How do you deal with concurrency and threading issues in MVVM with Java?

1 Use LiveData

LiveData is a class that holds observable data and notifies the observers when the data changes. It is part of the Android Architecture Components, a set of libraries that help you design robust and maintainable Android apps. LiveData is designed to work well with MVVM, as it can be used as a source of data for the viewmodel and as a way to update the view. LiveData also handles the lifecycle of the observers, so you don't have to worry about memory leaks or inconsistent UI states.

2 Use Coroutines

Coroutines are a way of writing asynchronous code in a sequential and readable way. They are based on the concept of suspending functions, which can pause and resume their execution without blocking the thread. Coroutines are supported by Kotlin, a modern and concise programming language that is interoperable with Java. You can use coroutines to perform background tasks, such as fetching data from a network or a database, and then update the viewmodel and the LiveData accordingly. Coroutines also offer various tools and libraries to handle concurrency, such as scopes, contexts, dispatchers, and channels.

4 Use Synchronization

Synchronization is a mechanism that ensures that only one thread can access a shared resource at a time. It is essential to avoid data inconsistency, race conditions, or deadlocks when multiple threads are modifying the same data. Synchronization can be achieved using various techniques, such as locks, semaphores, or monitors. You can use synchronization to protect the data that is shared between the model and the viewmodel, or between different instances of the viewmodel. However, you should be careful not to overuse synchronization, as it can degrade the performance or cause thread starvation.

5 Use Reactive Streams

Reactive streams are a standard for asynchronous and non-blocking data streams that support backpressure. Backpressure is a way of controlling the flow of data between the producer and the consumer, so that the consumer can signal how much data it can handle at a time. Reactive streams can be useful for dealing with large or infinite data sources, such as sensors, web sockets, or event streams. You can use reactive streams to create observable data sources for the viewmodel and the LiveData, and to apply transformations, filters, or operators on them. Reactive streams can be implemented using various libraries, such as RxJava, Flow, or Reactor.