sdk/cwl/arvados_cwl/executor.py

   1 # Copyright (C) The Arvados Authors. All rights reserved.
   2 #
   3 # SPDX-License-Identifier: Apache-2.0
   4
   5 from __future__ import division
   6 from builtins import next
   7 from builtins import object
   8 from builtins import str
   9 from future.utils import viewvalues, viewitems
  10
  11 import argparse
  12 import logging
  13 import os
  14 import sys
  15 import threading
  16 import copy
  17 import json
  18 import re
  19 from functools import partial
  20 import time
  21 import urllib
  22
  23 from cwltool.errors import WorkflowException
  24 import cwltool.workflow
  25 from schema_salad.sourceline import SourceLine
  26 import schema_salad.validate as validate
  27
  28 import arvados
  29 import arvados.config
  30 from arvados.keep import KeepClient
  31 from arvados.errors import ApiError
  32
  33 import arvados_cwl.util
  34 from .arvcontainer import RunnerContainer
  35 from .runner import Runner, upload_docker, upload_job_order, upload_workflow_deps
  36 from .arvtool import ArvadosCommandTool, validate_cluster_target, ArvadosExpressionTool
  37 from .arvworkflow import ArvadosWorkflow, upload_workflow
  38 from .fsaccess import CollectionFsAccess, CollectionFetcher, collectionResolver, CollectionCache, pdh_size
  39 from .perf import Perf
  40 from .pathmapper import NoFollowPathMapper
  41 from cwltool.task_queue import TaskQueue
  42 from .context import ArvLoadingContext, ArvRuntimeContext
  43 from ._version import __version__
  44
  45 from cwltool.process import shortname, UnsupportedRequirement, use_custom_schema
  46 from cwltool.utils import adjustFileObjs, adjustDirObjs, get_listing, visit_class, aslist
  47 from cwltool.command_line_tool import compute_checksums
  48 from cwltool.load_tool import load_tool
  49
  50 logger = logging.getLogger('arvados.cwl-runner')
  51 metrics = logging.getLogger('arvados.cwl-runner.metrics')
  52
  53 DEFAULT_PRIORITY = 500
  54
  55 class RuntimeStatusLoggingHandler(logging.Handler):
  56     """
  57     Intercepts logging calls and report them as runtime statuses on runner
  58     containers.
  59     """
  60     def __init__(self, runtime_status_update_func):
  61         super(RuntimeStatusLoggingHandler, self).__init__()
  62         self.runtime_status_update = runtime_status_update_func
  63         self.updatingRuntimeStatus = False
  64
  65     def emit(self, record):
  66         kind = None
  67         if record.levelno >= logging.ERROR:
  68             kind = 'error'
  69         elif record.levelno >= logging.WARNING:
  70             kind = 'warning'
  71         if kind is not None and self.updatingRuntimeStatus is not True:
  72             self.updatingRuntimeStatus = True
  73             try:
  74                 log_msg = record.getMessage()
  75                 if '\n' in log_msg:
  76                     # If the logged message is multi-line, use its first line as status
  77                     # and the rest as detail.
  78                     status, detail = log_msg.split('\n', 1)
  79                     self.runtime_status_update(
  80                         kind,
  81                         "%s: %s" % (record.name, status),
  82                         detail
  83                     )
  84                 else:
  85                     self.runtime_status_update(
  86                         kind,
  87                         "%s: %s" % (record.name, record.getMessage())
  88                     )
  89             finally:
  90                 self.updatingRuntimeStatus = False
  91
  92
  93 class ArvCwlExecutor(object):
  94     """Execute a CWL tool or workflow, submit work (using containers API),
  95     wait for them to complete, and report output.
