[GitHub] [spark] hvanhovell commented on a diff in pull request #40063: [CONNECT] Eager Execution of DF.sql()

["hvanhovell (via GitHub)" <gi...@apache.org>]

hvanhovell commented on code in PR #40063:
URL: https://github.com/apache/spark/pull/40063#discussion_r1109707851


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connector/connect/common/src/main/protobuf/spark/connect/base.proto:
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@@ -152,12 +152,19 @@ message ExecutePlanRequest {
 message ExecutePlanResponse {
   string client_id = 1;
 
-  ArrowBatch arrow_batch = 2;
+  oneof result_type {
+    ArrowBatch arrow_batch = 2;
+    RemoteDataFrame remote_data_frame = 5;

Review Comment:
   Instead of caching the dataframe, we could also return the results and put them in a client side local relation. The chance that folks are using the results of a sql command for further processing is very very small.
   
   BTW I do think that a remote dataframe is useful to have (it is very useful for use cases like input stabilization, dataframe sharing, ...) but I don't think we need it in this particular case.



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