[GitHub] [spark] SandishKumarHN commented on a diff in pull request #39550: [SPARK-42056][SQL][PROTOBUF] Add missing options for Protobuf functions

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

SandishKumarHN commented on code in PR #39550:
URL: https://github.com/apache/spark/pull/39550#discussion_r1167973045


##########
connector/protobuf/src/main/scala/org/apache/spark/sql/protobuf/functions.scala:
##########
@@ -72,51 +69,129 @@ object functions {
   }
 
   /**
-   * Converts a binary column of Protobuf format into its corresponding catalyst value. The
-   * specified Protobuf class must match the data, otherwise the behavior is
-   * undefined: it may fail or return arbitrary result. The jar containing Java class should be
+   * Converts a binary column of Protobuf format into its corresponding catalyst value.
+   * `messageClassName` points to Protobuf Java class. The jar containing Java class should be
    * shaded. Specifically, `com.google.protobuf.*` should be shaded to
    * `org.sparkproject.spark-protobuf.protobuf.*`.
+   * https://github.com/rangadi/shaded-protobuf-classes is useful to create shaded jar from
+   * Protobuf files.
    *
    * @param data
    *   the binary column.
-   * @param shadedMessageClassName
-   *   The Protobuf class name. E.g. <code>org.spark.examples.protobuf.ExampleEvent</code>.
+   * @param messageClassName
+   *   The full name for Protobuf Java class. E.g. <code>com.example.protos.ExampleEvent</code>.
    *   The jar with these classes needs to be shaded as described above.
    * @since 3.4.0
    */
   @Experimental
-  def from_protobuf(data: Column, shadedMessageClassName: String): Column = {
-    new Column(ProtobufDataToCatalyst(data.expr, shadedMessageClassName))
+  def from_protobuf(data: Column, messageClassName: String): Column = {
+    new Column(ProtobufDataToCatalyst(data.expr, messageClassName))
   }
 
   /**
-   * Converts a column into binary of protobuf format.
+   * Converts a binary column of Protobuf format into its corresponding catalyst value.
+   * `messageClassName` points to Protobuf Java class. The jar containing Java class should be
+   * shaded. Specifically, `com.google.protobuf.*` should be shaded to
+   * `org.sparkproject.spark-protobuf.protobuf.*`.
+   * https://github.com/rangadi/shaded-protobuf-classes is useful to create shaded jar from
+   * Protobuf files.
+   *
+   * @param data
+   *   the binary column.
+   * @param messageClassName
+   *   The full name for Protobuf Java class. E.g. <code>com.example.protos.ExampleEvent</code>.
+   *   The jar with these classes needs to be shaded as described above.
+   * @param options
+   * @since 3.4.0
+   */
+  @Experimental

Review Comment:
   @ericsun95 since the protobuf encoding format is binary, you can use the spark binary file data source and then use from_protobuf function to convert it into a spark dataframe. I don't see the need for a separate protobuf data source. 
   
   `
   spark.read.format("binaryFile").option("pathGlobFilter", "*.proto").load("/path/to/data")
   `
   
   having a separate data source for protobuf can achieve performance, type safety, and schema evolution by storing the protobuf schema along with the protobuf files on disk.
   
   @rangadi 



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