Merge pull request #1520 from simophin/fix-threading-issue

Remove the use of executor in ThreadUtils
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ThomasSession 2024-06-24 16:50:33 +10:00 committed by GitHub
commit 9c20ca2017
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2 changed files with 7 additions and 26 deletions

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@ -1,5 +1,7 @@
package org.thoughtcrime.securesms
import kotlinx.coroutines.Dispatchers
import kotlinx.coroutines.asExecutor
import nl.komponents.kovenant.Kovenant
import nl.komponents.kovenant.jvm.asDispatcher
import org.session.libsignal.utilities.Log
@ -11,7 +13,7 @@ object AppContext {
fun configureKovenant() {
Kovenant.context {
callbackContext.dispatcher = Executors.newSingleThreadExecutor().asDispatcher()
workerContext.dispatcher = ThreadUtils.executorPool.asDispatcher()
workerContext.dispatcher = Dispatchers.IO.asExecutor().asDispatcher()
multipleCompletion = { v1, v2 ->
Log.d("Loki", "Promise resolved more than once (first with $v1, then with $v2); ignoring $v2.")
}

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@ -1,11 +1,13 @@
package org.session.libsignal.utilities
import android.os.Process
import kotlinx.coroutines.Dispatchers
import java.util.concurrent.ExecutorService
import java.util.concurrent.LinkedBlockingQueue
import java.util.concurrent.SynchronousQueue
import java.util.concurrent.ThreadPoolExecutor
import java.util.concurrent.TimeUnit
import kotlin.coroutines.EmptyCoroutineContext
object ThreadUtils {
@ -13,39 +15,16 @@ object ThreadUtils {
const val PRIORITY_IMPORTANT_BACKGROUND_THREAD = Process.THREAD_PRIORITY_DEFAULT + Process.THREAD_PRIORITY_LESS_FAVORABLE
// Paraphrased from: https://www.baeldung.com/kotlin/create-thread-pool
// "A cached thread pool such as one created via:
// `val executorPool: ExecutorService = Executors.newCachedThreadPool()`
// will utilize resources according to the requirements of submitted tasks. It will try to reuse
// existing threads for submitted tasks but will create as many threads as it needs if new tasks
// keep pouring in (with a memory usage of at least 1MB per created thread). These threads will
// live for up to 60 seconds of idle time before terminating by default. As such, it presents a
// very sharp tool that doesn't include any backpressure mechanism - and a sudden peak in load
// can bring the system down with an OutOfMemory error. We can achieve a similar effect but with
// better control by creating a ThreadPoolExecutor manually."
private val corePoolSize = Runtime.getRuntime().availableProcessors() // Default thread pool size is our CPU core count
private val maxPoolSize = corePoolSize * 4 // Allow a maximum pool size of up to 4 threads per core
private val keepAliveTimeSecs = 100L // How long to keep idle threads in the pool before they are terminated
private val workQueue = SynchronousQueue<Runnable>()
val executorPool: ExecutorService = ThreadPoolExecutor(corePoolSize, maxPoolSize, keepAliveTimeSecs, TimeUnit.SECONDS, workQueue)
// Note: To see how many threads are running in our app at any given time we can use:
// val threadCount = getAllStackTraces().size
@JvmStatic
fun queue(target: Runnable) {
executorPool.execute {
try {
target.run()
} catch (e: Exception) {
Log.e(TAG, e)
}
}
queue(target::run)
}
fun queue(target: () -> Unit) {
executorPool.execute {
Dispatchers.IO.dispatch(EmptyCoroutineContext) {
try {
target()
} catch (e: Exception) {