study

When it comes to dealing with large amounts of data, creating studies can be quite challenging. A common requirement is the ability to quickly reconfigure a study, or modify information extracted at runtime. However, parallelism issues can limit flexibility.

Fortunately, the study framework offers a solution. It provides three different "study phases" that wrap around your domain-specific worker code. This approach makes it possible to change processing models for each phase and the connections between them with only minimal modifications to the code. Better yet, they can be reconfigured even after deployment, offering even greater flexibility.

Overall, the study framework is an excellent tool for those dealing with large amounts of data. Its flexibility and runtime functionality make it a worthwhile investment for any user.