Review - 1 changes

[SandishKumarHN]

From SandishKumarHN(sanysandish@gmail.com) and Mohan Parthasarathy(mposdev21@gmail.com)

Introduction

Protocol buffers are Google's language-neutral, platform-neutral, extensible mechanism for serializing structured data. It is widely used in Kafka-based data pipelines. Unlike Avro, Spark does not have native support for protobuf. This PR provides two new functions from_proto/to_proto to read and write Protobuf data within a data frame.

The implementation is closely modeled after Avro implementation so that it is easy to understand and review the changes.

Following is an example of a typical usage.

// `from_proto` requires absolute path of Protobuf schema file
// and the protobuf message within the file
val userProtoFile = "./examples/src/main/resources/user.desc"
val userProtoMsg = "User"

val df = spark
  .readStream
  .format("kafka")
  .option("kafka.bootstrap.servers", "host1:port1,host2:port2")
  .option("subscribe", "proto-topic-in")
  .load()

// 1. Decode the Protobuf data into a struct;
// 2. Filter by column `favorite_color`;
// 3. Encode the column `name` in Protobuf format.
val output = df
  .select(from_proto('value, userProtoFile, userProtoMsg) as 'user)
  .where("user.favorite_color == \"red\"")
  .select(to_proto($"user.name") as 'value)

val query = output
  .writeStream
  .format("kafka")
  .option("kafka.bootstrap.servers", "host1:port1,host2:port2")
  .option("topic", "proto-topic-out")
  .start()

The new functions are very similar to Avro

• from_proto requires the proto descriptor file and the message type within that file which is similar to from_avro requiring the JSON schema.
• to_proto is similar to to_avro and does not require the proto descriptor file as it can build the schema (protobuf descriptor) from the catalyst types. Similarly, to_proto (like to_avro) can also take in the descriptor file for describing the schema

What is supported

• Protobuf format proto3 is supported ( Even though proto2 and proto3 is inter-operable, we have explicitly tested only with proto3)
• Google protobuf supported types
  • Scalar value types
  • Enumerations
  • Message types as field types
  • Nested Messages
  • Maps
  • Unknown fields are well-formed protocol buffer serialized data representing fields that the parser does not recognize. Original version of proto3 did not include this when there are parsing problems. This feature is needed to detect schemas that does not match the message type and needed to support FAIL_SAFE and PERMISSIVE mode. This feature is available in proto3 with version. 3.5 onwards

What is not supported

• Any requires the knowledge of the underlying object type when deserializing the message and generally not considered type safe
• OneOf requires the knowledge of the object type that was encoded when deserializing the message
• Custom Options is an advanced feature within protobuf where the users can define their own options
• Catalyst types that are not natively supported in protobuf. This happens normally during serialization and an exception will be thrown when following types are encountered
  • DecimalType
  • DateType
  • TimestampType

Test cases covered

Tests have been written to test at different levels

• from_proto / to_proto (ProtoFunctionSuite)
• ProtoToCatalyst / CatalystToProto (ProtoCatalystDataConversionSuite)
• ProtoDeserializer / ProtoSerializer (ProtoSerdeSuite)

ProtoFunctionSuite

A bunch of roundtrip tests that go through to_proto(from_proto) or from_proto(to_proto) and compare the results. It also repeats some of the tests where to_proto is called without a descriptor file where the protobuf descriptor is built from the catalyst types.

• roundtrip in to_proto and from_proto for struct for protobuf scalar types
• roundtrip in to_proto(without descriptor params) and from_proto - struct for protobuf scalar types
• roundtrip in from_proto and to_proto - Repeated protobuf types
• roundtrip in from_proto and to_proto - Repeated Message Once
• roundtrip in from_proto and to_proto(without descriptor params) - Repeated Message Once”
• roundtrip in from_proto and to_proto - Repeated Message Twice
• roundtrip in from_proto and to_proto(without descriptor params) - Repeated Message Twice
• roundtrip in from_proto and to_proto - Map
• roundtrip in from_proto and to_proto(without descriptor params) - Map
• roundtrip in from_proto and to_proto - Enum
• roundtrip in from_proto and to_proto - Multiple Message
• roundtrip in from_proto and to_proto(without descriptor params) - Multiple Message
• roundtrip in to_proto and from_proto - with null

ProtoSerdeSuite

• Test basic conversion - serialize(deserialize(message)) == message
• Fail to convert with field type mismatch - Make sure the right exception is thrown for incompatible schema for serializer and deserializer
• Fail to convert with missing nested Proto fields
• Fail to convert with deeply nested field type mismatch
• Fail to convert with missing Catalyst fields

ProtoCatalystDataConversionSuite

• ProtoToCatalyst(to_proto(basic_catalyst_types )): Boolean,Integer,Double,Float,Binary,String,Byte,Shost
• Handle unsupported input of Message type: Serialize a message first and deserialize using a bad schema. Test with FAILFAST to get an exception and PERMISSIVE to get a null row
• filter push-down to proto deserializer: Filtering the rows based on the filter during proto deserialization
• Test ProtoDeserializer with binary message type

[github-actions]

We're closing this PR because it hasn't been updated in a while. This isn't a judgement on the merit of the PR in any way. It's just a way of keeping the PR queue manageable.
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