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, cleanup_name_for_collection
  35 from .runner import Runner, upload_docker, upload_job_order, upload_workflow_deps, make_builder
  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, output_properties, 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
 460         final.save_new(name=name, owner_uuid=self.project_uuid, storage_classes=storage_classes,
 461                        ensure_unique_name=True, properties=output_properties)
 462
 463         logger.info("Final output collection %s \"%s\" (%s)", final.portable_data_hash(),
 464                     final.api_response()["name"],
 465                     final.manifest_locator())
 466
 467         final_uuid = final.manifest_locator()
 468         tags = tagsString.split(',')
 469         for tag in tags:
 470              self.api.links().create(body={
 471                 "head_uuid": final_uuid, "link_class": "tag", "name": tag
 472                 }).execute(num_retries=self.num_retries)
 473
 474         def finalcollection(fileobj):
 475             fileobj["location"] = "keep:%s/%s" % (final.portable_data_hash(), fileobj["location"])
 476
 477         adjustDirObjs(outputObj, finalcollection)
 478         adjustFileObjs(outputObj, finalcollection)
 479
 480         return (outputObj, final)
 481
 482     def set_crunch_output(self):
 483         if self.work_api == "containers":
 484             current = arvados_cwl.util.get_current_container(self.api, self.num_retries, logger)
 485             if current is None:
 486                 return
 487             try:
 488                 self.api.containers().update(uuid=current['uuid'],
 489                                              body={
 490                                                  'output': self.final_output_collection.portable_data_hash(),
 491                                                  'output_properties': self.final_output_collection.get_properties(),
 492                                              }).execute(num_retries=self.num_retries)
 493                 self.api.collections().update(uuid=self.final_output_collection.manifest_locator(),
 494                                               body={
 495                                                   'is_trashed': True
 496                                               }).execute(num_retries=self.num_retries)
 497             except Exception:
 498                 logger.exception("Setting container output")
 499                 raise
 500
 501     def apply_reqs(self, job_order_object, tool):
 502         if "https://w3id.org/cwl/cwl#requirements" in job_order_object:
 503             if tool.metadata.get("http://commonwl.org/cwltool#original_cwlVersion") == 'v1.0':
 504                 raise WorkflowException(
 505                     "`cwl:requirements` in the input object is not part of CWL "
 506                     "v1.0. You can adjust to use `cwltool:overrides` instead; or you "
 507                     "can set the cwlVersion to v1.1 or greater and re-run with "
 508                     "--enable-dev.")
 509             job_reqs = job_order_object["https://w3id.org/cwl/cwl#requirements"]
 510             for req in job_reqs:
 511                 tool.requirements.append(req)
 512
 513     def arv_executor(self, updated_tool, job_order, runtimeContext, logger=None):
 514         self.debug = runtimeContext.debug
 515
 516         workbench1 = self.api.config()["Services"]["Workbench1"]["ExternalURL"]
 517         workbench2 = self.api.config()["Services"]["Workbench2"]["ExternalURL"]
 518         controller = self.api.config()["Services"]["Controller"]["ExternalURL"]
 519         logger.info("Using cluster %s (%s)", self.api.config()["ClusterID"], workbench2 or workbench1 or controller)
 520
 521         updated_tool.visit(self.check_features)
 522
 523         self.pipeline = None
 524         self.fs_access = runtimeContext.make_fs_access(runtimeContext.basedir)
 525         self.secret_store = runtimeContext.secret_store
 526
 527         self.trash_intermediate = runtimeContext.trash_intermediate
 528         if self.trash_intermediate and self.work_api != "containers":
 529             raise Exception("--trash-intermediate is only supported with --api=containers.")
 530
 531         self.intermediate_output_ttl = runtimeContext.intermediate_output_ttl
 532         if self.intermediate_output_ttl and self.work_api != "containers":
 533             raise Exception("--intermediate-output-ttl is only supported with --api=containers.")
