EAServer scales well, primarily through the use of native platform threads. Threading allows multiple components to execute concurrently with a minimum of context-switching overhead. Threading issues that affect performance include:
Number of threads You can tune the total number of EAServer threads, and partition the total to different tasks such as IIOP and HTTP request handling. More threads allow the server to handle more clients. However, if the number is too high, you may experience thrashing, which occurs when each thread gets so little execution time that more time is spent switching the thread context than running threads. You can avoid thrashing by reducing the number of threads, adding CPUs to a multi-CPU machine, or moving to a clustered EAServer deployment.
Concurrency When different threads share data structures or resources, you must synchronize their execution so that access to the shared data or resource is serialized, that is, accessed by only one thread at a time. If access to the shared object is not serialized, you can cause race conditions, where overlapping modifications yield unpredictable results, often causing a crash due to the resulting nonsense data or resource state. However, excessive serialization can slow down the application by creating bottlenecks where many threads idle waiting to acquire synchronization locks. To avoid this problem, do not use design patterns that require synchronized code. When objects must be shared across threads, minimize synchronization and design carefully to avoid deadlock.
Deadlock Deadlock occurs when two or more threads create recursive lock dependencies and wait indefinitely for each other to release the locks held. Figure 1-2 illustrates a deadlock scenario. Component 1 has locked object A while component 2 holds locks on object B. Now component 1 waits for B to be released while component 2 waits for A to be released.
Deadlock is an extreme problem that can hang the server or at least the threads that are deadlocked. You can eliminate deadlock by carefully designing and following a locking protocol that avoids recursive dependencies when a component locks more than one object at once. For example, to lock the two objects in Figure 1-2, always lock A before locking B.
Thread binding EAServer pools and reuses threads, allowing component instances to run on any thread rather than being tied to the same thread as a client connection or the thread that created the instance. Since most client connections have significant idle time, thread pooling allows fewer threads to serve more clients. However, if a component uses thread-local storage, each component instance must be bound to the thread that created it. Binding the thread significantly reduces scalability, since the thread cannot be used to run other instances and sits idle when the component is not running. For more information, see “Thread-related issues”.
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