-DEFAULT_PRIORITY = 500
-
-class RuntimeStatusLoggingHandler(logging.Handler):
- """
- Intercepts logging calls and report them as runtime statuses on runner
- containers.
- """
- def __init__(self, runtime_status_update_func):
- super(RuntimeStatusLoggingHandler, self).__init__()
- self.runtime_status_update = runtime_status_update_func
-
- def emit(self, record):
- kind = None
- if record.levelno >= logging.ERROR:
- kind = 'error'
- elif record.levelno >= logging.WARNING:
- kind = 'warning'
- if kind is not None:
- log_msg = record.getMessage()
- if '\n' in log_msg:
- # If the logged message is multi-line, use its first line as status
- # and the rest as detail.
- status, detail = log_msg.split('\n', 1)
- self.runtime_status_update(
- kind,
- "%s: %s" % (record.name, status),
- detail
- )
- else:
- self.runtime_status_update(
- kind,
- "%s: %s" % (record.name, record.getMessage())
- )
-
-class ArvCwlRunner(object):
- """Execute a CWL tool or workflow, submit work (using either jobs or
- containers API), wait for them to complete, and report output.
-
- """
-
- def __init__(self, api_client,
- arvargs=None,
- keep_client=None,
- num_retries=4,
- thread_count=4):
-
- if arvargs is None:
- arvargs = argparse.Namespace()
- arvargs.work_api = None
- arvargs.output_name = None
- arvargs.output_tags = None
- arvargs.thread_count = 1
-
- self.api = api_client
- self.processes = {}
- self.workflow_eval_lock = threading.Condition(threading.RLock())
- self.final_output = None
- self.final_status = None
- self.num_retries = num_retries
- self.uuid = None
- self.stop_polling = threading.Event()
- self.poll_api = None
- self.pipeline = None
- self.final_output_collection = None
- self.output_name = arvargs.output_name
- self.output_tags = arvargs.output_tags
- self.project_uuid = None
- self.intermediate_output_ttl = 0
- self.intermediate_output_collections = []
- self.trash_intermediate = False
- self.thread_count = arvargs.thread_count
- self.poll_interval = 12
- self.loadingContext = None
-
- if keep_client is not None:
- self.keep_client = keep_client
- else:
- self.keep_client = arvados.keep.KeepClient(api_client=self.api, num_retries=self.num_retries)
-
- self.collection_cache = CollectionCache(self.api, self.keep_client, self.num_retries)
-
- self.fetcher_constructor = partial(CollectionFetcher,
- api_client=self.api,
- fs_access=CollectionFsAccess("", collection_cache=self.collection_cache),
- num_retries=self.num_retries)
-
- self.work_api = None
- expected_api = ["jobs", "containers"]
- for api in expected_api:
- try:
- methods = self.api._rootDesc.get('resources')[api]['methods']
- if ('httpMethod' in methods['create'] and
- (arvargs.work_api == api or arvargs.work_api is None)):
- self.work_api = api
- break
- except KeyError:
- pass
-
- if not self.work_api:
- if arvargs.work_api is None:
- raise Exception("No supported APIs")
- else:
- raise Exception("Unsupported API '%s', expected one of %s" % (arvargs.work_api, expected_api))
-
- if self.work_api == "jobs":
- logger.warn("""
-*******************************
-Using the deprecated 'jobs' API.
