the changed data to the MV. Oracle 11 g R2 now offers the ability to purge the MV logs from outside the refresh process, and that means improved performance, especially for any MV that contains aggregates, joins, or both. Manageable Standby Databases Increased. In anticipation of the expansion of Data Guard platforms for intense data warehousing operations, Oracle 11 g R2 has increased the number of manageable standby databases from only nine to a total of thirty 30 in any combination physical standby, logical standby, or snapshot standby.
Integrated Application Failover. Earlier releases of Data Guard provided for relatively quick failover of application sessions during switchover and failover operations using Transparent Application Failover TAF , but Oracle 11 g R2 now offers the ability to leverage Fast Application Notification FAN features for even faster application failover.
As part of the separately-licensed Active Data Guard option, Oracle 11 g R1 offered Real Time Apply the ability to apply redo to a physical standby database while it was still open for read-only reporting in concert with Real Time Query the ability to query a read-only standby database while redo was still being applied. This provided an alternative to using basic replication for read-only data warehouse reporting, with one important exception: there was no way to respond to any significant delays in the application of redo information on the physical standby database.
Support for Compressed Tables and SecureFiles. Oracle 11 g R2 now fully supports the application of redo to logical standby databases with SQL Apply for primary database tables that use either basic DSS or advanced OLTP table compression because the LogMiner utility also now supports translation of redo entries for any tables using these data compression features. Oracle 11 g R2 extends the already-robust suite of backup and recovery tools that comprise Recovery Manager RMAN with some notable new enhancements, many of which are obvious extensions of earlier features:.
Automatic Block Recovery. Here, crossedition triggers propagate data changes made by the new edition into the columns of the old edition. Large, mission critical applications are often unavailable for long periods of time while database objects are patched or upgraded.
Edition-based redefinition allows this cost to be avoided. Oracle Database Development Guide for details. Oracle Database 11 g Release 1 In release Release This hint improves performance and ease-of-programming when implementing an online application upgrade script using edition-based redefinition.
The following sections describe new features in this release that provide improvements in Oracle Data Guard. Compressed tables that is, tables with compression that support both OLTP and direct load operations are supported in logical standby databases and Oracle LogMiner.
With support for this additional storage attribute, logical standby databases can now provide data protection and reporting benefits for a wider range of tables. A physical standby database can be open for read-only access while redo apply is active only if the Oracle Active Data Guard option is enabled.
This capability is known as real-time query. This capability allows queries to be safely offloaded from the primary database to a physical standby database, because it is possible to detect if the standby database has become unacceptably stale. Applications connected to a primary database can transparently failover to the new primary database upon an Oracle Data Guard role transition. Flexibility and manageability of disaster recovery configurations using Oracle Data Guard is improved. Oracle Data Guard Broker for details.
The number of standby databases that a primary database can support is increased from 9 to 30 in this release. The capability to create 30 standby databases, combined with the functionality of the Oracle Active Data Guard option, allows the creation of reader farms that can be used to offload large scale read-only workloads from a production database. New and enhanced analytical functions are introduced in this release. The new and enhanced SQL analytical functions allow more complex analysis in the database, using simpler SQL specification and providing better performance.
Oracle Database Data Warehousing Guide for details. That program must live in a directory path specified by a directory object defined in the database. This feature allows the DBA to control who is allowed to run preprocessors as part of loading data with external tables.
It also allows the DBA to restrict which programs those users can run. Oracle Database Utilities for details. The access parameters can specify the name of a directory object and the name of an executable file in that directory object.
When the access driver needs to read data from a file, it creates a process that runs the specified program, passing in the name of the data file. The output from the program is passed into the access driver which parses the data into records and columns.
The initial use of this feature is by a customer who needs to load data that is stored in compressed files. The user specifies the name of the program used to decompress the file as part of the access parameters.
The access driver reads the output of the decompression program. Virtual columns can be used as the primary or the foreign key column of a reference partition table. Allowing the use of virtual columns for reference partitioned tables enables an easier implementation of various business scenarios using Oracle Partitioning. This feature provides enhanced completeness of domain-specific indexing support for partitioning to meet user requirements including Oracle XML DB.
Performance of local domain indexes on list partitioned tables is improved in this release. The following sections describe new and improved performance and scalability capabilities in this release. Oracle automatically decides if an object being accessed using parallel execution benefits from being cached in the SGA buffer cache.
The decision to cache an object is based on a well defined set of heuristics including size of the object and the frequency that it is accessed. In an Oracle RAC environment, Oracle maps fragments of the object into each of the buffer caches on the active instances. By creating this mapping, Oracle knows which buffer cache to access to find a specific part or partition of an object to answer a given SQL query.
In-memory parallel query harnesses the aggregated memory in a system for parallel operations, enabling it to scale out with the available memory for data caching as the number of nodes in a cluster increases. When activated, Oracle determines the optimal degree of parallelism DOP for any given SQL operation based on the size of the objects, the complexity of a statement, and the existing hardware resources.
The database compensates for wrong or missing user settings for parallel execution, ensuring a more optimal resource consumption and overall system behavior. The statement must have two placeholders that define the start and end limit of a chunk. Typically, these are values for the rowid or a surrogate unique key in a large table.
