All Android apps use a main thread to handle UI operations. Calling long-running operations from this main thread can lead to freezes and unresponsiveness. For example, if your app makes a network request from the main thread, your app's UI is frozen until it receives the network response. You can create additional background threads to handle long-running operations while the main thread continues to handle UI updates.
This guide shows both Kotlin and Java Programming Language developers how to use a thread pool to set up and use multiple threads in an Android app. This guide also shows you how to define code to run on a thread and how to communicate between one of these threads and the main thread.
Examples overview
Based on the Guide to app architecture, the examples in this topic make a network request and return the result to the main thread, where the app then might display that result on the screen.
Specifically, the ViewModel calls the repository layer on the main
thread to trigger the network request. The repository layer is in charge
of moving the execution of the network request off the main thread and
posting the result back to the main thread using a callback.
To move the execution of the network request off the main thread, we need to create other threads in our app.
Creating multiple threads
A thread pool
is a managed collection of threads that runs tasks in parallel from a
queue. New tasks are executed on existing threads as those threads
become idle. To send a task to a thread pool, use the
ExecutorService
interface. Note that ExecutorService has nothing to do with
Services, the
Android application component.
Creating threads is expensive, so you should create a thread pool only
once as your app initializes. Be sure to save the instance of the
ExecutorService either
in your Application class or in a
dependency injection container.
The following example creates a thread pool of four threads that we can
use to run background tasks.
Kotlin
class MyApplication : Application() {
val executorService: ExecutorService = Executors.newFixedThreadPool(4)
}
Java
public class MyApplication extends Application {
ExecutorService executorService = Executors.newFixedThreadPool(4);
}
There are other ways you can configure a thread pool depending on expected workload. See Configuring a thread pool for more information.
Executing in a background thread
Making a network request on the main thread causes the thread to wait,
or block, until it receives a response. Since the thread is blocked,
the OS can't call onDraw(), and your app freezes, potentially leading
to an Application Not Responding (ANR) dialog. Instead, let's run this
operation on a background thread.
First, let's take a look at our Repository class and see how it's making
the network request:
Kotlin
sealed class Result<out R> {
data class Success<out T>(val data: T) : Result<T>()
data class Error(val exception: Exception) : Result<Nothing>()
}
class LoginRepository(private val responseParser: LoginResponseParser) {
private const val loginUrl = "https://example.com/login"
// Function that makes the network request, blocking the current thread
fun makeLoginRequest(
jsonBody: String
): Result<LoginResponse> {
val url = URL(loginUrl)
(url.openConnection() as? HttpURLConnection)?.run {
requestMethod = "POST"
setRequestProperty("Content-Type", "application/json; charset=utf-8")
setRequestProperty("Accept", "application/json")
doOutput = true
outputStream.write(jsonBody.toByteArray())
return Result.Success(responseParser.parse(inputStream))
}
return Result.Error(Exception("Cannot open HttpURLConnection"))
}
}
Java
// Result.java
public abstract class Result<T> {
private Result() {}
public static final class Success<T> extends Result<T> {
public T data;
public Success(T data) {
this.data = data;
}
}
public static final class Error<T> extends Result<T> {
public Exception exception;
public Error(Exception exception) {
this.exception = exception;
}
}
}
// LoginRepository.java
public class LoginRepository {
private final String loginUrl = "https://example.com/login";
private final LoginResponseParser responseParser;
public LoginRepository(LoginResponseParser responseParser) {
this.responseParser = responseParser;
}
public Result<LoginResponse> makeLoginRequest(String jsonBody) {
try {
URL url = new URL(loginUrl);
HttpURLConnection httpConnection = (HttpURLConnection) url.openConnection();
httpConnection.setRequestMethod("POST");
httpConnection.setRequestProperty("Content-Type", "application/json; charset=utf-8");
httpConnection.setRequestProperty("Accept", "application/json");
httpConnection.setDoOutput(true);
httpConnection.getOutputStream().write(jsonBody.getBytes("utf-8"));
LoginResponse loginResponse = responseParser.parse(httpConnection.getInputStream());
return new Result.Success<LoginResponse>(loginResponse);
} catch (Exception e) {
return new Result.Error<LoginResponse>(e);
}
}
}
makeLoginRequest() is synchronous and blocks the calling thread. To model
the response of the network request, we have our own Result class.
