[SES-1930] Catch HTTP exceptions from threads (#1491)

* Catch HTTP exceptions

* Fixes #1490

* Removed catch blocks that won't actually catch due to thread execution pool reasons & added a thread limiting mechanism to prevent excessive thread creation (when the queue is full then further tasks are queued)

* Corrected thread exception catching (hopefully)

* Addressed PR feedback

* Reverted build number bump used for testing without reinstall

* Added print of stack trace to any caught thread exceptions

* Log exception directly and do not print stack trace on thread exception

* Added TAG for logging output

---------

Co-authored-by: alansley <aclansley@gmail.com>

libsignal/src/main/java/org/session/libsignal/utilities/ThreadUtils.kt

@@ -1,23 +1,60 @@
 package org.session.libsignal.utilities
 
 import android.os.Process
-import java.util.concurrent.*
+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
 
 object ThreadUtils {
 
+    const val TAG = "ThreadUtils"
+
     const val PRIORITY_IMPORTANT_BACKGROUND_THREAD = Process.THREAD_PRIORITY_DEFAULT + Process.THREAD_PRIORITY_LESS_FAVORABLE
 
-    val executorPool: ExecutorService = Executors.newCachedThreadPool()
+    // 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(target)
+        executorPool.execute {
+            try {
+                target.run()
+            } catch (e: Exception) {
+                Log.e(TAG, e)
+            }
+        }
     }
 
     fun queue(target: () -> Unit) {
-        executorPool.execute(target)
+        executorPool.execute {
+            try {
+                target()
+            } catch (e: Exception) {
+                Log.e(TAG, e)
+            }
+        }
     }
 
+    // Thread executor used by the audio recorder only
     @JvmStatic
     fun newDynamicSingleThreadedExecutor(): ExecutorService {
         val executor = ThreadPoolExecutor(1, 1, 60, TimeUnit.SECONDS, LinkedBlockingQueue())