chaoqin-li1123 commented on code in PR #44643:
URL: https://github.com/apache/spark/pull/44643#discussion_r1470393614
##########
connector/protobuf/src/test/scala/org/apache/spark/sql/protobuf/ProtobufFunctionsSuite.scala:
##########
@@ -1124,7 +1124,79 @@ 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("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($"binary", name, descFilePathOpt,
options).as("empty_proto")
+ )
+ // Top level empty message is retained without adding dummy column to
the schema.
+ assert(df.schema ==
+ structFromDDL("empty_proto struct<__dummy_field_in_empty_struct:
string>"))
+ }
+
+ // EmptyProto at inner level, because empty struct type is not allowed in
Spark.,
+ // a dummy column is inserted to retain the empty message.
+ checkWithFileAndClassName("EmptyProtoWrapper") {
+ case (name, descFilePathOpt) =>
+ val df = emptyBinaryDF.select(
+ from_protobuf_wrapper($"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")
Review Comment:
Removed.
##########
connector/protobuf/src/test/scala/org/apache/spark/sql/protobuf/ProtobufFunctionsSuite.scala:
##########
@@ -1124,7 +1124,79 @@ 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("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<__dummy_field_in_empty_struct:
string>"))
+ }
+
+ // EmptyProto at inner level, because empty struct type is not allowed in
Spark.,
Review Comment:
Fixed.
##########
connector/protobuf/src/main/scala/org/apache/spark/sql/protobuf/utils/ProtobufOptions.scala:
##########
@@ -207,6 +207,23 @@ private[sql] class ProtobufOptions(
// nil => nil, Int32Value(0) => 0, Int32Value(100) => 100.
val unwrapWellKnownTypes: Boolean =
parameters.getOrElse("unwrap.primitive.wrapper.types",
false.toString).toBoolean
+
+ // Since Spark doesn't allow writing empty StructType, empty proto message
type will be
+ // dropped by default. Setting this option to true will insert a dummy
column to empty proto
+ // message so that the empty message will be retained.
+ // For example, an empty message is used as field in another message:
+ //
+ // ```
+ // message A {}
+ // Message B {A a = 1, string name = 2}
Review Comment:
Fixed.
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