In-memory Models Management

Memory usage settings manage, how long eventlogs and calculation results are kept in the memory, affecting both the memory usage and performance. The longer items are in the memory, the more memory is consumed, but on the other hand users perceive better performance as analyses are more likely to be available in the memory already calculated. Memory usage settings can be defined for the system level in the web.config file and for each model separately.

Model Memory Settings

Model level settings can be set in the Model properties dialog. The following settings are available:

• Drop Unused Model After: Duration after which the unused model is dropped from the memory. Defined in format HH:mm:ss or d.HH:mm:ss, for example 01:00:00 (one hour), 00:30:00 (30 minutes) or 1.00:00:00 (24 hours). When any calculation is performed for a model, the last used time of the model is updated. If this setting is not defined, the server level default setting is used.
• Drop Unused Filters After: Duration after which the unused filters in the model are dropped from the memory. Defined in format HH:mm:ss or d.HH:mm:ss, for example 01:00:00 (one hour), 00:30:00 (30 minutes) or 1.00:00:00 (24 hours). When any calculation is performed using a filter, the filter's last used time is updated (also model's last used time is updated). If this setting is not defined, the server level default setting is used.

Configuration Examples

Following values keep the model in memory for 1 hour and filters for 30 minutes.

• Drop Unused Model After: 1:00:00
• Drop Unused Filters After: 00:30:00

Following values keep the model in memory for 15 minutes and filters for 5 minutes.

• Drop Unused Model After: 0:15:00
• Drop Unused Filters After: 00:05:00

Following values keep the model in memory for 100 days (practically it's never dropped) and filters for 2 hours.

• Drop Unused Model After: 100.00:00:00
• Drop Unused Filters After: 02:00:00

Memory Stored Objects

Data handled by QPR ProcessAnalyzer memory is stored in following types of objects:

Stored object	Contents	Unused objects dropped after	Time to recreate after dropping	Memory consumption
Models (model eventlogs)	Models contain all data in a model, such as events, cases, event types and variations.	Primarily defined by the Drop Unused Model After setting in the Model settings dialog. If this not set for a model, the server level setting in the web.config file is used. If the server setting is not defined either, a default value of 10 hours is used. Even when the is a memory shortage in the server, models are not dropped from the memory.	Slow Models are loaded from the database requiring to transfer considerable amount of data, which takes much more time than e.g. calculating filters and analyses.	High
Filters (filter eventlogs)	Filters contain all filtered data in model, which includes similar data and structures as the models.	Primarily defined by the Drop Unused Filters After setting in the Model settings dialog. If this not set for a model, the server level setting in the web.config file is used. If the server setting is not defined, a default value of 1 hour is used. When the is a memory shortage in the server, they may be dropped from the memory earlier to free memory.	Fast Filters are calculated from the model data that already exists in the memory. Practically, filters are subsets of models.	Medium
Calculation results	Results of the calculations made e.g. for charts.	Unused calculation results are kept 30 minutes in the memory. When the is a memory shortage in the server, they may be dropped from the memory earlier to free memory.	Fast Analysis results are calculated from filters, which already exist in memory.	Low
Datatables	Contents of datatables.	There is a fixed duration of 1 hour. When the is a memory shortage in the server, they may be dropped from the memory earlier to free memory.	Between slow and fast, depending on how much there is data in the datatable.	Between high and low, depending on how much there is data in the datatable.

If the QPR ProcessAnalyzer server doesn't have enough memory to store more objects, already stored objects are dropped from the memory starting from the one having the longest time since the last usage. Thus, when there is a memory shortage, objects may be dropped earlier than their settings define. Filter eventlogs, calculation results and datatables are dropped during the memory shortage, and model eventlog are never dropped prematurely. This is because recalculating filters and calculation results is usually faster than loading models from the database. That is why, when trying to load more models than there is available memory in the server, an out of memory error situation may occur.