Merge branch 'thehyve/fix-crunch-documentation' Fix a typo in Crunch Dispatch install...
[arvados.git] / sdk / cwl / arvados_cwl / arvjob.py
1 # Copyright (C) The Arvados Authors. All rights reserved.
2 #
3 # SPDX-License-Identifier: Apache-2.0
4
5 import logging
6 import re
7 import copy
8 import json
9 import time
10
11 from cwltool.process import get_feature, shortname, UnsupportedRequirement
12 from cwltool.errors import WorkflowException
13 from cwltool.command_line_tool import revmap_file, CommandLineTool
14 from cwltool.load_tool import fetch_document
15 from cwltool.builder import Builder
16 from cwltool.pathmapper import adjustFileObjs, adjustDirObjs, visit_class
17
18 from schema_salad.sourceline import SourceLine
19
20 import ruamel.yaml as yaml
21
22 import arvados.collection
23 from arvados.errors import ApiError
24
25 from .arvdocker import arv_docker_get_image
26 from .runner import Runner, arvados_jobs_image, packed_workflow, upload_workflow_collection, trim_anonymous_location, remove_redundant_fields
27 from .pathmapper import VwdPathMapper, trim_listing
28 from .perf import Perf
29 from . import done
30 from ._version import __version__
31
32 logger = logging.getLogger('arvados.cwl-runner')
33 metrics = logging.getLogger('arvados.cwl-runner.metrics')
34
35 crunchrunner_re = re.compile(r"^.*crunchrunner: \$\(task\.(tmpdir|outdir|keep)\)=(.*)$")
36
37 crunchrunner_git_commit = 'a3f2cb186e437bfce0031b024b2157b73ed2717d'
38
39 class ArvadosJob(object):
40     """Submit and manage a Crunch job for executing a CWL CommandLineTool."""
41
42     def __init__(self, runner):
43         self.arvrunner = runner
44         self.running = False
45         self.uuid = None
46
47     def run(self, dry_run=False, pull_image=True, **kwargs):
48         script_parameters = {
49             "command": self.command_line
50         }
51         runtime_constraints = {}
52
53         with Perf(metrics, "generatefiles %s" % self.name):
54             if self.generatefiles["listing"]:
55                 vwd = arvados.collection.Collection(api_client=self.arvrunner.api,
56                                                     keep_client=self.arvrunner.keep_client,
57                                                     num_retries=self.arvrunner.num_retries)
58                 script_parameters["task.vwd"] = {}
59                 generatemapper = VwdPathMapper([self.generatefiles], "", "",
60                                                separateDirs=False)
61
62                 with Perf(metrics, "createfiles %s" % self.name):
63                     for f, p in generatemapper.items():
64                         if p.type == "CreateFile":
65                             with vwd.open(p.target, "w") as n:
66                                 n.write(p.resolved.encode("utf-8"))
67
68                 if vwd:
69                     with Perf(metrics, "generatefiles.save_new %s" % self.name):
70                         vwd.save_new()
71
72                 for f, p in generatemapper.items():
73                     if p.type == "File":
74                         script_parameters["task.vwd"][p.target] = p.resolved
75                     if p.type == "CreateFile":
76                         script_parameters["task.vwd"][p.target] = "$(task.keep)/%s/%s" % (vwd.portable_data_hash(), p.target)
77
78         script_parameters["task.env"] = {"TMPDIR": self.tmpdir, "HOME": self.outdir}
79         if self.environment:
80             script_parameters["task.env"].update(self.environment)
81
82         if self.stdin:
83             script_parameters["task.stdin"] = self.stdin
84
85         if self.stdout:
86             script_parameters["task.stdout"] = self.stdout
87
88         if self.stderr:
89             script_parameters["task.stderr"] = self.stderr
90
91         if self.successCodes:
92             script_parameters["task.successCodes"] = self.successCodes
93         if self.temporaryFailCodes:
94             script_parameters["task.temporaryFailCodes"] = self.temporaryFailCodes
95         if self.permanentFailCodes:
96             script_parameters["task.permanentFailCodes"] = self.permanentFailCodes
97
98         with Perf(metrics, "arv_docker_get_image %s" % self.name):
99             (docker_req, docker_is_req) = get_feature(self, "DockerRequirement")
100             if docker_req and kwargs.get("use_container") is not False:
101                 if docker_req.get("dockerOutputDirectory"):
102                     raise SourceLine(docker_req, "dockerOutputDirectory", UnsupportedRequirement).makeError(
103                         "Option 'dockerOutputDirectory' of DockerRequirement not supported.")