  96
  97     """
  98
  99     def __init__(self, api_client,
 100                  arvargs=None,
 101                  keep_client=None,
 102                  num_retries=4,
 103                  thread_count=4,
 104                  stdout=sys.stdout):
 105
 106         if arvargs is None:
 107             arvargs = argparse.Namespace()
 108             arvargs.work_api = None
 109             arvargs.output_name = None
 110             arvargs.output_tags = None
 111             arvargs.thread_count = 1
 112             arvargs.collection_cache_size = None
 113
 114         self.api = api_client
 115         self.processes = {}
 116         self.workflow_eval_lock = threading.Condition(threading.RLock())
 117         self.final_output = None
 118         self.final_status = None
 119         self.num_retries = num_retries
 120         self.uuid = None
 121         self.stop_polling = threading.Event()
 122         self.poll_api = None
 123         self.pipeline = None
 124         self.final_output_collection = None
 125         self.output_name = arvargs.output_name
 126         self.output_tags = arvargs.output_tags
 127         self.project_uuid = None
 128         self.intermediate_output_ttl = 0
 129         self.intermediate_output_collections = []
 130         self.trash_intermediate = False
 131         self.thread_count = arvargs.thread_count
 132         self.poll_interval = 12
 133         self.loadingContext = None
 134         self.should_estimate_cache_size = True
 135         self.fs_access = None
 136         self.secret_store = None
 137         self.stdout = stdout
 138
 139         if keep_client is not None:
 140             self.keep_client = keep_client
 141         else:
 142             self.keep_client = arvados.keep.KeepClient(api_client=self.api, num_retries=self.num_retries)
 143
 144         if arvargs.collection_cache_size:
 145             collection_cache_size = arvargs.collection_cache_size*1024*1024
 146             self.should_estimate_cache_size = False
 147         else:
 148             collection_cache_size = 256*1024*1024
 149
 150         self.collection_cache = CollectionCache(self.api, self.keep_client, self.num_retries,
 151                                                 cap=collection_cache_size)
 152
 153         self.fetcher_constructor = partial(CollectionFetcher,
 154                                            api_client=self.api,
 155                                            fs_access=CollectionFsAccess("", collection_cache=self.collection_cache),
 156                                            num_retries=self.num_retries)
 157
 158         self.work_api = None
 159         expected_api = ["containers"]
 160         for api in expected_api:
 161             try:
 162                 methods = self.api._rootDesc.get('resources')[api]['methods']
 163                 if ('httpMethod' in methods['create'] and
 164                     (arvargs.work_api == api or arvargs.work_api is None)):
 165                     self.work_api = api
 166                     break
 167             except KeyError:
 168                 pass
 169
 170         if not self.work_api:
 171             if arvargs.work_api is None:
 172                 raise Exception("No supported APIs")
 173             else:
 174                 raise Exception("Unsupported API '%s', expected one of %s" % (arvargs.work_api, expected_api))
 175
 176         if self.work_api == "jobs":
 177             logger.error("""
 178 *******************************
 179 The 'jobs' API is no longer supported.
 180 *******************************""")
 181             exit(1)
 182
 183         self.loadingContext = ArvLoadingContext(vars(arvargs))
 184         self.loadingContext.fetcher_constructor = self.fetcher_constructor
 185         self.loadingContext.resolver = partial(collectionResolver, self.api, num_retries=self.num_retries)
 186         self.loadingContext.construct_tool_object = self.arv_make_tool
 187
 188         # Add a custom logging handler to the root logger for runtime status reporting
 189         # if running inside a container
 190         if arvados_cwl.util.get_current_container(self.api, self.num_retries, logger):
 191             root_logger = logging.getLogger('')
 192
 193             # Remove existing RuntimeStatusLoggingHandlers if they exist
 194             handlers = [h for h in root_logger.handlers if not isinstance(h, RuntimeStatusLoggingHandler)]
 195             root_logger.handlers = handlers
 196
 197             handler = RuntimeStatusLoggingHandler(self.runtime_status_update)
 198             root_logger.addHandler(handler)
 199
 200         self.toplevel_runtimeContext = ArvRuntimeContext(vars(arvargs))
 201         self.toplevel_runtimeContext.make_fs_access = partial(CollectionFsAccess,
 202                                                      collection_cache=self.collection_cache)
 203
 204         validate_cluster_target(self, self.toplevel_runtimeContext)
 205
 206
 207     def arv_make_tool(self, toolpath_object, loadingContext):
 208         if "class" in toolpath_object and toolpath_object["class"] == "CommandLineTool":
 209             return ArvadosCommandTool(self, toolpath_object, loadingContext)
 210         elif "class" in toolpath_object and toolpath_object["class"] == "Workflow":
 211             return ArvadosWorkflow(self, toolpath_object, loadingContext)
 212         elif "class" in toolpath_object and toolpath_object["class"] == "ExpressionTool":