The ViewModel triggers the network request when the user taps,
for example, on a button:
Kotlin
class LoginViewModel(
private val loginRepository: LoginRepository
) {
fun makeLoginRequest(username: String, token: String) {
val jsonBody = "{ username: \"$username\", token: \"$token\"}"
loginRepository.makeLoginRequest(jsonBody)
}
}
Java
public class LoginViewModel {
private final LoginRepository loginRepository;
public LoginViewModel(LoginRepository loginRepository) {
this.loginRepository = loginRepository;
}
public void makeLoginRequest(String username, String token) {
String jsonBody = "{ username: \"" + username + "\", token: \"" + token + "\" }";
loginRepository.makeLoginRequest(jsonBody);
}
}
With the previous code, LoginViewModel is blocking the main thread
when making the network request. We can use the thread pool that we've
instantiated to move the execution to a background thread. First,
following the principles of dependency injection,
LoginRepository takes an instance of
Executor as opposed to
ExecutorService because it's executing code and not managing threads:
Kotlin
class LoginRepository(
private val responseParser: LoginResponseParser
private val executor: Executor
) { ... }
Java
public class LoginRepository {
...
private final Executor executor;
public LoginRepository(LoginResponseParser responseParser, Executor executor) {
this.responseParser = responseParser;
this.executor = executor;
}
...
}
The Executor's
execute()
method takes a
Runnable.
A Runnable is a Single Abstract Method (SAM) interface with a
run() method that is executed in a thread when invoked.
Let's create another function called makeLoginRequest() that moves the
execution to the background thread and ignores the response for now:
Kotlin
class LoginRepository(
private val responseParser: LoginResponseParser
private val executor: Executor
) {
fun makeLoginRequest(jsonBody: String) {
executor.execute {
val ignoredResponse = makeSynchronousLoginRequest(url, jsonBody)
}
}
private fun makeSynchronousLoginRequest(
jsonBody: String
): Result<LoginResponse> {
... // HttpURLConnection logic
}
}
Java
public class LoginRepository {
...
public void makeLoginRequest(final String jsonBody) {
executor.execute(new Runnable() {
@Override
public void run() {
Result<LoginResponse> ignoredResponse = makeSynchronousLoginRequest(jsonBody);
}
});
}
public Result<LoginResponse> makeSynchronousLoginRequest(String jsonBody) {
... // HttpURLConnection logic
}
...
}
Inside the execute() method, we create a new Runnable with the
block of code we want to execute in the background thread—in our case,
the synchronous network request method. Internally, the ExecutorService
manages the Runnable and executes it in an available thread.
Considerations
Any thread in your app can run in parallel to other threads, including the main thread, so you should ensure that your code is thread-safe. Notice that in our example that we avoid writing to variables shared between threads, passing immutable data instead. This is a good practice, because each thread works with its own instance of data, and we avoid the complexity of synchronization.
If you need to share state between threads, you must be careful to manage access from threads using synchronization mechanisms such as locks. This is outside of the scope of this guide. In general you should avoid sharing mutable state between threads whenever possible.
Communicating with the main thread
In the previous step, we ignored the network request response. To display
the result on the screen, LoginViewModel needs to know about it. We can do
that by using callbacks.
The function makeLoginRequest() should take a callback as a parameter
so that it can return a value asynchronously. The callback with the
result is called whenever the network request completes or a failure occurs.
In Kotlin, we can use a higher-order function. However, in Java, we have to
create a new callback interface to have the same functionality:
Kotlin
class LoginRepository(
private val responseParser: LoginResponseParser
private val executor: Executor
) {
fun makeLoginRequest(
jsonBody: String,
callback: (Result<LoginResponse>) -> Unit
) {
executor.execute {
try {
val response = makeSynchronousLoginRequest(jsonBody)
callback(response)
} catch (e: Exception) {
val errorResult = Result.Error(e)
callback(errorResult)
}
}
}
...
}
Java
interface RepositoryCallback<T> {
void onComplete(Result<T> result);
}
public class LoginRepository {
...
public void makeLoginRequest(
final String jsonBody,
final RepositoryCallback<LoginResponse> callback
) {
executor.execute(new Runnable() {
@Override
public void run() {
try {
Result<LoginResponse> result = makeSynchronousLoginRequest(jsonBody);
callback.onComplete(result);
} catch (Exception e) {
Result<LoginResponse> errorResult = new Result.Error<>(e);
callback.onComplete(errorResult);
}
}
});
}
...
