Practical API Design at Netflix, Part 1: Using Protobuf FieldMask | by Netflix Technology Blog | Sep, 2021

Practical API Design at Netflix, Part 1: Using Protobuf FieldMask | by Netflix Technology Blog | Sep, 2021


As we see, if a field is renamed, the backend should be able to support new and old field names until all the callers migrate to the new field name (backward compatibility issue).

There are multiple ways to deal with this limitation:

  • Never rename fields when FieldMask is used. This is the simplest solution, but it’s not always possible
  • Require the backend to support all the old field names. This solves the backward compatibility issue but requires extra code on the backend to keep track of all historical field names
  • Deprecate old and create a new field instead of renaming. In our example, we would create the title_name field number 6. This option has some advantages over the previous one: it allows the producer to keep using generated descriptors instead of custom converters; also, deprecating a field makes it more prominent on the consumer side

Regardless of the solution, it is important to remember that FieldMask makes field names an integral part of your API contract.

Using FieldMask on the Producer (Server) Side

On the producer (server) side, unnecessary fields can be removed from the response payload using the FieldMaskUtil.merge() method (lines ##8 and 9):

If the server code also needs to know which fields are requested in order to avoid making external calls, database queries or expensive computations, this information can be obtained from the FieldMask paths field:

This code calls the makeExpensiveCallToScheduleServicemethod (line #21) only if the schedule field is requested. Let’s explore this code sample in more detail.

(1) The SCHEDULE_FIELD_NAME constant contains the name of the field. This code sample uses message type Descriptor and FieldDescriptor to lookup field name by field number. The difference between protobuf field names and field numbers is described in the Protobuf Field Names vs Field Numbers section above.

(2) FieldMaskUtil.normalize() returns FieldMask with alphabetically sorted and deduplicated field paths (aka canonical form).

(3) Expression (lines ##14 – 17) that yields the scheduleFieldRequestedvalue takes a stream of FieldMask paths, maps it to a stream of top-level fields, and returns true if top-level fields contain the value of the SCHEDULE_FIELD_NAME constant.

(4) ProductionSchedule is retrieved only if scheduleFieldRequested is true.

If you end up using FieldMask for different messages and fields, consider creating reusable utility helper methods. For example, a method that returns all top-level fields based on FieldMask and FieldDescriptor, a method to return if a field is present in a FieldMask, etc.

Some access patterns can be more common than others. If multiple consumers are interested in the same subset of fields, API producers can ship client libraries with FieldMask pre-built for the most frequently used field combinations.

Providing pre-built field masks simplifies API usage for the most common scenarios and leaves consumers the flexibility to build their own field masks for more specific use-cases.

  • Using FieldMask can limit your ability to rename message fields (described in the Protobuf Field Names vs Field Numbers section)
  • Repeated fields are only allowed in the last position of a path string. This means you cannot select (mask) individual sub-fields in a message inside a list. This can change in the foreseeable future, as a recently approved Google API Improvement Proposal AIP-161 Field masks includes support for wildcards on repeated fields.

Protobuf FieldMask is a simple, yet powerful concept. It can help make APIs more robust and service implementations more efficient.

This blog post covered how and why it is used at Netflix Studio Engineering for APIs that read the data. Part 2 will shed light on using FieldMask for update and remove operations.



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