 534         if self.intermediate_output_ttl < 0:
 535             raise Exception("Invalid value %d for --intermediate-output-ttl, cannot be less than zero" % self.intermediate_output_ttl)
 536
 537         if runtimeContext.submit_request_uuid and self.work_api != "containers":
 538             raise Exception("--submit-request-uuid requires containers API, but using '{}' api".format(self.work_api))
 539
 540         runtimeContext = runtimeContext.copy()
 541
 542         default_storage_classes = ",".join([k for k,v in self.api.config().get("StorageClasses", {"default": {"Default": True}}).items() if v.get("Default") is True])
 543         if runtimeContext.storage_classes == "default":
 544             runtimeContext.storage_classes = default_storage_classes
 545         if runtimeContext.intermediate_storage_classes == "default":
 546             runtimeContext.intermediate_storage_classes = default_storage_classes
 547
 548         if not runtimeContext.name:
 549             runtimeContext.name = self.name = updated_tool.tool.get("label") or updated_tool.metadata.get("label") or os.path.basename(updated_tool.tool["id"])
 550
 551         if runtimeContext.copy_deps is None and (runtimeContext.create_workflow or runtimeContext.update_workflow):
 552             # When creating or updating workflow record, by default
 553             # always copy dependencies and ensure Docker images are up
 554             # to date.
 555             runtimeContext.copy_deps = True
 556             runtimeContext.match_local_docker = True
 557
 558         if runtimeContext.update_workflow and self.project_uuid is None:
 559             # If we are updating a workflow, make sure anything that
 560             # gets uploaded goes into the same parent project, unless
 561             # an alternate --project-uuid was provided.
 562             existing_wf = self.api.workflows().get(uuid=runtimeContext.update_workflow).execute()
 563             runtimeContext.project_uuid = existing_wf["owner_uuid"]
 564
 565         self.project_uuid = runtimeContext.project_uuid
 566
 567         # Upload local file references in the job order.
 568         job_order = upload_job_order(self, "%s input" % runtimeContext.name,
 569                                      updated_tool, job_order, runtimeContext)
 570
 571         # the last clause means: if it is a command line tool, and we
 572         # are going to wait for the result, and always_submit_runner
 573         # is false, then we don't submit a runner process.
 574
 575         submitting = (runtimeContext.update_workflow or
 576                       runtimeContext.create_workflow or
 577                       (runtimeContext.submit and not
 578                        (updated_tool.tool["class"] == "CommandLineTool" and
 579                         runtimeContext.wait and
 580                         not runtimeContext.always_submit_runner)))
 581
 582         loadingContext = self.loadingContext.copy()
 583         loadingContext.do_validate = False
 584         if submitting:
 585             loadingContext.do_update = False
 586             # Document may have been auto-updated. Reload the original
 587             # document with updating disabled because we want to
 588             # submit the document with its original CWL version, not
 589             # the auto-updated one.
 590             tool = load_tool(updated_tool.tool["id"], loadingContext)
 591         else:
 592             tool = updated_tool
 593
 594         # Upload direct dependencies of workflow steps, get back mapping of files to keep references.
 595         # Also uploads docker images.
 596         merged_map = upload_workflow_deps(self, tool, runtimeContext)
 597
 598         # Recreate process object (ArvadosWorkflow or
 599         # ArvadosCommandTool) because tool document may have been
 600         # updated by upload_workflow_deps in ways that modify
 601         # inheritance of hints or requirements.
 602         loadingContext.loader = tool.doc_loader
 603         loadingContext.avsc_names = tool.doc_schema
 604         loadingContext.metadata = tool.metadata
 605         tool = load_tool(tool.tool, loadingContext)
 606
 607         if runtimeContext.update_workflow or runtimeContext.create_workflow:
 608             # Create a pipeline template or workflow record and exit.
 609             if self.work_api == "containers":
 610                 uuid = upload_workflow(self, tool, job_order,
 611                                        runtimeContext.project_uuid,
 612                                        runtimeContext,
 613                                        uuid=runtimeContext.update_workflow,
 614                                        submit_runner_ram=runtimeContext.submit_runner_ram,
 615                                        name=runtimeContext.name,
 616                                        merged_map=merged_map,
 617                                        submit_runner_image=runtimeContext.submit_runner_image)
 618                 self.stdout.write(uuid + "\n")
 619                 return (None, "success")
 620
 621         self.apply_reqs(job_order, tool)
 622
 623         self.ignore_docker_for_reuse = runtimeContext.ignore_docker_for_reuse
 624         self.eval_timeout = runtimeContext.eval_timeout
 625
 626         runtimeContext.use_container = True
 627         runtimeContext.tmpdir_prefix = "tmp"
 628         runtimeContext.work_api = self.work_api
 629
 630         if not self.output_name:
 631              self.output_name = "Output from workflow %s" % runtimeContext.name
 632
 633         self.output_name  = cleanup_name_for_collection(self.output_name)
 634
 635         if self.work_api == "containers":
 636             if self.ignore_docker_for_reuse:
 637                 raise Exception("--ignore-docker-for-reuse not supported with containers API.")