-
-To get rid of this warning:
-
-Users: read about migrating at
-http://doc.arvados.org/user/cwl/cwl-style.html#migrate
-and use the option --api=containers
-
-Admins: configure the cluster to disable the 'jobs' API as described at:
-http://doc.arvados.org/install/install-api-server.html#disable_api_methods
-*******************************""")
-
- self.loadingContext = ArvLoadingContext(vars(arvargs))
- self.loadingContext.fetcher_constructor = self.fetcher_constructor
- self.loadingContext.resolver = partial(collectionResolver, self.api, num_retries=self.num_retries)
- self.loadingContext.construct_tool_object = self.arv_make_tool
-
- # Add a custom logging handler to the root logger for runtime status reporting
- # if running inside a container
- if get_current_container(self.api, self.num_retries, logger):
- root_logger = logging.getLogger('')
- handler = RuntimeStatusLoggingHandler(self.runtime_status_update)
- root_logger.addHandler(handler)
-
- def arv_make_tool(self, toolpath_object, loadingContext):
- if "class" in toolpath_object and toolpath_object["class"] == "CommandLineTool":
- return ArvadosCommandTool(self, toolpath_object, loadingContext)
- elif "class" in toolpath_object and toolpath_object["class"] == "Workflow":
- return ArvadosWorkflow(self, toolpath_object, loadingContext)
- else:
- return cwltool.workflow.default_make_tool(toolpath_object, loadingContext)
-
- def output_callback(self, out, processStatus):
- with self.workflow_eval_lock:
- if processStatus == "success":
- logger.info("Overall process status is %s", processStatus)
- state = "Complete"
- else:
- logger.error("Overall process status is %s", processStatus)
- state = "Failed"
- if self.pipeline:
- self.api.pipeline_instances().update(uuid=self.pipeline["uuid"],
- body={"state": state}).execute(num_retries=self.num_retries)
- self.final_status = processStatus
- self.final_output = out
- self.workflow_eval_lock.notifyAll()
-
-
- def start_run(self, runnable, runtimeContext):
- self.task_queue.add(partial(runnable.run, runtimeContext))
-
- def process_submitted(self, container):
- with self.workflow_eval_lock:
- self.processes[container.uuid] = container
-
- def process_done(self, uuid, record):
- with self.workflow_eval_lock:
- j = self.processes[uuid]
- logger.info("%s %s is %s", self.label(j), uuid, record["state"])
- self.task_queue.add(partial(j.done, record))
- del self.processes[uuid]
-
- def runtime_status_update(self, kind, message, detail=None):
- """
- Updates the runtime_status field on the runner container.
- Called when there's a need to report errors, warnings or just
- activity statuses, for example in the RuntimeStatusLoggingHandler.
- """
- with self.workflow_eval_lock:
- current = get_current_container(self.api, self.num_retries, logger)
- if current is None:
- return
- runtime_status = current.get('runtime_status', {})
- # In case of status being an error, only report the first one.
- if kind == 'error':
- if not runtime_status.get('error'):
- runtime_status.update({
- 'error': message
- })
- if detail is not None:
- runtime_status.update({
- 'errorDetail': detail
- })
- # Further errors are only mentioned as a count.
- else:
- # Get anything before an optional 'and N more' string.
- try:
- error_msg = re.match(
- r'^(.*?)(?=\s*\(and \d+ more\)|$)', runtime_status.get('error')).groups()[0]
- more_failures = re.match(
- r'.*\(and (\d+) more\)', runtime_status.get('error'))
- except TypeError:
- # Ignore tests stubbing errors
- return
- if more_failures:
- failure_qty = int(more_failures.groups()[0])
- runtime_status.update({
- 'error': "%s (and %d more)" % (error_msg, failure_qty+1)
- })
- else:
- runtime_status.update({
- 'error': "%s (and 1 more)" % error_msg
- })
- elif kind in ['warning', 'activity']:
- # Record the last warning/activity status without regard of
- # previous occurences.
- runtime_status.update({
- kind: message
- })
- if detail is not None:
- runtime_status.update({
- kind+"Detail": detail
- })
- else:
- # Ignore any other status kind
- return
- try:
- self.api.containers().update(uuid=current['uuid'],
- body={
- 'runtime_status': runtime_status,
- }).execute(num_retries=self.num_retries)
- except Exception as e:
- logger.info("Couldn't update runtime_status: %s", e)
-
- def wrapped_callback(self, cb, obj, st):
- with self.workflow_eval_lock:
- cb(obj, st)
- self.workflow_eval_lock.notifyAll()
-
- def get_wrapped_callback(self, cb):
- return partial(self.wrapped_callback, cb)
-
- def on_message(self, event):
- if event.get("object_uuid") in self.processes and event["event_type"] == "update":
- uuid = event["object_uuid"]
- if event["properties"]["new_attributes"]["state"] == "Running":
- with self.workflow_eval_lock:
- j = self.processes[uuid]
- if j.running is False:
- j.running = True
- j.update_pipeline_component(event["properties"]["new_attributes"])
- logger.info("%s %s is Running", self.label(j), uuid)
- elif event["properties"]["new_attributes"]["state"] in ("Complete", "Failed", "Cancelled", "Final"):
- self.process_done(uuid, event["properties"]["new_attributes"])
-
- def label(self, obj):
- return "[%s %s]" % (self.work_api[0:-1], obj.name)
-
- def poll_states(self):
- """Poll status of jobs or containers listed in the processes dict.