But, when an anonymous block is used, the block can interpret the values arbitrarily. The package has subprograms to define ranges that cover the specified table. These include rule-based division of a table's rowid or key range and support user-defined methods. The SQL statement together with the set of chunk ranges define a task. Another subprogram starts the task. Each task is processed using a scheduler job and automatically commits when it completes. Progress is logged. Untried, successful, and failed chunks are flagged as such on task completion or interruption.
Another subprogram allows the task to resume to try untried and failed chunks. Many scenarios require the bulk transformation of a large number of rows. Using an ordinary SQL statement suffers from the all-or-nothing effect. In the common case, where the transformation of one row is independent of that of other rows, it is correct to commit every row that is transformed successfully and to roll back every row where the transformation fails.
Some customers have implemented schemes to achieve this from scratch, using the Oracle Scheduler and suitable methods to record progress. This package provides a supported solution and adds database-wide manageability through new catalog views for parallel task metadata. The package is especially useful in online application upgrade scenarios to apply a crossedition trigger to all the rows in the table on which it is defined.
Fast refresh of a materialized view is now significantly faster due to reducing the time spent on log handling. The mapping editor has been enhanced with advanced find capabilities to make it easier to locate and make updates to operators, groups, and attributes in a mapping diagram, in the Available Objects tab, and in the Selected Objects tab.
This feature enhances ETL mapping developer productivity, especially on large and complex mappings and, for example, when working with complex data sources with large numbers of tables, views, or columns. Oracle Discoverer integration was added in a previous release, and includes derivation of metadata for Discoverer from the data warehouse design, and deploying those derived objects into Discoverer.
All business intelligence application objects are modeled in OWB and can be included in lineage and impact analysis at the column level. Customers using Oracle business intelligence tools with their Oracle data warehouses can get better answers from their warehouses faster, with no additional design or development effort.
In the mapping editor, users can now copy and paste operators within a mapping or across mappings, including attribute settings. This enhancement saves time and reduces errors in the development of complex ETL mappings that reuse common or similar elements. In the Design Center, there is now a dropdown list that displays the active configuration of the user. There are numerous support improvements for importing flat files, including a simplified Flat File Sampling wizard, support for multi-character and hexadecimal format delimiters and enclosures, simplified support for fixed format fields, and support for bulk flat file loads into heterogeneous targets.
Flat files are frequently used for simple and high performance data movement in ETL applications. These changes improve ETL developer productivity and provide flexible handling of flat files in more scenarios. OWB now has improved support for table functions, including importing metadata for existing table functions, an editor for creating table functions from within OWB, and better support for table functions in mappings. Improved support simplifies using table functions for much more flexible and powerful transformations, such as user-defined aggregations and data mining sampling operators.
This feature makes it possible to enhance and extend the functionality of the mapping editor, improving developer productivity. Expressions associated with operator attributes can now be entered directly into an Operator Edit Dialog or Expression Editor, rather than requiring that these expressions be entered into a property in the Property Inspector.
Developers can finish more of their work in one place when creating operators in ETL mappings, thus improving their productivity. In the mapping editor, users can now temporarily or permanently group objects in the mapping editor so that they are collapsed to a single icon. This hides complexity in mappings. Users can also spotlight a single operator, which temporarily hides all objects in the mapping except for those objects that connect directly to the operator.
These features improve productivity for developers working with complex mappings with large numbers of operators. The user interface for managing the registration of locations in control centers has been reworked to improve usability, especially when working with locations registered in multiple control centers. This change improves productivity of OWB administrators responsible for managing locations across control centers.
The user interface for managing OWB locations has been reworked to improve usability and support access to non-Oracle data sources using newly supported connectivity methods. These changes improve Oracle Warehouse Builder administrator and developer productivity in heterogeneous and Oracle-only environments. These changes make the lookup operator more powerful in many situations, including improving Type 2 slowly changing dimension support.
These enhancements improve productivity for ETL mapping developers, especially when working with complex mappings where the mapping debugger adds the most value. Support for opening multiple editors of the same type, for example, editing several ETL mappings at once in different windows. Developers experience increased productivity in the Oracle Warehouse Builder environment, which now benefits from the usability research behind the Fusion Client Platform and consistency with other Oracle products.
Developers can more easily troubleshoot issues with OWB-generated code that can only be detected when the code is deployed. This additional information enhances developer productivity. In this release, Oracle Warehouse Builder OWB introduces a new spreadsheet-like dialog for connecting operators in a mapping.
This functionality replaces the existing auto mapping dialog. This improvement saves developer time and reduces errors when working with operators with a large number of inputs or outputs.
The Repository Browser has been updated to support foldering, expose the new types of metadata associated with the release The repository upgrade automatically upgrades an Oracle Warehouse Builder OWB repository to the current release with less user intervention. The join operator in Oracle Warehouse Builder OWB now supports several new behaviors related to the use of subqueries in joins:. More flexible handling for join operations improves developer productivity and makes possible more flexible data transformations.
