Fine-tuning performance for Python, TERR, and R scripts
As you migrate your data functions from running on Spotfire Statistics Services server to the Spotfire Statistics Services, keep track of the system performance and note any relative slow-down or similar unexpected behavior—you can likely address this through configuration modifications in the service.
The default configurations are determined to provide reasonable
performance for most needs; however, you can customize the configuration to
improve performance. By exporting and editing the configuration file (as
described in the
Spotfire Server documentation), you can
change such settings as the number of engines and queue size, timeouts, engine
pruning, and JVM memory options, among others. These default configurations are
described in the topic
Custom configuration properties for each Spotfire Statistics
Service.