 213             return ArvadosExpressionTool(self, toolpath_object, loadingContext)
 214         else:
 215             raise Exception("Unknown tool %s" % toolpath_object.get("class"))
 216
 217     def output_callback(self, out, processStatus):
 218         with self.workflow_eval_lock:
 219             if processStatus == "success":
 220                 logger.info("Overall process status is %s", processStatus)
 221                 state = "Complete"
 222             else:
 223                 logger.error("Overall process status is %s", processStatus)
 224                 state = "Failed"
 225             if self.pipeline:
 226                 self.api.pipeline_instances().update(uuid=self.pipeline["uuid"],
 227                                                         body={"state": state}).execute(num_retries=self.num_retries)
 228             self.final_status = processStatus
 229             self.final_output = out
 230             self.workflow_eval_lock.notifyAll()
 231
 232
 233     def start_run(self, runnable, runtimeContext):
 234         self.task_queue.add(partial(runnable.run, runtimeContext),
 235                             self.workflow_eval_lock, self.stop_polling)
 236
 237     def process_submitted(self, container):
 238         with self.workflow_eval_lock:
 239             self.processes[container.uuid] = container
 240
 241     def process_done(self, uuid, record):
 242         with self.workflow_eval_lock:
 243             j = self.processes[uuid]
 244             logger.info("%s %s is %s", self.label(j), uuid, record["state"])
 245             self.task_queue.add(partial(j.done, record),
 246                                 self.workflow_eval_lock, self.stop_polling)
 247             del self.processes[uuid]
 248
 249     def runtime_status_update(self, kind, message, detail=None):
 250         """
 251         Updates the runtime_status field on the runner container.
 252         Called when there's a need to report errors, warnings or just
 253         activity statuses, for example in the RuntimeStatusLoggingHandler.
 254         """
 255         with self.workflow_eval_lock:
 256             current = None
 257             try:
 258                 current = arvados_cwl.util.get_current_container(self.api, self.num_retries, logger)
 259             except Exception as e:
 260                 logger.info("Couldn't get current container: %s", e)
 261             if current is None:
 262                 return
 263             runtime_status = current.get('runtime_status', {})
 264             if kind in ('error', 'warning'):
 265                 updatemessage = runtime_status.get(kind, "")
 266                 if not updatemessage:
 267                     updatemessage = message
 268
 269                 # Subsequent messages tacked on in detail
 270                 updatedetail = runtime_status.get(kind+'Detail', "")
 271                 maxlines = 40
 272                 if updatedetail.count("\n") < maxlines:
 273                     if updatedetail:
 274                         updatedetail += "\n"
 275                     updatedetail += message + "\n"
 276
 277                     if detail:
 278                         updatedetail += detail + "\n"
 279
 280                     if updatedetail.count("\n") >= maxlines:
 281                         updatedetail += "\nSome messages may have been omitted.  Check the full log."
 282
 283                 runtime_status.update({
 284                     kind: updatemessage,
 285                     kind+'Detail': updatedetail,
 286                 })
 287             else:
 288                 # Ignore any other status kind
 289                 return
 290             try:
 291                 self.api.containers().update(uuid=current['uuid'],
 292                                             body={
 293                                                 'runtime_status': runtime_status,
 294                                             }).execute(num_retries=self.num_retries)
 295             except Exception as e:
 296                 logger.info("Couldn't update runtime_status: %s", e)
 297
 298     def wrapped_callback(self, cb, obj, st):
 299         with self.workflow_eval_lock:
 300             cb(obj, st)
 301             self.workflow_eval_lock.notifyAll()
 302
 303     def get_wrapped_callback(self, cb):
 304         return partial(self.wrapped_callback, cb)
 305
 306     def on_message(self, event):
 307         if event.get("object_uuid") in self.processes and event["event_type"] == "update":
 308             uuid = event["object_uuid"]
 309             if event["properties"]["new_attributes"]["state"] == "Running":
 310                 with self.workflow_eval_lock:
 311                     j = self.processes[uuid]
 312                     if j.running is False:
 313                         j.running = True
 314                         j.update_pipeline_component(event["properties"]["new_attributes"])
 315                         logger.info("%s %s is Running", self.label(j), uuid)
 316             elif event["properties"]["new_attributes"]["state"] in ("Complete", "Failed", "Cancelled", "Final"):
 317                 self.process_done(uuid, event["properties"]["new_attributes"])
 318
 319     def label(self, obj):
 320         return "[%s %s]" % (self.work_api[0:-1], obj.name)
 321
 322     def poll_states(self):
 323         """Poll status of containers listed in the processes dict.
