[GitHub] [spark] rangadi commented on a diff in pull request #38212: [SPARK-40655][PYTHON][PROTOBUF] PySpark support for from_protobuf and to_protobuf

[GitBox <gi...@apache.org>]

rangadi commented on code in PR #38212:
URL: https://github.com/apache/spark/pull/38212#discussion_r994899383


##########
python/pyspark/sql/protobuf/functions.py:
##########
@@ -0,0 +1,196 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You 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.
+#
+
+"""
+A collections of builtin protobuf functions
+"""
+
+
+from typing import Dict, Optional, TYPE_CHECKING
+from pyspark import SparkContext
+from pyspark.sql.column import Column, _to_java_column
+from pyspark.util import _print_missing_jar
+
+if TYPE_CHECKING:
+    from pyspark.sql._typing import ColumnOrName
+
+
+def from_protobuf(
+    data: "ColumnOrName",
+    descFilePath: str,
+    messageName: str,

Review Comment:
   Could we we change the order of the arguments (might need change to scala side as well). I.e. messageName as the second arg. There will be multiple variations of this method, all of which will need `messageName`. It can be second arg. 



##########
python/pyspark/sql/protobuf/functions.py:
##########
@@ -0,0 +1,196 @@
+#
+# Licensed to the Apache Software Foundation (ASF) under one or more
+# contributor license agreements.  See the NOTICE file distributed with
+# this work for additional information regarding copyright ownership.
+# The ASF licenses this file to You 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.
+#
+
+"""
+A collections of builtin protobuf functions
+"""
+
+
+from typing import Dict, Optional, TYPE_CHECKING
+from pyspark import SparkContext
+from pyspark.sql.column import Column, _to_java_column
+from pyspark.util import _print_missing_jar
+
+if TYPE_CHECKING:
+    from pyspark.sql._typing import ColumnOrName
+
+
+def from_protobuf(
+    data: "ColumnOrName",
+    descFilePath: str,
+    messageName: str,
+    options: Optional[Dict[str, str]] = None,
+) -> Column:
+    """
+    Converts a binary column of Protobuf format into its corresponding catalyst value.
+    The specified schema must match the read data, otherwise the behavior is undefined:
+    it may fail or return arbitrary result.
+    To deserialize the data with a compatible and evolved schema, the expected
+    Protobuf schema can be set via the option protobuf descriptor.
+
+    .. versionadded:: 3.4.0
+
+    Parameters
+    ----------
+    data : :class:`~pyspark.sql.Column` or str
+        the binary column.
+    descFilePath : str
+        the protobuf descriptor in Message GeneratedMessageV3 format.
+    messageName: str
+        the protobuf message name to look for in descriptorFile.
+    options : dict, optional
+        options to control how the Protobuf record is parsed.
+
+    Notes
+    -----
+    Protobuf functionality is provided as an pluggable external module since Spark 3.4.0.
+
+    Examples
+    --------
+    >>> from pyspark.sql import Row

Review Comment:
   This example is more complex because it uses both `to_protobuf` & `from_protobuf()`. 
   Majority of the use case would be for `from_protobuf()`. Is it worth simplifying with just `from_protobuf()` demo? We could have some protobuf records in a file.



##########
connector/protobuf/src/test/resources/protobuf/pyspark_test.desc:
##########
@@ -0,0 +1,7 @@
+

Review Comment:
   This could be part of build for tests, similar to how we generate compiled classes during build (same for Scala tests too). We can do that as a follow up with TODO.



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