 638             runtimeContext.outdir = "/var/spool/cwl"
 639             runtimeContext.docker_outdir = "/var/spool/cwl"
 640             runtimeContext.tmpdir = "/tmp"
 641             runtimeContext.docker_tmpdir = "/tmp"
 642
 643         if runtimeContext.priority < 1 or runtimeContext.priority > 1000:
 644             raise Exception("--priority must be in the range 1..1000.")
 645
 646         if self.should_estimate_cache_size:
 647             visited = set()
 648             estimated_size = [0]
 649             def estimate_collection_cache(obj):
 650                 if obj.get("location", "").startswith("keep:"):
 651                     m = pdh_size.match(obj["location"][5:])
 652                     if m and m.group(1) not in visited:
 653                         visited.add(m.group(1))
 654                         estimated_size[0] += int(m.group(2))
 655             visit_class(job_order, ("File", "Directory"), estimate_collection_cache)
 656             runtimeContext.collection_cache_size = max(((estimated_size[0]*192) // (1024*1024))+1, 256)
 657             self.collection_cache.set_cap(runtimeContext.collection_cache_size*1024*1024)
 658
 659         logger.info("Using collection cache size %s MiB", runtimeContext.collection_cache_size)
 660
 661         runnerjob = None
 662         if runtimeContext.submit:
 663             # Submit a runner job to run the workflow for us.
 664             if self.work_api == "containers":
 665                 if submitting:
 666                     tool = RunnerContainer(self, updated_tool,
 667                                            tool, loadingContext, runtimeContext.enable_reuse,
 668                                            self.output_name,
 669                                            self.output_tags,
 670                                            submit_runner_ram=runtimeContext.submit_runner_ram,
 671                                            name=runtimeContext.name,
 672                                            on_error=runtimeContext.on_error,
 673                                            submit_runner_image=runtimeContext.submit_runner_image,
 674                                            intermediate_output_ttl=runtimeContext.intermediate_output_ttl,
 675                                            merged_map=merged_map,
 676                                            priority=runtimeContext.priority,
 677                                            secret_store=self.secret_store,
 678                                            collection_cache_size=runtimeContext.collection_cache_size,
 679                                            collection_cache_is_default=self.should_estimate_cache_size)
 680                 else:
 681                     runtimeContext.runnerjob = tool.tool["id"]
 682
 683         if runtimeContext.cwl_runner_job is not None:
 684             self.uuid = runtimeContext.cwl_runner_job.get('uuid')
 685
 686         jobiter = tool.job(job_order,
 687                            self.output_callback,
 688                            runtimeContext)
 689
 690         if runtimeContext.submit and not runtimeContext.wait:
 691             runnerjob = next(jobiter)
 692             runnerjob.run(runtimeContext)
 693             self.stdout.write(runnerjob.uuid+"\n")
 694             return (None, "success")
 695
 696         current_container = arvados_cwl.util.get_current_container(self.api, self.num_retries, logger)
 697         if current_container:
 698             logger.info("Running inside container %s", current_container.get("uuid"))
 699
 700         self.poll_api = arvados.api('v1', timeout=runtimeContext.http_timeout)
 701         self.polling_thread = threading.Thread(target=self.poll_states)
 702         self.polling_thread.start()
 703
 704         self.task_queue = TaskQueue(self.workflow_eval_lock, self.thread_count)
 705
 706         try:
 707             self.workflow_eval_lock.acquire()
 708
 709             # Holds the lock while this code runs and releases it when
 710             # it is safe to do so in self.workflow_eval_lock.wait(),
 711             # at which point on_message can update job state and
 712             # process output callbacks.
