import logging
import os
import sys
-import threading
-import hashlib
-import copy
-import json
import re
-from functools import partial
import pkg_resources # part of setuptools
-import Queue
-import time
-import signal
-import thread
-from cwltool.errors import WorkflowException
import cwltool.main
import cwltool.workflow
import cwltool.process
from arvados.errors import ApiError
import arvados.commands._util as arv_cmd
-from .arvcontainer import ArvadosContainer, RunnerContainer
-from .arvjob import ArvadosJob, RunnerJob, RunnerTemplate
-from .runner import Runner, upload_docker, upload_job_order, upload_workflow_deps
-from .arvtool import ArvadosCommandTool
-from .arvworkflow import ArvadosWorkflow, upload_workflow
-from .fsaccess import CollectionFsAccess, CollectionFetcher, collectionResolver, CollectionCache
from .perf import Perf
-from .pathmapper import NoFollowPathMapper
-from .task_queue import TaskQueue
-from .context import ArvLoadingContext, ArvRuntimeContext
-from .util import get_current_container
from ._version import __version__
+from .executor import ArvCwlExecutor
-from cwltool.pack import pack
from cwltool.process import shortname, UnsupportedRequirement, use_custom_schema
from cwltool.pathmapper import adjustFileObjs, adjustDirObjs, get_listing
-from cwltool.command_line_tool import compute_checksums
from arvados.api import OrderedJsonModel
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)
-
-
def versionstring():
"""Print version string of key packages for provenance and debugging."""
help="Docker image for workflow runner job, default arvados/jobs:%s" % __version__,
default=None)
- parser.add_argument("--submit-request-uuid", type=str,
+ exgroup = parser.add_mutually_exclusive_group()
+ exgroup.add_argument("--submit-request-uuid", type=str,
default=None,
- help="Update and commit supplied container request instead of creating a new one (containers API only).")
+ help="Update and commit to supplied container request instead of creating a new one (containers API only).")
+ exgroup.add_argument("--submit-runner-cluster", type=str,
+ help="Submit toplevel runner to a remote cluster (containers API only)",
+ default=None)
parser.add_argument("--name", type=str,
help="Name to use for workflow execution instance.",
add_arv_hints()
+ for key, val in cwltool.argparser.get_default_args().items():
+ if not hasattr(arvargs, key):
+ setattr(arvargs, key, val)
+
try:
if api_client is None:
api_client = arvados.safeapi.ThreadSafeApiCache(
api_client.users().current().execute()
if keep_client is None:
keep_client = arvados.keep.KeepClient(api_client=api_client, num_retries=4)
- runner = ArvCwlRunner(api_client, arvargs, keep_client=keep_client, num_retries=4)
+ executor = ArvCwlExecutor(api_client, arvargs, keep_client=keep_client, num_retries=4)
except Exception as e:
logger.error(e)
return 1
else:
arvados.log_handler.setFormatter(logging.Formatter('%(name)s %(levelname)s: %(message)s'))
- for key, val in cwltool.argparser.get_default_args().items():
- if not hasattr(arvargs, key):
- setattr(arvargs, key, val)
-
- runtimeContext = ArvRuntimeContext(vars(arvargs))
- runtimeContext.make_fs_access = partial(CollectionFsAccess,
- collection_cache=runner.collection_cache)
- runtimeContext.http_timeout = arvargs.http_timeout
-
return cwltool.main.main(args=arvargs,
stdout=stdout,
stderr=stderr,
- executor=runner.arv_executor,
+ executor=executor.arv_executor,
versionfunc=versionstring,
job_order_object=job_order_object,
logger_handler=arvados.log_handler,
custom_schema_callback=add_arv_hints,
- loadingContext=runner.loadingContext,
- runtimeContext=runtimeContext)
+ loadingContext=executor.loadingContext,
+ runtimeContext=executor.runtimeContext)
--- /dev/null
+# Copyright (C) The Arvados Authors. All rights reserved.
+#
+# SPDX-License-Identifier: Apache-2.0
+
+import argparse
+import logging
+import os
+import sys
+import threading
+import copy
+import json
+import re
+from functools import partial
+import time
+
+from cwltool.errors import WorkflowException
+import cwltool.workflow
+from schema_salad.sourceline import SourceLine
+import schema_salad.validate as validate
+
+import arvados
+import arvados.config
+from arvados.keep import KeepClient
+from arvados.errors import ApiError
+
+from .arvcontainer import RunnerContainer
+from .arvjob import RunnerJob, RunnerTemplate
+from .runner import Runner, upload_docker, upload_job_order, upload_workflow_deps
+from .arvtool import ArvadosCommandTool
+from .arvworkflow import ArvadosWorkflow, upload_workflow
+from .fsaccess import CollectionFsAccess, CollectionFetcher, collectionResolver, CollectionCache
+from .perf import Perf
+from .pathmapper import NoFollowPathMapper
+from .task_queue import TaskQueue
+from .context import ArvLoadingContext, ArvRuntimeContext
+from .util import get_current_container
+from ._version import __version__
+
+from cwltool.process import shortname, UnsupportedRequirement, use_custom_schema
+from cwltool.pathmapper import adjustFileObjs, adjustDirObjs, get_listing
+from cwltool.command_line_tool import compute_checksums
+
+logger = logging.getLogger('arvados.cwl-runner')
+
+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 ArvCwlExecutor(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)
+
+ self.runtimeContext = ArvRuntimeContext(vars(arvargs))
+ self.runtimeContext.make_fs_access = partial(CollectionFsAccess,
+ collection_cache=self.collection_cache)
+
+
+ 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)
projects / arvados.git / commitdiff