 324
 325         Runs in a separate thread.
 326         """
 327
 328         try:
 329             remain_wait = self.poll_interval
 330             while True:
 331                 if remain_wait > 0:
 332                     self.stop_polling.wait(remain_wait)
 333                 if self.stop_polling.is_set():
 334                     break
 335                 with self.workflow_eval_lock:
 336                     keys = list(self.processes)
 337                 if not keys:
 338                     remain_wait = self.poll_interval
 339                     continue
 340
 341                 begin_poll = time.time()
 342                 if self.work_api == "containers":
 343                     table = self.poll_api.container_requests()
 344
 345                 pageSize = self.poll_api._rootDesc.get('maxItemsPerResponse', 1000)
 346
 347                 while keys:
 348                     page = keys[:pageSize]
 349                     try:
 350                         proc_states = table.list(filters=[["uuid", "in", page]]).execute(num_retries=self.num_retries)
 351                     except Exception:
 352                         logger.exception("Error checking states on API server: %s")
 353                         remain_wait = self.poll_interval
 354                         continue
 355
 356                     for p in proc_states["items"]:
 357                         self.on_message({
 358                             "object_uuid": p["uuid"],
 359                             "event_type": "update",
 360                             "properties": {
 361                                 "new_attributes": p
 362                             }
 363                         })
 364                     keys = keys[pageSize:]
 365
 366                 finish_poll = time.time()
 367                 remain_wait = self.poll_interval - (finish_poll - begin_poll)
 368         except:
 369             logger.exception("Fatal error in state polling thread.")
 370             with self.workflow_eval_lock:
 371                 self.processes.clear()
 372                 self.workflow_eval_lock.notifyAll()
 373         finally:
 374             self.stop_polling.set()
 375
 376     def add_intermediate_output(self, uuid):
 377         if uuid:
 378             self.intermediate_output_collections.append(uuid)
 379
 380     def trash_intermediate_output(self):
 381         logger.info("Cleaning up intermediate output collections")
 382         for i in self.intermediate_output_collections:
 383             try:
 384                 self.api.collections().delete(uuid=i).execute(num_retries=self.num_retries)
 385             except Exception:
 386                 logger.warning("Failed to delete intermediate output: %s", sys.exc_info()[1], exc_info=(sys.exc_info()[1] if self.debug else False))
 387             except (KeyboardInterrupt, SystemExit):
 388                 break
 389
 390     def check_features(self, obj, parentfield=""):
 391         if isinstance(obj, dict):
 392             if obj.get("class") == "DockerRequirement":
 393                 if obj.get("dockerOutputDirectory"):
 394                     if not obj.get("dockerOutputDirectory").startswith('/'):
 395                         raise SourceLine(obj, "dockerOutputDirectory", validate.ValidationException).makeError(
 396                             "Option 'dockerOutputDirectory' must be an absolute path.")
 397             if obj.get("class") == "InplaceUpdateRequirement":
 398                 if obj["inplaceUpdate"] and parentfield == "requirements":
 399                     raise SourceLine(obj, "class", UnsupportedRequirement).makeError("InplaceUpdateRequirement not supported for keep collections.")
 400             for k,v in viewitems(obj):
 401                 self.check_features(v, parentfield=k)
 402         elif isinstance(obj, list):
 403             for i,v in enumerate(obj):
 404                 with SourceLine(obj, i, UnsupportedRequirement, logger.isEnabledFor(logging.DEBUG)):
 405                     self.check_features(v, parentfield=parentfield)
 406
 407     def make_output_collection(self, name, storage_classes, tagsString, outputObj):
 408         outputObj = copy.deepcopy(outputObj)
 409
 410         files = []
 411         def capture(fileobj):
 412             files.append(fileobj)
 413
 414         adjustDirObjs(outputObj, capture)
 415         adjustFileObjs(outputObj, capture)
 416
 417         generatemapper = NoFollowPathMapper(files, "", "", separateDirs=False)
 418
 419         final = arvados.collection.Collection(api_client=self.api,
 420                                               keep_client=self.keep_client,
 421                                               num_retries=self.num_retries)
 422
 423         for k,v in generatemapper.items():
 424             if v.type == "Directory" and v.resolved.startswith("_:"):
 425                     continue
 426             if v.type == "CreateFile" and (k.startswith("_:") or v.resolved.startswith("_:")):
 427                 with final.open(v.target, "wb") as f:
 428                     f.write(v.resolved.encode("utf-8"))
 429                     continue
 430
 431             if not v.resolved.startswith("keep:"):
 432                 raise Exception("Output source is not in keep or a literal")
 433             sp = v.resolved.split("/")
 434             srccollection = sp[0][5:]
 435             try:
 436                 reader = self.collection_cache.get(srccollection)
 437                 srcpath = urllib.parse.unquote("/".join(sp[1:]) if len(sp) > 1 else ".")