-
- Runs in a separate thread.
- """
-
- try:
- remain_wait = self.poll_interval
- while True:
- if remain_wait > 0:
- self.stop_polling.wait(remain_wait)
- if self.stop_polling.is_set():
- break
- with self.workflow_eval_lock:
- keys = list(self.processes.keys())
- if not keys:
- remain_wait = self.poll_interval
- continue
-
- begin_poll = time.time()
- if self.work_api == "containers":
- table = self.poll_api.container_requests()
- elif self.work_api == "jobs":
- table = self.poll_api.jobs()
-
- try:
- proc_states = table.list(filters=[["uuid", "in", keys]]).execute(num_retries=self.num_retries)
- except Exception as e:
- logger.warn("Error checking states on API server: %s", e)
- remain_wait = self.poll_interval
- continue
-
- for p in proc_states["items"]:
- self.on_message({
- "object_uuid": p["uuid"],
- "event_type": "update",
- "properties": {
- "new_attributes": p
- }
- })
- finish_poll = time.time()
- remain_wait = self.poll_interval - (finish_poll - begin_poll)
- except:
- logger.exception("Fatal error in state polling thread.")
- with self.workflow_eval_lock:
- self.processes.clear()
- self.workflow_eval_lock.notifyAll()
- finally:
- self.stop_polling.set()
-
- def add_intermediate_output(self, uuid):
- if uuid:
- self.intermediate_output_collections.append(uuid)
-
- def trash_intermediate_output(self):
- logger.info("Cleaning up intermediate output collections")
- for i in self.intermediate_output_collections:
- try:
- self.api.collections().delete(uuid=i).execute(num_retries=self.num_retries)
- except:
- logger.warn("Failed to delete intermediate output: %s", sys.exc_info()[1], exc_info=(sys.exc_info()[1] if self.debug else False))
- if sys.exc_info()[0] is KeyboardInterrupt or sys.exc_info()[0] is SystemExit:
- break
-
- def check_features(self, obj):
- if isinstance(obj, dict):
- if obj.get("writable") and self.work_api != "containers":
- raise SourceLine(obj, "writable", UnsupportedRequirement).makeError("InitialWorkDir feature 'writable: true' not supported with --api=jobs")
- if obj.get("class") == "DockerRequirement":
- if obj.get("dockerOutputDirectory"):
- if self.work_api != "containers":
- raise SourceLine(obj, "dockerOutputDirectory", UnsupportedRequirement).makeError(
- "Option 'dockerOutputDirectory' of DockerRequirement not supported with --api=jobs.")
- if not obj.get("dockerOutputDirectory").startswith('/'):
- raise SourceLine(obj, "dockerOutputDirectory", validate.ValidationException).makeError(
- "Option 'dockerOutputDirectory' must be an absolute path.")
- if obj.get("class") == "http://commonwl.org/cwltool#Secrets" and self.work_api != "containers":
- raise SourceLine(obj, "class", UnsupportedRequirement).makeError("Secrets not supported with --api=jobs")
- for v in obj.itervalues():
- self.check_features(v)
- elif isinstance(obj, list):
- for i,v in enumerate(obj):
- with SourceLine(obj, i, UnsupportedRequirement, logger.isEnabledFor(logging.DEBUG)):
- self.check_features(v)
-
- def make_output_collection(self, name, storage_classes, tagsString, outputObj):
- outputObj = copy.deepcopy(outputObj)
-
- files = []
- def capture(fileobj):
- files.append(fileobj)
-
- adjustDirObjs(outputObj, capture)
- adjustFileObjs(outputObj, capture)
-
- generatemapper = NoFollowPathMapper(files, "", "", separateDirs=False)
-
- final = arvados.collection.Collection(api_client=self.api,
- keep_client=self.keep_client,
- num_retries=self.num_retries)
-
- for k,v in generatemapper.items():
- if k.startswith("_:"):
- if v.type == "Directory":
- continue
- if v.type == "CreateFile":
- with final.open(v.target, "wb") as f:
- f.write(v.resolved.encode("utf-8"))
- continue
-
- if not k.startswith("keep:"):
- raise Exception("Output source is not in keep or a literal")
- sp = k.split("/")
- srccollection = sp[0][5:]
- try:
- reader = self.collection_cache.get(srccollection)
- srcpath = "/".join(sp[1:]) if len(sp) > 1 else "."
