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.
