Download Oracle WebLogic Server 12c Essentials.1z0-599.ActualTests.2018-10-20.47q.tqb

Active GridLink for Oracle RAC In Oracle WebLogic Server 10.3.4, a single data source implementation has been introduced to support an Oracle RAC cluster. It responds to FAN events to provide Fast Connection Failover (FCF), Runtime Connection Load-Balancing (RCLB), and RAC instance graceful shutdown.  XA affinity is supported at the global transaction Id level. The new feature is called WebLogic Active GridLink for RAC; which is implemented as the GridLink data source within WebLogic Server. Note:The WebLogic Server JDBC subsystem has supported Oracle RAC since WLS version 9.0, originally developed for Oracle9i RAC.  This support is based on a particular type of data source configuration, called a multi data source.  A multi data source is a data source abstraction over one or more individual data sources.  It serves JDBC connections from each of the member data sources according to a specified policy.  A RAC multi data source configuration requires that each member data source obtain connections to a particular RAC instance. Reference: How-To: Use Oracle WebLogic Server with a JDBC GridLink Data Source

To manage work in your applications, you define one or more of the following Work Manager components:Fair Share Request Class:Response Time Request Class:Min Threads Constraint:Max Threads Constraint:Capacity Constraint Context Request Class:Note:* max-threads-constraint—This constraint limits the number of concurrent threads executing requests from the constrained work set. The default is unlimited. For example, consider a constraint defined with maximum threads of 10 and shared by 3 entry points. The scheduling logic ensures that not more than 10 threads are executing requests from the three entry points combined. A max-threads-constraint can be defined in terms of a the availability of resource that requests depend upon, such as a connection pool. A max-threads-constraint might, but does not necessarily, prevent a request class from taking its fair share of threads or meeting its response time goal. Once the constraint is reached the server does not schedule requests of this type until the number of concurrent executions falls below the limit. The server then schedules work based on the fair share or response time goal. * WebLogic Server prioritizes work and allocates threads based on an execution model that takes into account administrator-defined parameters and actual run-time performance and throughput. Administrators can configure a set of scheduling guidelines and associate them with one or more applications, or with particular application components. * WebLogic Server uses a single thread pool, in which all types of work are executed. WebLogic Server prioritizes work based on rules you define, and run-time metrics, including the actual time it takes to execute a request and the rate at which requests are entering and leaving the pool. The common thread pool changes its size automatically to maximize throughput. The queue monitors throughput over time and based on history, determines whether to adjust the thread count. For example, if historical throughput statistics indicate that a higher thread count increased throughput, WebLogic increases the thread count. Similarly, if statistics indicate that fewer threads did not reduce throughput, WebLogic decreases the thread count. This new strategy makes it easier for administrators to allocate processing resources and manage performance, avoiding the effort and complexity involved in configuring, monitoring, and tuning custom executes queues. Reference: Using Work Managers to Optimize Scheduled Work

A:* Troubleshooting Slow Response Time from the Client and Low Database Usage These symptoms are usually caused by a bottleneck upstream of the database, perhaps in the JDBC connectionpooling. Monitor the active JDBC connections in the WebLogic Console and watch for excessive waiters and wait times; increase the pool size, if necessary. * Attribute: Maximum CapacityMaximum number of physical database connections that this connection pool can contain. Different JDBC Drivers and database servers may limit the number of possible physical connections. C: Attribute: Statement Cache SizeThe algorithm used to maintain the statement cache:LRU - After the statementCacheSize is met, the Least Recently Used statement is removed when a new statement is used. Fixed - The first statementCacheSize number of statements is stored and stay fixed in the cache. No new statements are cached unless the cache is manually cleared. E: If the queue appears starved but adding execute threads does not improve performance, there may be resource contention. Because CPU utilization is low, the threads are probably spending much of their time waiting for some resource, quite often a database connection. Use the JDBC monitoring facilities in the console to check for high levels of waiters or long wait times. Adding connections to the JDBC connection pool may be all that is required to fix the problem. Note:* If you had a JDBC connection pool where the Initial Capacity and Maximum Capacity attributes were different, you might want to create a gauge monitor to monitor the maximum and minimum number of connections. By setting the Threshold Low value to be one less than the Initial Capacity, your gauge monitor trapcould monitor the Active Connections Current Count attribute of the JDBC Data Source Runtime MBean and alert you whenever the number of active connections are less than the Initial Capacity (which might indicate database connectivity problems).