Exemplo n.º 1
0
    def test_score_job_exe_for_reservation_insufficient_resources(self):
        """Tests calling score_job_exe_for_reservation() when there are not enough resources to reserve for the job"""

        node = MagicMock()
        node.hostname = 'host_1'
        node.id = 1
        node.is_ready_for_new_job = MagicMock()
        node.is_ready_for_new_job.return_value = True
        node.is_ready_for_next_job_task = MagicMock()
        node.is_ready_for_next_job_task.return_value = True
        offered_resources = NodeResources([Cpus(20.0), Mem(100.0)])
        watermark_resources = NodeResources([Cpus(200.0), Mem(700.0)])
        resource_set = ResourceSet(offered_resources, NodeResources(),
                                   watermark_resources)
        task = HealthTask(
            '1234', 'agent_1')  # Resources are 0.1 CPUs and 32 MiB memory
        job_exe_1 = job_test_utils.create_running_job_exe(
            agent_id=self.agent_id,
            resources=NodeResources([Cpus(10.0), Mem(50.0)]),
            priority=1000)
        job_exe_2 = job_test_utils.create_running_job_exe(
            agent_id=self.agent_id,
            resources=NodeResources([Cpus(56.0), Mem(15.0)]),
            priority=100)
        scheduling_node = SchedulingNode('agent_1', node, [task],
                                         [job_exe_1, job_exe_2], resource_set)
        queue_model_1 = queue_test_utils.create_queue(priority=100,
                                                      cpus_required=8.0,
                                                      mem_required=40.0,
                                                      disk_in_required=0.0,
                                                      disk_out_required=0.0,
                                                      disk_total_required=0.0)
        job_exe_1 = QueuedJobExecution(queue_model_1)
        queue_model_2 = queue_test_utils.create_queue(priority=1000,
                                                      cpus_required=8.0,
                                                      mem_required=40.0,
                                                      disk_in_required=0.0,
                                                      disk_out_required=0.0,
                                                      disk_total_required=0.0)
        job_exe_2 = QueuedJobExecution(queue_model_2)
        scheduling_node.accept_new_job_exe(job_exe_1)
        scheduling_node.accept_new_job_exe(job_exe_2)

        # We are going to try to reserve the node for a job execution with priority 120
        # Calculate available resources for reservation:
        # Watermark (200, 700) - System Tasks (0.1, 32) - Higher Priority Existing Job Exes (56, 15) -  Higher Priority
        # New Job Exes (8, 40) = 135.9 CPUs, 613 memory
        # This new job should NOT fit for reservation
        queue_model = queue_test_utils.create_queue(priority=120,
                                                    cpus_required=140.0,
                                                    mem_required=600.0,
                                                    disk_in_required=0.0,
                                                    disk_out_required=0.0,
                                                    disk_total_required=0.0)
        job_exe = QueuedJobExecution(queue_model)
        job_type_resource_1 = NodeResources([Cpus(2.0), Mem(10.0)])

        score = scheduling_node.score_job_exe_for_reservation(
            job_exe, [job_type_resource_1])
        self.assertIsNone(score)
Exemplo n.º 2
0
    def test_accept_new_job_exe_no_jobs(self):
        """Tests calling accept_new_job_exe() when new job exes are not allowed"""

        node = MagicMock()
        node.hostname = 'host_1'
        node.id = 1
        node.is_ready_for_new_job = MagicMock()
        node.is_ready_for_new_job.return_value = False
        node.is_ready_for_next_job_task = MagicMock()
        node.is_ready_for_next_job_task.return_value = True
        offered_resources = NodeResources([Cpus(10.0), Mem(50.0)])
        task_resources = NodeResources()
        watermark_resources = NodeResources([Cpus(100.0), Mem(500.0)])
        resource_set = ResourceSet(offered_resources, task_resources,
                                   watermark_resources)
        scheduling_node = SchedulingNode('agent_1', node, [], [], resource_set)

        queue_model = queue_test_utils.create_queue(cpus_required=1.0,
                                                    mem_required=10.0,
                                                    disk_in_required=0.0,
                                                    disk_out_required=0.0,
                                                    disk_total_required=0.0)
        job_exe = QueuedJobExecution(queue_model)

        accepted = scheduling_node.accept_new_job_exe(job_exe)
        self.assertFalse(accepted)
        self.assertEqual(len(scheduling_node._allocated_queued_job_exes), 0)
        self.assertTrue(
            scheduling_node.allocated_resources.is_equal(NodeResources()))
        self.assertTrue(
            scheduling_node._remaining_resources.is_equal(
                NodeResources([Cpus(10.0), Mem(50.0)])))
        self.assertIsNone(job_exe._scheduled_node_id)
Exemplo n.º 3
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    def test_accept_new_job_exe_gpu_partial_node_other_task(self):
        """Tests successfully calling accept_new_job_exe() when job requires less GPUs than available"""