}
The ViewModel needs to implement the callback now. It can perform different
logic depending on the result:
Kotlin
class LoginViewModel(
private val loginRepository: LoginRepository
) {
fun makeLoginRequest(username: String, token: String) {
val jsonBody = "{ username: \"$username\", token: \"$token\"}"
loginRepository.makeLoginRequest(jsonBody) { result ->
when(result) {
is Result.Success<LoginResponse> -> // Happy path
else -> // Show error in UI
}
}
}
}
Java
public class LoginViewModel {
...
public void makeLoginRequest(String username, String token) {
String jsonBody = "{ username: \"" + username + "\", token: \"" + token + "\" }";
loginRepository.makeLoginRequest(jsonBody, new RepositoryCallback<LoginResponse>() {
@Override
public void onComplete(Result<LoginResponse> result) {
if (result instanceof Result.Success) {
// Happy path
} else {
// Show error in UI
}
}
});
}
}
In this example, the callback is executed in the calling thread, which is a background thread. This means that you cannot modify or communicate directly with the UI layer until you switch back to the main thread.
Using handlers
You can use a Handler to enqueue an
action to be performed on a different thread. To specify the thread on
which to run the action, construct the Handler using a
Looper for the thread. A Looper is an
object that runs the message loop for an associated thread. Once you've
created a Handler, you can then use the
post(Runnable)
method to run a block of code in the corresponding thread.
Looper includes a helper function,
getMainLooper(),
which retrieves the Looper of the main thread. You can run code in the
main thread by using this Looper to create a Handler. As this is
something you might do quite often, you can also save an instance of
the Handler in the same place you saved the ExecutorService:
Kotlin
class MyApplication : Application() {
val executorService: ExecutorService = Executors.newFixedThreadPool(4)
val mainThreadHandler: Handler = HandlerCompat.createAsync(Looper.getMainLooper())
}
Java
public class MyApplication extends Application {
ExecutorService executorService = Executors.newFixedThreadPool(4);
Handler mainThreadHandler = HandlerCompat.createAsync(Looper.getMainLooper());
}
It's a good practice to inject the handler to the Repository, as it gives
you more flexibility. For example, in the future you might want to pass in
a different Handler to schedule tasks on a separate thread. If you're
always communicating back to the same thread, you can pass the Handler
into the Repository constructor, as shown in the following example.
Kotlin
class LoginRepository(
...
private val resultHandler: Handler
) {
fun makeLoginRequest(
jsonBody: String,
callback: (Result<LoginResponse>) -> Unit
) {
executor.execute {
try {
val response = makeSynchronousLoginRequest(jsonBody)
resultHandler.post { callback(response) }
} catch (e: Exception) {
val errorResult = Result.Error(e)
resultHandler.post { callback(errorResult) }
}
}
}
...
}
Java
public class LoginRepository {
...
private final Handler resultHandler;
public LoginRepository(LoginResponseParser responseParser, Executor executor,
Handler resultHandler) {
this.responseParser = responseParser;
this.executor = executor;
this.resultHandler = resultHandler;
}
public void makeLoginRequest(
final String jsonBody,
final RepositoryCallback<LoginResponse> callback
) {
executor.execute(new Runnable() {
@Override
public void run() {
try {
Result<LoginResponse> result = makeSynchronousLoginRequest(jsonBody);
notifyResult(result, callback);
} catch (Exception e) {
Result<LoginResponse> errorResult = new Result.Error<>(e);
notifyResult(errorResult, callback);
}
}
});
}
private void notifyResult(
final Result<LoginResponse> result,
final RepositoryCallback<LoginResponse> callback,
) {
resultHandler.post(new Runnable() {
@Override
public void run() {
callback.onComplete(result);
}
});
}
...