- final.copy(srcpath, v.target, source_collection=reader, overwrite=False)
- except arvados.errors.ArgumentError as e:
- logger.error("Creating CollectionReader for '%s' '%s': %s", k, v, e)
- raise
- except IOError as e:
- logger.warn("While preparing output collection: %s", e)
-
- def rewrite(fileobj):
- fileobj["location"] = generatemapper.mapper(fileobj["location"]).target
- for k in ("listing", "contents", "nameext", "nameroot", "dirname"):
- if k in fileobj:
- del fileobj[k]
-
- adjustDirObjs(outputObj, rewrite)
- adjustFileObjs(outputObj, rewrite)
-
- with final.open("cwl.output.json", "w") as f:
- json.dump(outputObj, f, sort_keys=True, indent=4, separators=(',',': '))
-
- final.save_new(name=name, owner_uuid=self.project_uuid, storage_classes=storage_classes, ensure_unique_name=True)
-
- logger.info("Final output collection %s \"%s\" (%s)", final.portable_data_hash(),
- final.api_response()["name"],
- final.manifest_locator())
-
- final_uuid = final.manifest_locator()
- tags = tagsString.split(',')
- for tag in tags:
- self.api.links().create(body={
- "head_uuid": final_uuid, "link_class": "tag", "name": tag
- }).execute(num_retries=self.num_retries)
-
- def finalcollection(fileobj):
- fileobj["location"] = "keep:%s/%s" % (final.portable_data_hash(), fileobj["location"])
-
- adjustDirObjs(outputObj, finalcollection)
- adjustFileObjs(outputObj, finalcollection)
-
- return (outputObj, final)
-
- def set_crunch_output(self):
- if self.work_api == "containers":
- current = get_current_container(self.api, self.num_retries, logger)
- if current is None:
- return
- try:
- self.api.containers().update(uuid=current['uuid'],
- body={
- 'output': self.final_output_collection.portable_data_hash(),
- }).execute(num_retries=self.num_retries)
- self.api.collections().update(uuid=self.final_output_collection.manifest_locator(),
- body={
- 'is_trashed': True
- }).execute(num_retries=self.num_retries)
- except Exception as e:
- logger.info("Setting container output: %s", e)
- elif self.work_api == "jobs" and "TASK_UUID" in os.environ:
- self.api.job_tasks().update(uuid=os.environ["TASK_UUID"],
- body={
- 'output': self.final_output_collection.portable_data_hash(),
- 'success': self.final_status == "success",
- 'progress':1.0
- }).execute(num_retries=self.num_retries)
-
- def arv_executor(self, tool, job_order, runtimeContext, logger=None):
- self.debug = runtimeContext.debug
-
- tool.visit(self.check_features)
-
- self.project_uuid = runtimeContext.project_uuid
- self.pipeline = None
- self.fs_access = runtimeContext.make_fs_access(runtimeContext.basedir)
- self.secret_store = runtimeContext.secret_store
-
- self.trash_intermediate = runtimeContext.trash_intermediate
- if self.trash_intermediate and self.work_api != "containers":
- raise Exception("--trash-intermediate is only supported with --api=containers.")
-
- self.intermediate_output_ttl = runtimeContext.intermediate_output_ttl
- if self.intermediate_output_ttl and self.work_api != "containers":
- raise Exception("--intermediate-output-ttl is only supported with --api=containers.")
- if self.intermediate_output_ttl < 0:
- raise Exception("Invalid value %d for --intermediate-output-ttl, cannot be less than zero" % self.intermediate_output_ttl)
-
- if runtimeContext.submit_request_uuid and self.work_api != "containers":
- raise Exception("--submit-request-uuid requires containers API, but using '{}' api".format(self.work_api))
-
- if not runtimeContext.name:
- runtimeContext.name = self.name = tool.tool.get("label") or tool.metadata.get("label") or os.path.basename(tool.tool["id"])
-
- # Upload direct dependencies of workflow steps, get back mapping of files to keep references.