 438                 final.copy(srcpath, v.target, source_collection=reader, overwrite=False)
 439             except arvados.errors.ArgumentError as e:
 440                 logger.error("Creating CollectionReader for '%s' '%s': %s", k, v, e)
 441                 raise
 442             except IOError as e:
 443                 logger.error("While preparing output collection: %s", e)
 444                 raise
 445
 446         def rewrite(fileobj):
 447             fileobj["location"] = generatemapper.mapper(fileobj["location"]).target
 448             for k in ("listing", "contents", "nameext", "nameroot", "dirname"):
 449                 if k in fileobj:
 450                     del fileobj[k]
 451
 452         adjustDirObjs(outputObj, rewrite)
 453         adjustFileObjs(outputObj, rewrite)
 454
 455         with final.open("cwl.output.json", "w") as f:
 456             res = str(json.dumps(outputObj, sort_keys=True, indent=4, separators=(',',': '), ensure_ascii=False))
 457             f.write(res)
 458
 459         final.save_new(name=name, owner_uuid=self.project_uuid, storage_classes=storage_classes, ensure_unique_name=True)
 460
 461         logger.info("Final output collection %s \"%s\" (%s)", final.portable_data_hash(),
 462                     final.api_response()["name"],
 463                     final.manifest_locator())
 464
 465         final_uuid = final.manifest_locator()
 466         tags = tagsString.split(',')
 467         for tag in tags:
 468              self.api.links().create(body={
 469                 "head_uuid": final_uuid, "link_class": "tag", "name": tag
 470                 }).execute(num_retries=self.num_retries)
 471
 472         def finalcollection(fileobj):
 473             fileobj["location"] = "keep:%s/%s" % (final.portable_data_hash(), fileobj["location"])
 474
 475         adjustDirObjs(outputObj, finalcollection)
 476         adjustFileObjs(outputObj, finalcollection)
 477
 478         return (outputObj, final)
 479
 480     def set_crunch_output(self):
 481         if self.work_api == "containers":
 482             current = arvados_cwl.util.get_current_container(self.api, self.num_retries, logger)
 483             if current is None:
 484                 return
 485             try:
 486                 self.api.containers().update(uuid=current['uuid'],
 487                                              body={
 488                                                  'output': self.final_output_collection.portable_data_hash(),
 489                                              }).execute(num_retries=self.num_retries)
 490                 self.api.collections().update(uuid=self.final_output_collection.manifest_locator(),
 491                                               body={
 492                                                   'is_trashed': True
 493                                               }).execute(num_retries=self.num_retries)
 494             except Exception:
 495                 logger.exception("Setting container output")
 496                 raise
 497
 498     def apply_reqs(self, job_order_object, tool):
 499         if "https://w3id.org/cwl/cwl#requirements" in job_order_object:
 500             if tool.metadata.get("http://commonwl.org/cwltool#original_cwlVersion") == 'v1.0':
 501                 raise WorkflowException(
 502                     "`cwl:requirements` in the input object is not part of CWL "
 503                     "v1.0. You can adjust to use `cwltool:overrides` instead; or you "
 504                     "can set the cwlVersion to v1.1 or greater and re-run with "
 505                     "--enable-dev.")
 506             job_reqs = job_order_object["https://w3id.org/cwl/cwl#requirements"]
 507             for req in job_reqs:
 508                 tool.requirements.append(req)
 509
 510     def arv_executor(self, updated_tool, job_order, runtimeContext, logger=None):
 511         self.debug = runtimeContext.debug
 512
 513         workbench1 = self.api.config()["Services"]["Workbench1"]["ExternalURL"]
 514         workbench2 = self.api.config()["Services"]["Workbench2"]["ExternalURL"]
 515         controller = self.api.config()["Services"]["Controller"]["ExternalURL"]
 516         logger.info("Using cluster %s (%s)", self.api.config()["ClusterID"], workbench2 or workbench1 or controller)
 517
 518         updated_tool.visit(self.check_features)
 519
 520         self.pipeline = None
 521         self.fs_access = runtimeContext.make_fs_access(runtimeContext.basedir)
 522         self.secret_store = runtimeContext.secret_store
 523
 524         self.trash_intermediate = runtimeContext.trash_intermediate
 525         if self.trash_intermediate and self.work_api != "containers":
 526             raise Exception("--trash-intermediate is only supported with --api=containers.")
