Add a protocol buffer decode kernel

src/main/cpp/CMakeLists.txt

@@ -1,5 +1,5 @@
 # =============================================================================
-# Copyright (c) 2022-2025, NVIDIA CORPORATION.
+# Copyright (c) 2022-2026, NVIDIA CORPORATION.
 #
 # Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
 # in compliance with the License. You may obtain a copy of the License at
@@ -207,6 +207,7 @@ add_library(
   src/NativeParquetJni.cpp
   src/NumberConverterJni.cpp
   src/ParseURIJni.cpp
+  src/ProtobufJni.cpp
   src/RegexRewriteUtilsJni.cpp
   src/RowConversionJni.cpp
   src/SparkResourceAdaptorJni.cpp
@@ -254,6 +255,7 @@ add_library(
   src/multiply.cu
   src/number_converter.cu
   src/parse_uri.cu
+  src/protobuf.cu
   src/regex_rewrite_utils.cu
   src/row_conversion.cu
   src/round_float.cu

src/main/cpp/src/ProtobufJni.cpp

@@ -0,0 +1,80 @@
+/*
+ * Copyright (c) 2026, NVIDIA CORPORATION.
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+#include "cudf_jni_apis.hpp"
+#include "dtype_utils.hpp"
+#include "protobuf.hpp"
+
+#include <cudf/column/column_view.hpp>
+#include <cudf/utilities/traits.hpp>
+
+extern "C" {
+
+JNIEXPORT jlong JNICALL
+Java_com_nvidia_spark_rapids_jni_Protobuf_decodeToStruct(JNIEnv* env,
+                                                         jclass,
+                                                         jlong binary_input_view,
+                                                         jintArray field_numbers,
+                                                         jintArray type_ids,
+                                                         jintArray type_scales,
+                                                         jboolean fail_on_errors)
+{
+  JNI_NULL_CHECK(env, binary_input_view, "binary_input_view is null", 0);
+  JNI_NULL_CHECK(env, field_numbers, "field_numbers is null", 0);
+  JNI_NULL_CHECK(env, type_ids, "type_ids is null", 0);
+  JNI_NULL_CHECK(env, type_scales, "type_scales is null", 0);
+
+  JNI_TRY
+  {
+    cudf::jni::auto_set_device(env);
+    auto const* input = reinterpret_cast<cudf::column_view const*>(binary_input_view);
+    cudf::jni::native_jintArray n_field_numbers(env, field_numbers);
+    cudf::jni::native_jintArray n_type_ids(env, type_ids);
+    cudf::jni::native_jintArray n_type_scales(env, type_scales);
+    if (n_field_numbers.size() != n_type_ids.size() ||
+        n_field_numbers.size() != n_type_scales.size()) {
+      JNI_THROW_NEW(env,
+                    cudf::jni::ILLEGAL_ARG_EXCEPTION_CLASS,
+                    "fieldNumbers/typeIds/typeScales must be the same length",
+                    0);
+    }
+
+    std::vector<int> field_nums(n_field_numbers.begin(), n_field_numbers.end());
+    std::vector<int> encodings(n_type_scales.begin(), n_type_scales.end());
+    std::vector<cudf::data_type> out_types;
+    out_types.reserve(n_type_ids.size());
+    for (int i = 0; i < n_type_ids.size(); ++i) {
+      // For protobuf decoding, typeScales contains encoding info (0=default, 1=fixed,
+      // 2=zigzag) not decimal scales. For non-decimal types, scale should be 0. Decimal types are
+      // not currently supported in protobuf decoder.
+      auto type_id = static_cast<cudf::type_id>(n_type_ids[i]);
+      if (cudf::is_fixed_point(cudf::data_type{type_id})) {
+        // For decimal types, use the scale from typeScales (though currently unsupported)
+        out_types.emplace_back(cudf::jni::make_data_type(n_type_ids[i], n_type_scales[i]));
+      } else {
+        // For non-decimal types, scale is always 0; typeScales contains encoding info
+        out_types.emplace_back(cudf::jni::make_data_type(n_type_ids[i], 0));
+      }
+    }
+
+    auto result = spark_rapids_jni::decode_protobuf_to_struct(
+      *input, field_nums, out_types, encodings, fail_on_errors);
+    return cudf::jni::release_as_jlong(result);
+  }
+  JNI_CATCH(env, 0);
+}
+
+}  // extern "C"