- # Also uploads docker images.
- merged_map = upload_workflow_deps(self, tool)
-
- # Reload tool object which may have been updated by
- # upload_workflow_deps
- # Don't validate this time because it will just print redundant errors.
- loadingContext = self.loadingContext.copy()
- loadingContext.loader = tool.doc_loader
- loadingContext.avsc_names = tool.doc_schema
- loadingContext.metadata = tool.metadata
- loadingContext.do_validate = False
-
- tool = self.arv_make_tool(tool.doc_loader.idx[tool.tool["id"]],
- loadingContext)
-
- # Upload local file references in the job order.
- job_order = upload_job_order(self, "%s input" % runtimeContext.name,
- tool, job_order)
-
- existing_uuid = runtimeContext.update_workflow
- if existing_uuid or runtimeContext.create_workflow:
- # Create a pipeline template or workflow record and exit.
- if self.work_api == "jobs":
- tmpl = RunnerTemplate(self, tool, job_order,
- runtimeContext.enable_reuse,
- uuid=existing_uuid,
- submit_runner_ram=runtimeContext.submit_runner_ram,
- name=runtimeContext.name,
- merged_map=merged_map)
- tmpl.save()
- # cwltool.main will write our return value to stdout.
- return (tmpl.uuid, "success")
- elif self.work_api == "containers":
- return (upload_workflow(self, tool, job_order,
- self.project_uuid,
- uuid=existing_uuid,
- submit_runner_ram=runtimeContext.submit_runner_ram,
- name=runtimeContext.name,
- merged_map=merged_map),
- "success")
-
- self.ignore_docker_for_reuse = runtimeContext.ignore_docker_for_reuse
- self.eval_timeout = runtimeContext.eval_timeout
-
- runtimeContext = runtimeContext.copy()
- runtimeContext.use_container = True
- runtimeContext.tmpdir_prefix = "tmp"
- runtimeContext.work_api = self.work_api
-
- if self.work_api == "containers":
- if self.ignore_docker_for_reuse:
- raise Exception("--ignore-docker-for-reuse not supported with containers API.")
- runtimeContext.outdir = "/var/spool/cwl"
- runtimeContext.docker_outdir = "/var/spool/cwl"
- runtimeContext.tmpdir = "/tmp"
- runtimeContext.docker_tmpdir = "/tmp"
- elif self.work_api == "jobs":
- if runtimeContext.priority != DEFAULT_PRIORITY:
- raise Exception("--priority not implemented for jobs API.")
- runtimeContext.outdir = "$(task.outdir)"
- runtimeContext.docker_outdir = "$(task.outdir)"
- runtimeContext.tmpdir = "$(task.tmpdir)"
-
- if runtimeContext.priority < 1 or runtimeContext.priority > 1000:
- raise Exception("--priority must be in the range 1..1000.")
-
- runnerjob = None
- if runtimeContext.submit:
- # Submit a runner job to run the workflow for us.
- if self.work_api == "containers":
- if tool.tool["class"] == "CommandLineTool" and runtimeContext.wait:
- runtimeContext.runnerjob = tool.tool["id"]
- runnerjob = tool.job(job_order,
- self.output_callback,
- runtimeContext).next()
- else:
- runnerjob = RunnerContainer(self, tool, job_order, runtimeContext.enable_reuse,
- self.output_name,
- self.output_tags,
- submit_runner_ram=runtimeContext.submit_runner_ram,
- name=runtimeContext.name,
- on_error=runtimeContext.on_error,
- submit_runner_image=runtimeContext.submit_runner_image,
- intermediate_output_ttl=runtimeContext.intermediate_output_ttl,
- merged_map=merged_map,
- priority=runtimeContext.priority,
- secret_store=self.secret_store)
- elif self.work_api == "jobs":
- runnerjob = RunnerJob(self, tool, job_order, runtimeContext.enable_reuse,
- self.output_name,
- self.output_tags,
- submit_runner_ram=runtimeContext.submit_runner_ram,
- name=runtimeContext.name,
- on_error=runtimeContext.on_error,
- submit_runner_image=runtimeContext.submit_runner_image,
- merged_map=merged_map)
- elif runtimeContext.cwl_runner_job is None and self.work_api == "jobs":
- # Create pipeline for local run
- self.pipeline = self.api.pipeline_instances().create(
- body={
- "owner_uuid": self.project_uuid,