 527
 528         self.intermediate_output_ttl = runtimeContext.intermediate_output_ttl
 529         if self.intermediate_output_ttl and self.work_api != "containers":
 530             raise Exception("--intermediate-output-ttl is only supported with --api=containers.")
 531         if self.intermediate_output_ttl < 0:
 532             raise Exception("Invalid value %d for --intermediate-output-ttl, cannot be less than zero" % self.intermediate_output_ttl)
 533
 534         if runtimeContext.submit_request_uuid and self.work_api != "containers":
 535             raise Exception("--submit-request-uuid requires containers API, but using '{}' api".format(self.work_api))
 536
 537         runtimeContext = runtimeContext.copy()
 538
 539         default_storage_classes = ",".join([k for k,v in self.api.config().get("StorageClasses", {"default": {"Default": True}}).items() if v.get("Default") is True])
 540         if runtimeContext.storage_classes == "default":
 541             runtimeContext.storage_classes = default_storage_classes
 542         if runtimeContext.intermediate_storage_classes == "default":
 543             runtimeContext.intermediate_storage_classes = default_storage_classes
 544
 545         if not runtimeContext.name:
 546             runtimeContext.name = self.name = updated_tool.tool.get("label") or updated_tool.metadata.get("label") or os.path.basename(updated_tool.tool["id"])
 547
 548         if runtimeContext.copy_deps is None and (runtimeContext.create_workflow or runtimeContext.update_workflow):
 549             # When creating or updating workflow record, by default
 550             # always copy dependencies and ensure Docker images are up
 551             # to date.
 552             runtimeContext.copy_deps = True
 553             runtimeContext.match_local_docker = True
 554
 555         if runtimeContext.update_workflow and self.project_uuid is None:
 556             # If we are updating a workflow, make sure anything that
 557             # gets uploaded goes into the same parent project, unless
 558             # an alternate --project-uuid was provided.
 559             existing_wf = self.api.workflows().get(uuid=runtimeContext.update_workflow).execute()
 560             runtimeContext.project_uuid = existing_wf["owner_uuid"]
 561
 562         self.project_uuid = runtimeContext.project_uuid
 563
 564         # Upload local file references in the job order.
 565         job_order = upload_job_order(self, "%s input" % runtimeContext.name,
 566                                      updated_tool, job_order, runtimeContext)
 567
 568         # the last clause means: if it is a command line tool, and we
 569         # are going to wait for the result, and always_submit_runner
 570         # is false, then we don't submit a runner process.
 571
 572         submitting = (runtimeContext.update_workflow or
 573                       runtimeContext.create_workflow or
 574                       (runtimeContext.submit and not
 575                        (updated_tool.tool["class"] == "CommandLineTool" and
 576                         runtimeContext.wait and
 577                         not runtimeContext.always_submit_runner)))
 578
 579         loadingContext = self.loadingContext.copy()
 580         loadingContext.do_validate = False
 581         if submitting:
 582             loadingContext.do_update = False
 583             # Document may have been auto-updated. Reload the original
 584             # document with updating disabled because we want to
 585             # submit the document with its original CWL version, not
 586             # the auto-updated one.
 587             tool = load_tool(updated_tool.tool["id"], loadingContext)
 588         else:
 589             tool = updated_tool
 590
 591         # Upload direct dependencies of workflow steps, get back mapping of files to keep references.
 592         # Also uploads docker images.
 593         merged_map = upload_workflow_deps(self, tool, runtimeContext)
 594
 595         # Recreate process object (ArvadosWorkflow or
 596         # ArvadosCommandTool) because tool document may have been
 597         # updated by upload_workflow_deps in ways that modify
 598         # inheritance of hints or requirements.
 599         loadingContext.loader = tool.doc_loader
 600         loadingContext.avsc_names = tool.doc_schema
 601         loadingContext.metadata = tool.metadata
 602         tool = load_tool(tool.tool, loadingContext)
 603
 604         if runtimeContext.update_workflow or runtimeContext.create_workflow:
 605             # Create a pipeline template or workflow record and exit.
