SandishKumarHN commented on code in PR #39550:
URL: https://github.com/apache/spark/pull/39550#discussion_r1167973045
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connector/protobuf/src/main/scala/org/apache/spark/sql/protobuf/functions.scala:
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@@ -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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