cleaner handling of connection loss

implemented ordered/unordered task result delivery


git-svn-id: https://pycam.svn.sourceforge.net/svnroot/pycam/trunk@748 bbaffbd6-741e-11dd-a85d-61de82d9cad9

src/pycam/Utils/threading.py

@@ -83,8 +83,8 @@ def init_threading(number_of_processes=None, enable_server=False, remote=None, r
                 __num_of_processes = multiprocessing.cpu_count()
             else:
                 __multiprocessing = False
-        elif (number_of_processes < 1) and (remote is None):
-            # zero processes are allowed if we use a remote server
+        elif (number_of_processes < 1) and (remote is None) and (enable_server is None):
+            # zero processes are allowed if we use a remote server or offer a server
             __multiprocessing = False
         else:
             __multiprocessing = multiprocessing
@@ -168,7 +168,10 @@ def cleanup():
     global __manager, __closing
     if __multiprocessing and __closing:
         log.debug("Shutting down process handler")
+        try:
             __closing.set(True)
+        except EOFError:
+            log.debug("Connection to manager lost during cleanup")
         # Only managers that were started via ".start()" implement a "shutdown".
         # Managers started via ".connect" may skip this.
         if hasattr(__manager, "shutdown"):
@@ -204,9 +207,12 @@ def _spawn_daemon(manager, number_of_processes, worker_uuid_list):
             else:
                 time.sleep(0.2)
     except KeyboardInterrupt:
-        log.debug("Spawner daemon killed by keyboard interrupt")
+        log.info("Spawner daemon killed by keyboard interrupt")
         # set the "closing" flag and just exit
         __closing.set(True)
+    except EOFError:
+        # the connection was closed
+        log.info("Spawner daemon lost connection to server")
 
 def _handle_tasks(tasks, results, stats, cache, closing):
     global __multiprocessing
@@ -219,7 +225,7 @@ def _handle_tasks(tasks, results, stats, cache, closing):
         while (timeout_counter < timeout_limit) and not closing.get():
             try:
                 start_time = time.time()
-                job_id, func, args = tasks.get(timeout=1.0)
+                job_id, task_id, func, args = tasks.get(timeout=1.0)
                 real_args = []
                 for arg in args:
                     if isinstance(arg, ProcessDataCacheItemID):
@@ -231,7 +237,7 @@ def _handle_tasks(tasks, results, stats, cache, closing):
                         real_args.append(arg)
                 stats.add_transfer_time(name, time.time() - start_time)
                 start_time = time.time()
-                results.put((job_id, func(*real_args)))
+                results.put((job_id, task_id, func(*real_args)))
                 stats.add_process_time(name, time.time() - start_time)
             except Queue.Empty:
                 time.sleep(1.0)
@@ -254,7 +260,7 @@ def run_in_parallel_remote(func, args_list, unordered=False,
         results_queue = __manager.results()
         remote_cache = __manager.cache()
         stats = __manager.statistics()
-        for args in args_list:
+        for index, args in enumerate(args_list):
             start_time = time.time()
             result_args = []
             for arg in args:
@@ -267,18 +273,34 @@ def run_in_parallel_remote(func, args_list, unordered=False,
                     result_args.append(data_uuid)
                 else:
                     result_args.append(arg)
-            tasks_queue.put((job_id, func, result_args))
+            tasks_queue.put((job_id, index, func, result_args))
             stats.add_queueing_time(__task_source_uuid, time.time() - start_time)
         log.debug("Added %d tasks for job %s" % (len(args_list), job_id))
         def job_cleanup():
             print stats.get_stats()
-        for index in range(len(args_list)):
+        result_buffer = {}
+        index = 0
+        while index < len(args_list):
             try:
                 result_job_id = None
                 while result_job_id != job_id:
-                    result_job_id, result = results_queue.get()
+                    result_job_id, task_id, result = results_queue.get()
                     if result_job_id == job_id:
+                        if unordered:
+                            # just return the values in any order
                             yield result
+                            index += 1
+                        else:
+                            # return the results in order (based on task_id)
+                            if task_id == index:
+                                yield result
+                                index += 1
+                                while index in result_buffer.keys():
+                                    yield result_buffer[index]
+                                    del result_buffer[index]
+                                    index += 1
+                            else:
+                                result_buffer[task_id] = result
                     elif result_job_id in __finished_jobs:
                         # throw away this result of an old job
                         log.debug("Throwing away a result of an old task: %s" % result_job_id)
@@ -296,9 +318,9 @@ def run_in_parallel_remote(func, args_list, unordered=False,
                 # remove all remaining tasks with the current job id
                 removed_job_counter = 0
                 for index in range(queue_len):
-                    this_job_id, func, args = tasks_queue.get(timeout=0.1)
+                    this_job_id, task_id, func, args = tasks_queue.get(timeout=0.1)
                     if this_job_id != job_id:
-                        tasks_queue.put((this_job_id, func, args))
+                        tasks_queue.put((this_job_id, task_id, func, args))
                     else:
                         removed_job_counter += 1
                 if removed_job_counter > 0: