charlesy6 commented on code in PR #44643:
URL: https://github.com/apache/spark/pull/44643#discussion_r1458381280
##########
connector/protobuf/src/test/scala/org/apache/spark/sql/protobuf/ProtobufFunctionsSuite.scala:
##########
@@ -1124,7 +1124,78 @@ class ProtobufFunctionsSuite extends QueryTest with
SharedSparkSession with Prot
}
}
- test("Corner case: empty recursive proto fields should be dropped") {
+ test("Retain empty proto fields when retain.empty.message.types=true") {
+ // When retain.empty.message.types=true, empty proto like 'message A {}'
can be retained as
+ // a field by inserting a dummy column as sub column.
+ val options = Map("recursive.fields.max.depth" -> "4",
"retain.empty.message.types" -> "true")
+
+ // EmptyProto at the top level. It will be an empty struct.
+ checkWithFileAndClassName("EmptyProto") {
+ case (name, descFilePathOpt) =>
+ val df = emptyBinaryDF.select(
+ from_protobuf_wrapper($"binary", name, descFilePathOpt,
options).as("empty_proto")
+ )
+ // Top level empty message is retained without adding dummy column to
the schema.
+ assert(df.schema == structFromDDL("empty_proto struct<>"))
+ }
+
+ // EmptyProto at inner level, because empty struct type is not allowed in
Spark.,
+ // a dummy column is inserted to retain the empty message.
+ checkWithFileAndClassName("EmptyProtoWrapper") {
+ case (name, descFilePathOpt) =>
+ val df = emptyBinaryDF.select(
+ from_protobuf_wrapper($"binary", name, descFilePathOpt,
options).as("wrapper")
+ )
+ // Nested empty message is retained by adding dummy column to the
schema.
+ assert(df.schema == structFromDDL("wrapper struct" +
+ "<name: string, empty_proto struct<__dummy_field_in_empty_struct:
string>>"))
+ }
+ }
+
+ test("Write empty proto to parquet when retain.empty.message.types=true") {
+ // When retain.empty.message.types=true, empty proto like 'message A {}'
can be retained
+ // as a field by inserting a dummy column as sub column, such schema can
be written to parquet.
+ val options = Map("recursive.fields.max.depth" -> "4",
"retain.empty.message.types" -> "true")
+ withTempDir { file =>
+ val binaryDF = Seq(
+
EmptyRecursiveProtoWrapper.newBuilder.setName("my_name").build().toByteArray)
+ .toDF("binary")
+ checkWithFileAndClassName("EmptyProtoWrapper") {
+ case (name, descFilePathOpt) =>
+ val df = binaryDF.select(
+ from_protobuf_wrapper($"binary", name, descFilePathOpt,
options).as("wrapper")
+ )
+
df.write.format("parquet").mode("overwrite").save(file.getAbsolutePath)
+ }
+ val resultDF = spark.read.format("parquet").load(file.getAbsolutePath)
+ assert(resultDF.schema == structFromDDL("wrapper struct" +
+ "<name: string, empty_proto struct<__dummy_field_in_empty_struct:
string>>"
+ ))
+ // The dummy column of empty proto should have null value.
+ checkAnswer(resultDF, Seq(Row(Row("my_name", null))))
+ }
+
+ // Top level message can't be empty, otherwise AnalysisException will be
thrown.
Review Comment:
> Test added.
👍
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