Administering Mediator : Advanced Settings and Server Configuration Parameters : Advanced Settings : pg.3pSnmpSender.
pg.3pSnmpSender.
pg.3pSnmpSender.sendDelay
This is an internal parameter. Do not modify.
pg.backupFailedProxies
pg.backupFailedProxies
Indicates whether the backup services failed. The default is false.
pg.CollectionPool.
pg.CollectionPool.minThreads
The minimum number of threads to be used for data collection (metrics and events). Specifying more threads means that Mediator can collect more data faster, but it increases the usage of system resources, which could result in slower service execution. The default is 1.
pg.CollectionPool.maxThreads
The maximum number of threads to be used for data collection (metrics and events). This value must be greater than or equal to the value of pg.CollectionPool.minThreads. The default is 8.
pg.CollectionPool.forcefulShutdown
Specifies whether the data collection thread pool must shut down immediately or wait for queued tasks to complete during Mediator shutdown. The default is false.
pg.CollectionPool.poolName
Sets the name for the data collection thread pool. The default is CollectionPool.
pg.CollectionWorkQueue.
pg.CollectionWorkQueue.queueCapacity
The size of the collection work queue to be used during data collection (metrics and events). This queue is used only when there are not enough collection pool threads to process all the data. For example, if pg.CollectionPool.maxThreads is set to 10 and the 10 threads are not sufficient for processing all the data, then the unprocessed data is put into the collection work queue. If the queue capacity is reached, then any additional data is lost. The default is 10000 items of data allowed in the queue.
Specifying a large queue and a small collection pool minimizes CPU usage and operating system resources, but this can lead to low throughput which causes delays in data collection. Using a small collection work queue generally requires larger collection pool sizes, which keeps CPUs busier. This avoids the delay but may encounter unacceptable scheduling overhead, which also decreases service execution.
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