}
Alternatively, if you want more flexibility, you can pass in a Handler to each function:
Kotlin
class LoginRepository(...) {
...
fun makeLoginRequest(
jsonBody: String,
resultHandler: Handler,
callback: (Result<LoginResponse>) -> Unit
) {
executor.execute {
try {
val response = makeSynchronousLoginRequest(jsonBody)
resultHandler.post { callback(response) }
} catch (e: Exception) {
val errorResult = Result.Error(e)
resultHandler.post { callback(errorResult) }
}
}
}
}
Java
public class LoginRepository {
...
public void makeLoginRequest(
final String jsonBody,
final RepositoryCallback<LoginResponse> callback,
final Handler resultHandler,
) {
executor.execute(new Runnable() {
@Override
public void run() {
try {
Result<LoginResponse> result = makeSynchronousLoginRequest(jsonBody);
notifyResult(result, callback, resultHandler);
} catch (Exception e) {
Result<LoginResponse> errorResult = new Result.Error<>(e);
notifyResult(errorResult, callback, resultHandler);
}
}
});
}
private void notifyResult(
final Result<LoginResponse> result,
final RepositoryCallback<LoginResponse> callback,
final Handler resultHandler
) {
resultHandler.post(new Runnable() {
@Override
public void run() {
callback.onComplete(result);
}
});
}
}
In this example, the callback passed into the Repository's makeLoginRequest
call is executed on the main thread. That means you can directly modify the
UI from the callback or use LiveData.setValue() to communicate with the UI.
Configuring a thread pool
You can create a thread pool using one of the
Executor helper functions
with predefined settings, as shown in the previous example code.
Alternatively, if you want to customize the details of the thread
pool, you can create an instance using
ThreadPoolExecutor
directly. You can configure the following details:
- Initial and maximum pool size.
- Keep alive time and time unit. Keep alive time is the maximum duration that a thread can remain idle before it shuts down.
- An input queue that holds
Runnabletasks. This queue must implement theBlockingQueueinterface. To match the requirements of your app, you can choose from the available queue implementations. To learn more, see the class overview forThreadPoolExecutor.
Here's an example that specifies thread pool size based on the total number of processor cores, a keep alive time of one second, and an input queue.
Kotlin
class MyApplication : Application() {
/*
* Gets the number of available cores
* (not always the same as the maximum number of cores)
*/
private val NUMBER_OF_CORES = Runtime.getRuntime().availableProcessors()
// Instantiates the queue of Runnables as a LinkedBlockingQueue
private val workQueue: BlockingQueue<Runnable> =
LinkedBlockingQueue<Runnable>()
// Sets the amount of time an idle thread waits before terminating
private const val KEEP_ALIVE_TIME = 1L
// Sets the Time Unit to seconds
private val KEEP_ALIVE_TIME_UNIT = TimeUnit.SECONDS
// Creates a thread pool manager
private val threadPoolExecutor: ThreadPoolExecutor = ThreadPoolExecutor(
NUMBER_OF_CORES, // Initial pool size
NUMBER_OF_CORES, // Max pool size
KEEP_ALIVE_TIME,
KEEP_ALIVE_TIME_UNIT,
workQueue
)
}
Java
public class MyApplication extends Application {
/*
* Gets the number of available cores
* (not always the same as the maximum number of cores)
*/
private static int NUMBER_OF_CORES = Runtime.getRuntime().availableProcessors();
// Instantiates the queue of Runnables as a LinkedBlockingQueue
private final BlockingQueue<Runnable> workQueue = new LinkedBlockingQueue<Runnable>();
// Sets the amount of time an idle thread waits before terminating
private static final int KEEP_ALIVE_TIME = 1;
// Sets the Time Unit to seconds
private static final TimeUnit KEEP_ALIVE_TIME_UNIT = TimeUnit.SECONDS;
// Creates a thread pool manager
ThreadPoolExecutor threadPoolExecutor = new ThreadPoolExecutor(
NUMBER_OF_CORES, // Initial pool size
NUMBER_OF_CORES, // Max pool size
KEEP_ALIVE_TIME,
KEEP_ALIVE_TIME_UNIT,
workQueue
);
...
}
Concurrency libraries
It's important to understand the basics of threading and its underlying mechanisms. There are, however, many popular libraries that offer higher-level abstractions over these concepts and ready-to-use utilities for passing data between threads. These libraries include Guava and RxJava for the Java Programming Language users and coroutines, which we recommend for Kotlin users.
In practice, you should pick the one that works best for your app and your development team, though the rules of threading remain the same.
See also
For more information about processes and threads in Android, see Process and threads overview.