- "name": runtimeContext.name if runtimeContext.name else shortname(tool.tool["id"]),
- "components": {},
- "state": "RunningOnClient"}).execute(num_retries=self.num_retries)
- logger.info("Pipeline instance %s", self.pipeline["uuid"])
-
- if runnerjob and not runtimeContext.wait:
- submitargs = runtimeContext.copy()
- submitargs.submit = False
- runnerjob.run(submitargs)
- return (runnerjob.uuid, "success")
-
- self.poll_api = arvados.api('v1', timeout=runtimeContext.http_timeout)
- self.polling_thread = threading.Thread(target=self.poll_states)
- self.polling_thread.start()
-
- self.task_queue = TaskQueue(self.workflow_eval_lock, self.thread_count)
-
- if runnerjob:
- jobiter = iter((runnerjob,))
- else:
- if runtimeContext.cwl_runner_job is not None:
- self.uuid = runtimeContext.cwl_runner_job.get('uuid')
- jobiter = tool.job(job_order,
- self.output_callback,
- runtimeContext)
-
- try:
- self.workflow_eval_lock.acquire()
- # Holds the lock while this code runs and releases it when
- # it is safe to do so in self.workflow_eval_lock.wait(),
- # at which point on_message can update job state and
- # process output callbacks.
-
- loopperf = Perf(metrics, "jobiter")
- loopperf.__enter__()
- for runnable in jobiter:
- loopperf.__exit__()
-
- if self.stop_polling.is_set():
- break
-
- if self.task_queue.error is not None:
- raise self.task_queue.error
-
- if runnable:
- with Perf(metrics, "run"):
- self.start_run(runnable, runtimeContext)
- else:
- if (self.task_queue.in_flight + len(self.processes)) > 0:
- self.workflow_eval_lock.wait(3)
- else:
- logger.error("Workflow is deadlocked, no runnable processes and not waiting on any pending processes.")
- break
- loopperf.__enter__()
- loopperf.__exit__()
-
- while (self.task_queue.in_flight + len(self.processes)) > 0:
- if self.task_queue.error is not None:
- raise self.task_queue.error
- self.workflow_eval_lock.wait(3)
-
- except UnsupportedRequirement:
- raise
- except:
- if sys.exc_info()[0] is KeyboardInterrupt or sys.exc_info()[0] is SystemExit:
- logger.error("Interrupted, workflow will be cancelled")
- else:
- logger.error("Execution failed: %s", sys.exc_info()[1], exc_info=(sys.exc_info()[1] if self.debug else False))
- if self.pipeline:
- self.api.pipeline_instances().update(uuid=self.pipeline["uuid"],
- body={"state": "Failed"}).execute(num_retries=self.num_retries)
- if runnerjob and runnerjob.uuid and self.work_api == "containers":
- self.api.container_requests().update(uuid=runnerjob.uuid,
- body={"priority": "0"}).execute(num_retries=self.num_retries)
- finally:
- self.workflow_eval_lock.release()
- self.task_queue.drain()
- self.stop_polling.set()
- self.polling_thread.join()
- self.task_queue.join()
-
- if self.final_status == "UnsupportedRequirement":
- raise UnsupportedRequirement("Check log for details.")
-
- if self.final_output is None:
- raise WorkflowException("Workflow did not return a result.")
-
- if runtimeContext.submit and isinstance(runnerjob, Runner):
- logger.info("Final output collection %s", runnerjob.final_output)
- else:
- if self.output_name is None:
- self.output_name = "Output of %s" % (shortname(tool.tool["id"]))
- if self.output_tags is None:
- self.output_tags = ""
-
- storage_classes = runtimeContext.storage_classes.strip().split(",")
- self.final_output, self.final_output_collection = self.make_output_collection(self.output_name, storage_classes, self.output_tags, self.final_output)
- self.set_crunch_output()
-
- if runtimeContext.compute_checksum:
- adjustDirObjs(self.final_output, partial(get_listing, self.fs_access))
- adjustFileObjs(self.final_output, partial(compute_checksums, self.fs_access))
-
- if self.trash_intermediate and self.final_status == "success":
- self.trash_intermediate_output()
-
- return (self.final_output, self.final_status)
-
-