The following sections describe new clustering features for Oracle Database 11 g Release 2 This release of Oracle Real Application Clusters Oracle RAC provides many features to dramatically simplify installation and on-going management of a cluster and Oracle RAC database, making it easy for the novice to adopt clustering and Oracle RAC and reap the benefits of this technology.
Configuration Assistants automate the configuration of the environment ensuring the correct steps are taken. The assistants simplify the implementation of clusters and clustered databases. Additional functionality has been added to the Cluster Verification Utility CVU in regard to checking certain storage types and configurations.
Furthermore, it gives more consideration to user-specific settings. These enhancements provide easier implementation and configuration of cluster environments and improved problem diagnostics in a cluster environment. The Cluster Verification Utility CVU is now fully integrated with the installer so that checks are done automatically for all nodes included in the installation.
This integration improves Oracle RAC manageability and deployment by ensuring that any problems with cluster setup are detected and corrected prior to installing Oracle software. The Cluster Time Service synchronizes the system time on all nodes in the cluster. A synchronized system time across the cluster is a prerequisite to install and successfully run an Oracle cluster.
This feature simplifies management, maintenance, and support of an Oracle cluster and an Oracle RAC environment by providing an out-of-the-box time server. It also improves the reliability of Oracle RAC environments.
Oracle Clusterware Administration and Deployment Guide for details. These improvements include:. These enhancements improve performance in Oracle Clusterware and Oracle Real Application Clusters environments and provide easier management of the cluster through consistent storage management automation. Grid Plug and Play GPnP eliminates per-node configuration data and the need for explicit add and delete nodes steps. This allows a system administrator to take a template system image and run it on a new node with no further configuration.
This removes many manual operations, reduces the opportunity for errors, and encourages configurations that can be changed easily. Removal of the per-node configuration makes the nodes easier to replace, because they do not need to contain individually-managed state. Grid Plug and Play reduces the cost of installing, configuring, and managing database nodes by making their per-node state disposable. It allows nodes to be easily replaced with regenerated state. Oracle Grid Infrastructure Installation Guide for details.
Oracle Restart improves the availability of your single-instance Oracle database. Oracle Restart automatically restarts the database instance, the Automatic Storage Management ASM instance, the listener, and other components after a hardware or software failure or whenever your database host computer restarts.
This feature provides improved reliability and automated management of a single-instance Oracle database and the management of any process or application running on the database server. Oracle Database Administrator's Guide for details. Oracle Clusterware allocates and reassigns capacity based on policies defined by you. This enables faster resource failover and dynamic capacity assignment using a policy-based management. Policy-Based Cluster and Capacity Management allows the efficient allocation of all kinds of applications in the cluster.
Various applications can be hosted on a shared infrastructure being isolated regarding their resource consumption by policies and, therefore, behave as if they were deployed in single system environments.
In this release, there are now more options for managing all types of applications and creating dependencies among them using Oracle Clusterware. Improved Clusterware Resource Modeling enables a granular definition of dependencies among applications or processes to manage them as one entity.
Role-separated management for Oracle Clusterware allows certain administrative tasks to be delegated to different people, representing different roles in the company. It is based on the idea of a clusterware administrator. The administrator may grant administrative tasks on a per resource basis.
For example, if two databases are placed into the same cluster, the clusterware administrator can manage both databases in the cluster. But, the clusterware administrator may decide to grant different administrative privileges to each DBA responsible for one of those databases. Role-separated management allows multiple applications and databases to share the same cluster and hardware resources, but ensures that different administration groups do not interfere with each other. Oracle Clusterware provides an agent framework for managing all kinds of applications with Oracle Clusterware.
Using the agent framework provides optimized application startup, checking, and stopping based on user-defined scripts.
Making it easy to protect applications with Oracle Clusterware reduces costs allowing you to efficiently enable high availability for applications. The patching of Oracle Clusterware and Oracle Real Application Clusters can now be completed without taking the entire cluster down.
Patchsets are now installed as out-of-place upgrades to the Oracle Grid infrastructure for a cluster software Oracle Clusterware and Automatic Storage Management and Oracle Database.
Now you can reduce your unplanned downtime of clustered databases and applications running in a cluster. New in this release is an Enterprise Manager graphical user interface GUI to manage various Oracle Clusterware resources with full lifecycle support.
In addition to allowing the creation and configuration of resources within Oracle Clusterware, it also helps to monitor and manage resources once deployed in the cluster. Using Oracle Enterprise Manager as a GUI to monitor and manage various Oracle Clusterware resources eases the daily management in high availability environments. Enterprise Manager provisioning introduces procedures to easily scale up or scale down Oracle Clusterware and Oracle Real Application Clusters. Ease-of-implementation and management for a clustered database environment can be achieved through utilizing the Enterprise Manager provisioning framework.
This integration provides an easy-to-use interface that customers are familiar with to manage Grid Plug and Play environments. Enterprise Manager provides support for Oracle Restart and the configuration with single-instance databases. This is a change in configuration, monitoring, and administration to enable Oracle Restart. Perhaps you are interested in the exciting new features and you do not know whether 11gR1 or 11gR2 is right for you?
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