 713
 714             loopperf = Perf(metrics, "jobiter")
 715             loopperf.__enter__()
 716             for runnable in jobiter:
 717                 loopperf.__exit__()
 718
 719                 if self.stop_polling.is_set():
 720                     break
 721
 722                 if self.task_queue.error is not None:
 723                     raise self.task_queue.error
 724
 725                 if runnable:
 726                     with Perf(metrics, "run"):
 727                         self.start_run(runnable, runtimeContext)
 728                 else:
 729                     if (self.task_queue.in_flight + len(self.processes)) > 0:
 730                         self.workflow_eval_lock.wait(3)
 731                     else:
 732                         logger.error("Workflow is deadlocked, no runnable processes and not waiting on any pending processes.")
 733                         break
 734
 735                 if self.stop_polling.is_set():
 736                     break
 737
 738                 loopperf.__enter__()
 739             loopperf.__exit__()
 740
 741             while (self.task_queue.in_flight + len(self.processes)) > 0:
 742                 if self.task_queue.error is not None:
 743                     raise self.task_queue.error
 744                 self.workflow_eval_lock.wait(3)
 745
 746         except UnsupportedRequirement:
 747             raise
 748         except:
 749             if sys.exc_info()[0] is KeyboardInterrupt or sys.exc_info()[0] is SystemExit:
 750                 logger.error("Interrupted, workflow will be cancelled")
 751             elif isinstance(sys.exc_info()[1], WorkflowException):
 752                 logger.error("Workflow execution failed:\n%s", sys.exc_info()[1], exc_info=(sys.exc_info()[1] if self.debug else False))
 753             else:
 754                 logger.exception("Workflow execution failed")
 755
 756             if self.pipeline:
 757                 self.api.pipeline_instances().update(uuid=self.pipeline["uuid"],
 758                                                      body={"state": "Failed"}).execute(num_retries=self.num_retries)
 759
 760             if self.work_api == "containers" and not current_container:
 761                 # Not running in a crunch container, so cancel any outstanding processes.
 762                 for p in self.processes:
 763                     try:
 764                         self.api.container_requests().update(uuid=p,
 765                                                              body={"priority": "0"}
 766                         ).execute(num_retries=self.num_retries)
 767                     except Exception:
 768                         pass
 769         finally:
 770             self.workflow_eval_lock.release()
 771             self.task_queue.drain()
 772             self.stop_polling.set()
 773             self.polling_thread.join()
 774             self.task_queue.join()
 775
 776         if self.final_status == "UnsupportedRequirement":
 777             raise UnsupportedRequirement("Check log for details.")
 778
 779         if self.final_output is None:
 780             raise WorkflowException("Workflow did not return a result.")
 781
 782         if runtimeContext.submit and isinstance(tool, Runner):
 783             logger.info("Final output collection %s", tool.final_output)
 784             if workbench2 or workbench1:
 785                 logger.info("Output at %scollections/%s", workbench2 or workbench1, tool.final_output)
 786         else:
 787             if self.output_tags is None:
 788                 self.output_tags = ""
 789
 790             storage_classes = ""
 791             storage_class_req, _ = tool.get_requirement("http://arvados.org/cwl#OutputStorageClass")
 792             if storage_class_req and storage_class_req.get("finalStorageClass"):
 793                 storage_classes = aslist(storage_class_req["finalStorageClass"])
 794             else:
 795                 storage_classes = runtimeContext.storage_classes.strip().split(",")
 796
 797             output_properties = {}
 798             output_properties_req, _ = tool.get_requirement("http://arvados.org/cwl#OutputCollectionProperties")
 799             if output_properties_req:
 800                 builder = make_builder(job_order, tool.hints, tool.requirements, runtimeContext, tool.metadata)
 801                 for pr in output_properties_req["outputProperties"]:
 802                     output_properties[pr["propertyName"]] = builder.do_eval(pr["propertyValue"])
 803
 804             self.final_output, self.final_output_collection = self.make_output_collection(self.output_name, storage_classes,
 805                                                                                           self.output_tags, output_properties,
 806                                                                                           self.final_output)
 807             self.set_crunch_output()
 808
 809         if runtimeContext.compute_checksum:
 810             adjustDirObjs(self.final_output, partial(get_listing, self.fs_access))
 811             adjustFileObjs(self.final_output, partial(compute_checksums, self.fs_access))
 812
 813         if self.trash_intermediate and self.final_status == "success":
 814             self.trash_intermediate_output()
 815
 816         return (self.final_output, self.final_status)