 606             if self.work_api == "containers":
 607                 uuid = upload_workflow(self, tool, job_order,
 608                                        runtimeContext.project_uuid,
 609                                        runtimeContext,
 610                                        uuid=runtimeContext.update_workflow,
 611                                        submit_runner_ram=runtimeContext.submit_runner_ram,
 612                                        name=runtimeContext.name,
 613                                        merged_map=merged_map,
 614                                        submit_runner_image=runtimeContext.submit_runner_image)
 615                 self.stdout.write(uuid + "\n")
 616                 return (None, "success")
 617
 618         self.apply_reqs(job_order, tool)
 619
 620         self.ignore_docker_for_reuse = runtimeContext.ignore_docker_for_reuse
 621         self.eval_timeout = runtimeContext.eval_timeout
 622
 623         runtimeContext.use_container = True
 624         runtimeContext.tmpdir_prefix = "tmp"
 625         runtimeContext.work_api = self.work_api
 626
 627         if self.work_api == "containers":
 628             if self.ignore_docker_for_reuse:
 629                 raise Exception("--ignore-docker-for-reuse not supported with containers API.")
 630             runtimeContext.outdir = "/var/spool/cwl"
 631             runtimeContext.docker_outdir = "/var/spool/cwl"
 632             runtimeContext.tmpdir = "/tmp"
 633             runtimeContext.docker_tmpdir = "/tmp"
 634
 635         if runtimeContext.priority < 1 or runtimeContext.priority > 1000:
 636             raise Exception("--priority must be in the range 1..1000.")
 637
 638         if self.should_estimate_cache_size:
 639             visited = set()
 640             estimated_size = [0]
 641             def estimate_collection_cache(obj):
 642                 if obj.get("location", "").startswith("keep:"):
 643                     m = pdh_size.match(obj["location"][5:])
 644                     if m and m.group(1) not in visited:
 645                         visited.add(m.group(1))
 646                         estimated_size[0] += int(m.group(2))
 647             visit_class(job_order, ("File", "Directory"), estimate_collection_cache)
 648             runtimeContext.collection_cache_size = max(((estimated_size[0]*192) // (1024*1024))+1, 256)
 649             self.collection_cache.set_cap(runtimeContext.collection_cache_size*1024*1024)
 650
 651         logger.info("Using collection cache size %s MiB", runtimeContext.collection_cache_size)
 652
 653         runnerjob = None
 654         if runtimeContext.submit:
 655             # Submit a runner job to run the workflow for us.
 656             if self.work_api == "containers":
 657                 if submitting:
 658                     tool = RunnerContainer(self, updated_tool,
 659                                            tool, loadingContext, runtimeContext.enable_reuse,
 660                                            self.output_name,
 661                                            self.output_tags,
 662                                            submit_runner_ram=runtimeContext.submit_runner_ram,
 663                                            name=runtimeContext.name,
 664                                            on_error=runtimeContext.on_error,
 665                                            submit_runner_image=runtimeContext.submit_runner_image,
 666                                            intermediate_output_ttl=runtimeContext.intermediate_output_ttl,
 667                                            merged_map=merged_map,
 668                                            priority=runtimeContext.priority,
 669                                            secret_store=self.secret_store,
 670                                            collection_cache_size=runtimeContext.collection_cache_size,
 671                                            collection_cache_is_default=self.should_estimate_cache_size)
 672                 else:
 673                     runtimeContext.runnerjob = tool.tool["id"]
 674
 675         if runtimeContext.cwl_runner_job is not None:
 676             self.uuid = runtimeContext.cwl_runner_job.get('uuid')
 677
 678         jobiter = tool.job(job_order,
 679                            self.output_callback,
 680                            runtimeContext)
 681
 682         if runtimeContext.submit and not runtimeContext.wait:
 683             runnerjob = next(jobiter)
 684             runnerjob.run(runtimeContext)
 685             self.stdout.write(runnerjob.uuid+"\n")
 686             return (None, "success")
 687
 688         current_container = arvados_cwl.util.get_current_container(self.api, self.num_retries, logger)
 689         if current_container:
 690             logger.info("Running inside container %s", current_container.get("uuid"))
 691
 692         self.poll_api = arvados.api('v1', timeout=runtimeContext.http_timeout)
 693         self.polling_thread = threading.Thread(target=self.poll_states)
 694         self.polling_thread.start()
 695
 696         self.task_queue = TaskQueue(self.workflow_eval_lock, self.thread_count)
 697
 698         try:
 699             self.workflow_eval_lock.acquire()
 700
 701             # Holds the lock while this code runs and releases it when
 702             # it is safe to do so in self.workflow_eval_lock.wait(),
 703             # at which point on_message can update job state and
 704             # process output callbacks.
