Streaming the Graph: Architecting Flow-Based Progressive Hydration in Android

In the world of mobile, the “all-or-nothing” data fetching model is a UX killer. When a single slow field in your GraphQL query—like a complex pricing calculation or an AI-generated summary—holds up the entire response, your users are left staring at a blank screen.

The GraphQL @defer directive offers a solution, but implementing it on Android requires more than just adding a keyword to your schema. It requires a fundamental shift in how we architect our data layer.

In this session, we will dive deep into building a Flow-based Defer Architecture. We will explore how to leverage Apollo Kotlin 4.x to transform multi-part GraphQL responses into a seamless stream of data using Kotlin Flow.

Key takeaways from this session:

• The Blueprint: How to structure your domain layer to handle incremental updates without triggering unnecessary UI “flicker.”
• Flow & Compose Integration: Techniques for collecting deferred emissions in Jetpack Compose to achieve smooth, progressive UI hydration.
• Error Handling in a Partial World: Strategies for managing failures when the primary data arrives but the deferred fragment fails.
• Performance Deep Dive: Monitoring the impact of @defer on battery life and network overhead compared to traditional polling or multiple queries.