andygrove opened a new issue, #2003:
URL: https://github.com/apache/datafusion-ballista/issues/2003

   **Is your feature request related to a problem or challenge? Please describe 
what you are trying to do.**
   
   Ballista currently implements a batch execution model directly modeled after 
Apache Spark. Query stages are executed to completion, with output written to 
shuffle files. The plan is optionally re-optimized based on statistics from 
completed query stages (AQE). This is a well proven design that scales 
massively for ETL and analytical workloads.
   
   This issue is to discuss whether we should consider extending Ballista to 
also support a model that is closer to DataFusion's in-process execution model, 
where the whole plan is executed eagerly and results are streamed between 
stages, bypassing the shuffle files. This can lead to faster time to first 
results in some cases, and lower latency queries. 
   
   **Describe the solution you'd like**
   
   **Describe alternatives you've considered**
   
   **Additional context**
   


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