        node = MagicMock()
        node.hostname = 'host_1'
        node.id = 1
        node.is_ready_for_new_job = MagicMock()
        node.is_ready_for_new_job.return_value = True
        node.is_ready_for_next_job_task = MagicMock()
        node.is_ready_for_next_job_task.return_value = True
        offered_resources = NodeResources([Cpus(10.0), Mem(50.0), Gpus(1.0)])
        task_resources = NodeResources([Gpus(1.0)])
        watermark_resources = NodeResources(
            [Cpus(100.0), Mem(500.0), Gpus(1.0)])
        resource_set = ResourceSet(offered_resources, task_resources,
                                   watermark_resources)
        scheduling_node = SchedulingNode('agent_1', node, [], [], resource_set)

        queue_model = queue_test_utils.create_queue(cpus_required=1.0,
                                                    mem_required=10.0,
                                                    disk_in_required=0.0,
                                                    disk_out_required=0.0,
                                                    disk_total_required=0.0,
                                                    gpus_required=2)
        job_exe = QueuedJobExecution(queue_model)

        accepted = scheduling_node.accept_new_job_exe(job_exe)
        self.assertFalse(accepted)
Exemplo n.º 4
0
    def test_reset_new_job_exes(self):
        """Tests calling reset_new_job_exes() successfully"""

        node = MagicMock()
        node.hostname = 'host_1'
        node.id = 1
        node.is_ready_for_new_job = MagicMock()
        node.is_ready_for_new_job.return_value = True
        node.is_ready_for_next_job_task = MagicMock()
        node.is_ready_for_next_job_task.return_value = True
        offered_resources = NodeResources([Cpus(100.0), Mem(500.0)])
        watermark_resources = NodeResources([Cpus(100.0), Mem(500.0)])
        resource_set = ResourceSet(offered_resources, NodeResources(),
                                   watermark_resources)
        scheduling_node = SchedulingNode('agent_1', node, [], [], resource_set)
        queue_model_1 = queue_test_utils.create_queue(cpus_required=2.0,
                                                      mem_required=60.0,
                                                      disk_in_required=0.0,
                                                      disk_out_required=0.0,
                                                      disk_total_required=0.0)
        job_exe_1 = QueuedJobExecution(queue_model_1)
        queue_model_2 = queue_test_utils.create_queue(cpus_required=4.5,
                                                      mem_required=400.0,
                                                      disk_in_required=0.0,
                                                      disk_out_required=0.0,
                                                      disk_total_required=0.0)
        job_exe_2 = QueuedJobExecution(queue_model_2)
        allocated_resources = NodeResources()
        allocated_resources.add(job_exe_1.required_resources)
        allocated_resources.add(job_exe_2.required_resources)

        # Set up node with queued job exes
        scheduling_node.accept_new_job_exe(job_exe_1)
        scheduling_node.accept_new_job_exe(job_exe_2)
        self.assertEqual(len(scheduling_node._allocated_queued_job_exes), 2)
        self.assertTrue(
            scheduling_node.allocated_resources.is_equal(allocated_resources))

        # Reset queued job exes and check that everything is back to square one
        scheduling_node.reset_new_job_exes()
        self.assertEqual(len(scheduling_node._allocated_queued_job_exes), 0)
        self.assertTrue(
            scheduling_node.allocated_resources.is_equal(NodeResources()))
        self.assertTrue(
            scheduling_node._remaining_resources.is_equal(offered_resources))
Exemplo n.º 5
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    def test_accept_new_job_exe_gpu_partial_node(self):
        """Tests successfully calling accept_new_job_exe() when job requires less GPUs than available"""

        node = MagicMock()
        node.hostname = 'host_1'
        node.id = 1
        node.is_ready_for_new_job = MagicMock()
        node.is_ready_for_new_job.return_value = True
        node.is_ready_for_next_job_task = MagicMock()
        node.is_ready_for_next_job_task.return_value = True
        offered_resources = NodeResources([Cpus(10.0), Mem(50.0), Gpus(4.0)])
        task_resources = NodeResources()
        watermark_resources = NodeResources(
            [Cpus(100.0), Mem(500.0), Gpus(4.0)])
        resource_set = ResourceSet(offered_resources, task_resources,
                                   watermark_resources)
        scheduling_node = SchedulingNode('agent_1', node, [], [], resource_set)