104                 runtime_constraints["docker_image"] = arv_docker_get_image(self.arvrunner.api, docker_req, pull_image, self.arvrunner.project_uuid)
105             else:
106                 runtime_constraints["docker_image"] = "arvados/jobs"
107
108         resources = self.builder.resources
109         if resources is not None:
110             runtime_constraints["min_cores_per_node"] = resources.get("cores", 1)
111             runtime_constraints["min_ram_mb_per_node"] = resources.get("ram")
112             runtime_constraints["min_scratch_mb_per_node"] = resources.get("tmpdirSize", 0) + resources.get("outdirSize", 0)
113
114         runtime_req, _ = get_feature(self, "http://arvados.org/cwl#RuntimeConstraints")
115         if runtime_req:
116             if "keep_cache" in runtime_req:
117                 runtime_constraints["keep_cache_mb_per_task"] = runtime_req["keep_cache"]
118                 runtime_constraints["min_ram_mb_per_node"] += runtime_req["keep_cache"]
119             if "outputDirType" in runtime_req:
120                 if runtime_req["outputDirType"] == "local_output_dir":
121                     script_parameters["task.keepTmpOutput"] = False
122                 elif runtime_req["outputDirType"] == "keep_output_dir":
123                     script_parameters["task.keepTmpOutput"] = True
124
125         filters = [["repository", "=", "arvados"],
126                    ["script", "=", "crunchrunner"],
127                    ["script_version", "in git", crunchrunner_git_commit]]
128         if not self.arvrunner.ignore_docker_for_reuse:
129             filters.append(["docker_image_locator", "in docker", runtime_constraints["docker_image"]])
130
131         enable_reuse = kwargs.get("enable_reuse", True)
132         if enable_reuse:
133             reuse_req, _ = get_feature(self, "http://arvados.org/cwl#ReuseRequirement")
134             if reuse_req:
135                 enable_reuse = reuse_req["enableReuse"]
136
137         self.output_callback = self.arvrunner.get_wrapped_callback(self.output_callback)
138
139         try:
140             with Perf(metrics, "create %s" % self.name):
141                 response = self.arvrunner.api.jobs().create(
142                     body={
143                         "owner_uuid": self.arvrunner.project_uuid,
144                         "script": "crunchrunner",
145                         "repository": "arvados",
146                         "script_version": "master",
147                         "minimum_script_version": crunchrunner_git_commit,
148                         "script_parameters": {"tasks": [script_parameters]},
149                         "runtime_constraints": runtime_constraints
150                     },
151                     filters=filters,
152                     find_or_create=enable_reuse
153                 ).execute(num_retries=self.arvrunner.num_retries)
154
155             self.uuid = response["uuid"]
156             self.arvrunner.process_submitted(self)
157
158             self.update_pipeline_component(response)
159
160             if response["state"] == "Complete":
161                 logger.info("%s reused job %s", self.arvrunner.label(self), response["uuid"])
162                 # Give read permission to the desired project on reused jobs
163                 if response["owner_uuid"] != self.arvrunner.project_uuid:
164                     try:
165                         self.arvrunner.api.links().create(body={
166                             'link_class': 'permission',
167                             'name': 'can_read',
168                             'tail_uuid': self.arvrunner.project_uuid,
169                             'head_uuid': response["uuid"],
170                             }).execute(num_retries=self.arvrunner.num_retries)
171                     except ApiError as e:
172                         # The user might not have "manage" access on the job: log
173                         # a message and continue.
174                         logger.info("Creating read permission on job %s: %s",
175                                     response["uuid"],
176                                     e)
177             else:
178                 logger.info("%s %s is %s", self.arvrunner.label(self), response["uuid"], response["state"])
179         except Exception as e:
180             logger.exception("%s error" % (self.arvrunner.label(self)))
181             self.output_callback({}, "permanentFail")
182
183     def update_pipeline_component(self, record):
184         with self.arvrunner.workflow_eval_lock:
185             if self.arvrunner.pipeline:
186                 self.arvrunner.pipeline["components"][self.name] = {"job": record}
187                 with Perf(metrics, "update_pipeline_component %s" % self.name):
188                     self.arvrunner.pipeline = self.arvrunner.api.pipeline_instances().update(
189                         uuid=self.arvrunner.pipeline["uuid"],
190                         body={
191                             "components": self.arvrunner.pipeline["components"]
192                         }).execute(num_retries=self.arvrunner.num_retries)
193             if self.arvrunner.uuid:
194                 try:
195                     job = self.arvrunner.api.jobs().get(uuid=self.arvrunner.uuid).execute()
196                     if job:
197                         components = job["components"]
198                         components[self.name] = record["uuid"]
199                         self.arvrunner.api.jobs().update(
200                             uuid=self.arvrunner.uuid,
201                             body={
202                                 "components": components
203                             }).execute(num_retries=self.arvrunner.num_retries)
204                 except Exception as e:
205                     logger.info("Error adding to components: %s", e)
206
207     def done(self, record):
208         try:
209             self.update_pipeline_component(record)
210         except:
211             pass
212
213         try:
214             if record["state"] == "Complete":
215                 processStatus = "success"
216             else:
217                 processStatus = "permanentFail"
218
219             outputs = {}
220             try:
221                 if record["output"]:
222                     with Perf(metrics, "inspect log %s" % self.name):
223                         logc = arvados.collection.CollectionReader(record["log"],
224                                                                    api_client=self.arvrunner.api,
225                                                                    keep_client=self.arvrunner.keep_client,
226                                                                    num_retries=self.arvrunner.num_retries)
227                         log = logc.open(logc.keys()[0])
228                         dirs = {
229                             "tmpdir": "/tmpdir",
230                             "outdir": "/outdir",
231                             "keep": "/keep"
232                         }
233                         for l in log:
234                             # Determine the tmpdir, outdir and keep paths from
235                             # the job run.  Unfortunately, we can't take the first
236                             # values we find (which are expected to be near the
237                             # top) and stop scanning because if the node fails and
238                             # the job restarts on a different node these values
239                             # will different runs, and we need to know about the
240                             # final run that actually produced output.
