[GitHub] [spark] HyukjinKwon commented on a diff in pull request #38653: [SPARK-41128][CONNECT][PYTHON] Implement `DataFrame.fillna ` and `DataFrame.na.fill `

[GitBox <gi...@apache.org>]

HyukjinKwon commented on code in PR #38653:
URL: https://github.com/apache/spark/pull/38653#discussion_r1022295525


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connector/connect/src/main/protobuf/spark/connect/relations.proto:
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@@ -316,6 +319,36 @@ message StatCrosstab {
   string col2 = 3;
 }
 
+// Replaces null values.
+// It will invoke 'Dataset.na.fill' (same as 'DataFrameNaFunctions.fill') to compute the results.
+// Following 3 parameter combinations are supported:
+//  1, 'values' only contains 1 item, 'cols' is empty:
+//    replaces null values in all type-matched columns.
+//  2, 'values' only contains 1 item, 'cols' is not empty:
+//    replaces null values in specified columns.
+//  3, 'values' contains more than 1 items, then 'cols' is required to have the same length:
+//    replaces each specified column with corresponding value.
+message NAFill {
+  // (Required) The input relation.
+  Relation input = 1;
+
+  // (Optional) Optional list of column names to consider.
+  repeated string cols = 2;
+
+  // (Required) Values to replace null values with. Should contains at least 1 item.
+  repeated Type values = 3;
+
+  // Available data types.
+  message Type {

Review Comment:
   Could we probably use `Literal` to ship these values? We can call `eval` to take this out in JVM side.



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