        queue_model = queue_test_utils.create_queue(cpus_required=1.0,
                                                    mem_required=10.0,
                                                    disk_in_required=0.0,
                                                    disk_out_required=0.0,
                                                    disk_total_required=0.0,
                                                    gpus_required=1)
        job_exe = QueuedJobExecution(queue_model)

        accepted = scheduling_node.accept_new_job_exe(job_exe)
        self.assertTrue(accepted)
        self.assertEqual(len(scheduling_node._allocated_queued_job_exes), 1)
        # Verify that our greedy GPU allocation logic is working
        self.assertTrue(
            scheduling_node.allocated_resources.is_equal(
                NodeResources([Cpus(1.0), Mem(10.0),
                               Gpus(4.0)])))
        self.assertTrue(
            scheduling_node._remaining_resources.is_equal(
                NodeResources([Cpus(9.0), Mem(40.0)])))
        self.assertEqual(job_exe._scheduled_node_id, node.id)
Exemplo n.º 6
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    def test_score_job_exe_for_reservation(self):
        """Tests calling score_job_exe_for_reservation() successfully"""

        node = MagicMock()
        node.hostname = 'host_1'
        node.id = 1
        node.is_ready_for_new_job = MagicMock()
        node.is_ready_for_new_job.return_value = True
        node.is_ready_for_next_job_task = MagicMock()
        node.is_ready_for_next_job_task.return_value = True
        offered_resources = NodeResources([Cpus(20.0), Mem(100.0)])
        watermark_resources = NodeResources([Cpus(200.0), Mem(700.0)])
        resource_set = ResourceSet(offered_resources, NodeResources(),
                                   watermark_resources)
        task = HealthTask(
            '1234', 'agent_1')  # Resources are 0.1 CPUs and 32 MiB memory
        job_exe_1 = job_test_utils.create_running_job_exe(
            agent_id=self.agent_id,
            resources=NodeResources([Cpus(10.0), Mem(50.0)]),
            priority=1000)
        job_exe_2 = job_test_utils.create_running_job_exe(
            agent_id=self.agent_id,
            resources=NodeResources([Cpus(56.0), Mem(15.0)]),
            priority=100)
        scheduling_node = SchedulingNode('agent_1', node, [task],
                                         [job_exe_1, job_exe_2], resource_set)
        queue_model_1 = queue_test_utils.create_queue(priority=100,
                                                      cpus_required=8.0,
                                                      mem_required=40.0,
                                                      disk_in_required=0.0,
                                                      disk_out_required=0.0,
                                                      disk_total_required=0.0)
        job_exe_1 = QueuedJobExecution(queue_model_1)
        queue_model_2 = queue_test_utils.create_queue(priority=1000,
                                                      cpus_required=8.0,
                                                      mem_required=40.0,
                                                      disk_in_required=0.0,
                                                      disk_out_required=0.0,
                                                      disk_total_required=0.0)
        job_exe_2 = QueuedJobExecution(queue_model_2)
        scheduling_node.accept_new_job_exe(job_exe_1)
        scheduling_node.accept_new_job_exe(job_exe_2)

        # We are going to try to reserve the node for a job execution with priority 120
        # Calculate available resources for reservation:
        # Watermark (200, 700) - System Tasks (0.1, 32) - Higher Priority Existing Job Exes (56, 15) -  Higher Priority
        # New Job Exes (8, 40) = 135.9 CPUs, 613 memory
        # This new job should fit for reservation
        queue_model = queue_test_utils.create_queue(priority=120,
                                                    cpus_required=130.0,
                                                    mem_required=600.0,
                                                    disk_in_required=0.0,
                                                    disk_out_required=0.0,
                                                    disk_total_required=0.0)
        job_exe = QueuedJobExecution(queue_model)
        # Expected available 5.9 CPUs and 13 MiB memory "left" on node
        # (available above - new job we are scoring)
        # First 2 job types should fit, next 2 are too big, so score should be 2
        job_type_resource_1 = NodeResources([Cpus(2.0), Mem(10.0)])
        job_type_resource_2 = NodeResources([Cpus(5.5), Mem(12.0)])
        job_type_resource_3 = NodeResources([Cpus(6.0), Mem(10.0)])
        job_type_resource_4 = NodeResources([Cpus(2.0), Mem(14.0)])

        score = scheduling_node.score_job_exe_for_reservation(
            job_exe, [
                job_type_resource_1, job_type_resource_2, job_type_resource_3,
                job_type_resource_4
            ])
        self.assertEqual(score, 2)