241                             g = crunchrunner_re.match(l)
242                             if g:
243                                 dirs[g.group(1)] = g.group(2)
244
245                     if processStatus == "permanentFail":
246                         done.logtail(logc, logger, "%s error log:" % self.arvrunner.label(self))
247
248                     with Perf(metrics, "output collection %s" % self.name):
249                         outputs = done.done(self, record, dirs["tmpdir"],
250                                             dirs["outdir"], dirs["keep"])
251             except WorkflowException as e:
252                 logger.error("%s unable to collect output from %s:\n%s",
253                              self.arvrunner.label(self), record["output"], e, exc_info=(e if self.arvrunner.debug else False))
254                 processStatus = "permanentFail"
255             except Exception as e:
256                 logger.exception("Got unknown exception while collecting output for job %s:", self.name)
257                 processStatus = "permanentFail"
258
259             # Note: Currently, on error output_callback is expecting an empty dict,
260             # anything else will fail.
261             if not isinstance(outputs, dict):
262                 logger.error("Unexpected output type %s '%s'", type(outputs), outputs)
263                 outputs = {}
264                 processStatus = "permanentFail"
265         finally:
266             self.output_callback(outputs, processStatus)
267
268
269 class RunnerJob(Runner):
270     """Submit and manage a Crunch job that runs crunch_scripts/cwl-runner."""
271
272     def arvados_job_spec(self, dry_run=False, pull_image=True, **kwargs):
273         """Create an Arvados job specification for this workflow.
274
275         The returned dict can be used to create a job (i.e., passed as
276         the +body+ argument to jobs().create()), or as a component in
277         a pipeline template or pipeline instance.
278         """
279
280         if self.tool.tool["id"].startswith("keep:"):
281             self.job_order["cwl:tool"] = self.tool.tool["id"][5:]
282         else:
283             packed = packed_workflow(self.arvrunner, self.tool, self.merged_map)
284             wf_pdh = upload_workflow_collection(self.arvrunner, self.name, packed)
285             self.job_order["cwl:tool"] = "%s/workflow.cwl#main" % wf_pdh
286
287         adjustDirObjs(self.job_order, trim_listing)
288         visit_class(self.job_order, ("File", "Directory"), trim_anonymous_location)
289         visit_class(self.job_order, ("File", "Directory"), remove_redundant_fields)
290
291         if self.output_name:
292             self.job_order["arv:output_name"] = self.output_name
293
294         if self.output_tags:
295             self.job_order["arv:output_tags"] = self.output_tags
296
297         self.job_order["arv:enable_reuse"] = self.enable_reuse
298
299         if self.on_error:
300             self.job_order["arv:on_error"] = self.on_error
301
302         if kwargs.get("debug"):
303             self.job_order["arv:debug"] = True
304
305         return {
306             "script": "cwl-runner",
307             "script_version": "master",
308             "minimum_script_version": "570509ab4d2ef93d870fd2b1f2eab178afb1bad9",
309             "repository": "arvados",
310             "script_parameters": self.job_order,
311             "runtime_constraints": {
312                 "docker_image": arvados_jobs_image(self.arvrunner, self.jobs_image),
313                 "min_ram_mb_per_node": self.submit_runner_ram
314             }
315         }
316
317     def run(self, **kwargs):
318         job_spec = self.arvados_job_spec(**kwargs)
319
320         job_spec.setdefault("owner_uuid", self.arvrunner.project_uuid)
321
322         job = self.arvrunner.api.jobs().create(
323             body=job_spec,
324             find_or_create=self.enable_reuse
325         ).execute(num_retries=self.arvrunner.num_retries)
326
327         for k,v in job_spec["script_parameters"].items():
328             if v is False or v is None or isinstance(v, dict):
329                 job_spec["script_parameters"][k] = {"value": v}
330
331         del job_spec["owner_uuid"]
332         job_spec["job"] = job
333
334         instance_spec = {
335             "owner_uuid": self.arvrunner.project_uuid,
336             "name": self.name,
337             "components": {
338                 "cwl-runner": job_spec,
339             },
340             "state": "RunningOnServer",
341         }
342         if not self.enable_reuse:
343             instance_spec["properties"] = {"run_options": {"enable_job_reuse": False}}
344
345         self.arvrunner.pipeline = self.arvrunner.api.pipeline_instances().create(
346             body=instance_spec).execute(num_retries=self.arvrunner.num_retries)
347         logger.info("Created pipeline %s", self.arvrunner.pipeline["uuid"])
348
349         if kwargs.get("wait") is False:
350             self.uuid = self.arvrunner.pipeline["uuid"]
351             return
352
353         self.uuid = job["uuid"]
354         self.arvrunner.process_submitted(self)
355
356
357 class RunnerTemplate(object):
358     """An Arvados pipeline template that invokes a CWL workflow."""