 705
 706             loopperf = Perf(metrics, "jobiter")
 707             loopperf.__enter__()
 708             for runnable in jobiter:
 709                 loopperf.__exit__()
 710
 711                 if self.stop_polling.is_set():
 712                     break
 713
 714                 if self.task_queue.error is not None:
 715                     raise self.task_queue.error
 716
 717                 if runnable:
 718                     with Perf(metrics, "run"):
 719                         self.start_run(runnable, runtimeContext)
 720                 else:
 721                     if (self.task_queue.in_flight + len(self.processes)) > 0:
 722                         self.workflow_eval_lock.wait(3)
 723                     else:
 724                         logger.error("Workflow is deadlocked, no runnable processes and not waiting on any pending processes.")
 725                         break
 726
 727                 if self.stop_polling.is_set():
 728                     break
 729
 730                 loopperf.__enter__()
 731             loopperf.__exit__()
 732
 733             while (self.task_queue.in_flight + len(self.processes)) > 0:
 734                 if self.task_queue.error is not None:
 735                     raise self.task_queue.error
 736                 self.workflow_eval_lock.wait(3)
 737
 738         except UnsupportedRequirement:
 739             raise
 740         except:
 741             if sys.exc_info()[0] is KeyboardInterrupt or sys.exc_info()[0] is SystemExit:
 742                 logger.error("Interrupted, workflow will be cancelled")
 743             elif isinstance(sys.exc_info()[1], WorkflowException):
 744                 logger.error("Workflow execution failed:\n%s", sys.exc_info()[1], exc_info=(sys.exc_info()[1] if self.debug else False))
 745             else:
 746                 logger.exception("Workflow execution failed")
 747
 748             if self.pipeline:
 749                 self.api.pipeline_instances().update(uuid=self.pipeline["uuid"],
 750                                                      body={"state": "Failed"}).execute(num_retries=self.num_retries)
 751
 752             if self.work_api == "containers" and not current_container:
 753                 # Not running in a crunch container, so cancel any outstanding processes.
 754                 for p in self.processes:
 755                     try:
 756                         self.api.container_requests().update(uuid=p,
 757                                                              body={"priority": "0"}
 758                         ).execute(num_retries=self.num_retries)
 759                     except Exception:
 760                         pass
 761         finally:
 762             self.workflow_eval_lock.release()
 763             self.task_queue.drain()
 764             self.stop_polling.set()
 765             self.polling_thread.join()
 766             self.task_queue.join()
 767
 768         if self.final_status == "UnsupportedRequirement":
 769             raise UnsupportedRequirement("Check log for details.")
 770
 771         if self.final_output is None:
 772             raise WorkflowException("Workflow did not return a result.")
 773
 774         if runtimeContext.submit and isinstance(tool, Runner):
 775             logger.info("Final output collection %s", tool.final_output)
 776             if workbench2 or workbench1:
 777                 logger.info("Output at %scollections/%s", workbench2 or workbench1, tool.final_output)
 778         else:
 779             if self.output_name is None:
 780                 self.output_name = "Output of %s" % (shortname(tool.tool["id"]))
 781             if self.output_tags is None:
 782                 self.output_tags = ""
 783
 784             storage_classes = ""
 785             storage_class_req, _ = tool.get_requirement("http://arvados.org/cwl#OutputStorageClass")
 786             if storage_class_req and storage_class_req.get("finalStorageClass"):
 787                 storage_classes = aslist(storage_class_req["finalStorageClass"])
 788             else:
 789                 storage_classes = runtimeContext.storage_classes.strip().split(",")
 790
 791             self.final_output, self.final_output_collection = self.make_output_collection(self.output_name, storage_classes, self.output_tags, self.final_output)
 792             self.set_crunch_output()
 793
 794         if runtimeContext.compute_checksum:
 795             adjustDirObjs(self.final_output, partial(get_listing, self.fs_access))
 796             adjustFileObjs(self.final_output, partial(compute_checksums, self.fs_access))
 797
 798         if self.trash_intermediate and self.final_status == "success":
 799             self.trash_intermediate_output()
 800
 801         return (self.final_output, self.final_status)