359
360     type_to_dataclass = {
361         'boolean': 'boolean',
362         'File': 'File',
363         'Directory': 'Collection',
364         'float': 'number',
365         'int': 'number',
366         'string': 'text',
367     }
368
369     def __init__(self, runner, tool, job_order, enable_reuse, uuid,
370                  submit_runner_ram=0, name=None, merged_map=None):
371         self.runner = runner
372         self.tool = tool
373         self.job = RunnerJob(
374             runner=runner,
375             tool=tool,
376             job_order=job_order,
377             enable_reuse=enable_reuse,
378             output_name=None,
379             output_tags=None,
380             submit_runner_ram=submit_runner_ram,
381             name=name,
382             merged_map=merged_map)
383         self.uuid = uuid
384
385     def pipeline_component_spec(self):
386         """Return a component that Workbench and a-r-p-i will understand.
387
388         Specifically, translate CWL input specs to Arvados pipeline
389         format, like {"dataclass":"File","value":"xyz"}.
390         """
391
392         spec = self.job.arvados_job_spec()
393
394         # Most of the component spec is exactly the same as the job
395         # spec (script, script_version, etc.).
396         # spec['script_parameters'] isn't right, though. A component
397         # spec's script_parameters hash is a translation of
398         # self.tool.tool['inputs'] with defaults/overrides taken from
399         # the job order. So we move the job parameters out of the way
400         # and build a new spec['script_parameters'].
401         job_params = spec['script_parameters']
402         spec['script_parameters'] = {}
403
404         for param in self.tool.tool['inputs']:
405             param = copy.deepcopy(param)
406
407             # Data type and "required" flag...
408             types = param['type']
409             if not isinstance(types, list):
410                 types = [types]
411             param['required'] = 'null' not in types
412             non_null_types = [t for t in types if t != "null"]
413             if len(non_null_types) == 1:
414                 the_type = [c for c in non_null_types][0]
415                 dataclass = None
416                 if isinstance(the_type, basestring):
417                     dataclass = self.type_to_dataclass.get(the_type)
418                 if dataclass:
419                     param['dataclass'] = dataclass
420             # Note: If we didn't figure out a single appropriate
421             # dataclass, we just left that attribute out.  We leave
422             # the "type" attribute there in any case, which might help
423             # downstream.
424
425             # Title and description...
426             title = param.pop('label', '')
427             descr = param.pop('doc', '').rstrip('\n')
428             if title:
429                 param['title'] = title
430             if descr:
431                 param['description'] = descr
432
433             # Fill in the value from the current job order, if any.
434             param_id = shortname(param.pop('id'))
435             value = job_params.get(param_id)
436             if value is None:
437                 pass
438             elif not isinstance(value, dict):
439                 param['value'] = value
440             elif param.get('dataclass') in ('File', 'Collection') and value.get('location'):
441                 param['value'] = value['location'][5:]
442
443             spec['script_parameters'][param_id] = param
444         spec['script_parameters']['cwl:tool'] = job_params['cwl:tool']
445         return spec
446
447     def save(self):
448         body = {
449             "components": {
450                 self.job.name: self.pipeline_component_spec(),
451             },
452             "name": self.job.name,
453         }
454         if self.runner.project_uuid:
455             body["owner_uuid"] = self.runner.project_uuid
456         if self.uuid:
457             self.runner.api.pipeline_templates().update(
458                 uuid=self.uuid, body=body).execute(
459                     num_retries=self.runner.num_retries)
460             logger.info("Updated template %s", self.uuid)
461         else:
462             self.uuid = self.runner.api.pipeline_templates().create(
463                 body=body, ensure_unique_name=True).execute(
464                     num_retries=self.runner.num_retries)['uuid']
465             logger.info("Created template %s", self.uuid)