#
# SPDX-License-Identifier: Apache-2.0
+from __future__ import division
+from builtins import next
+from builtins import object
+from builtins import str
+from future.utils import viewvalues
+
import argparse
import logging
import os
from arvados.keep import KeepClient
from arvados.errors import ApiError
+import arvados_cwl.util
from .arvcontainer import RunnerContainer
from .arvjob import RunnerJob, RunnerTemplate
from .runner import Runner, upload_docker, upload_job_order, upload_workflow_deps
-from .arvtool import ArvadosCommandTool
+from .arvtool import ArvadosCommandTool, validate_cluster_target, ArvadosExpressionTool
from .arvworkflow import ArvadosWorkflow, upload_workflow
-from .fsaccess import CollectionFsAccess, CollectionFetcher, collectionResolver, CollectionCache
+from .fsaccess import CollectionFsAccess, CollectionFetcher, collectionResolver, CollectionCache, pdh_size
from .perf import Perf
from .pathmapper import NoFollowPathMapper
from .task_queue import TaskQueue
from .context import ArvLoadingContext, ArvRuntimeContext
-from .util import get_current_container
from ._version import __version__
from cwltool.process import shortname, UnsupportedRequirement, use_custom_schema
-from cwltool.pathmapper import adjustFileObjs, adjustDirObjs, get_listing
+from cwltool.pathmapper import adjustFileObjs, adjustDirObjs, get_listing, visit_class
from cwltool.command_line_tool import compute_checksums
logger = logging.getLogger('arvados.cwl-runner')
metrics = logging.getLogger('arvados.cwl-runner.metrics')
+DEFAULT_PRIORITY = 500
+
class RuntimeStatusLoggingHandler(logging.Handler):
"""
Intercepts logging calls and report them as runtime statuses on runner
def __init__(self, runtime_status_update_func):
super(RuntimeStatusLoggingHandler, self).__init__()
self.runtime_status_update = runtime_status_update_func
+ self.updatingRuntimeStatus = False
def emit(self, record):
kind = None
kind = 'error'
elif record.levelno >= logging.WARNING:
kind = 'warning'
- if kind is not None:
- log_msg = record.getMessage()
- if '\n' in log_msg:
- # If the logged message is multi-line, use its first line as status
- # and the rest as detail.
- status, detail = log_msg.split('\n', 1)
- self.runtime_status_update(
- kind,
- "%s: %s" % (record.name, status),
- detail
- )
- else:
- self.runtime_status_update(
- kind,
- "%s: %s" % (record.name, record.getMessage())
- )
+ if kind is not None and self.updatingRuntimeStatus is not True:
+ self.updatingRuntimeStatus = True
+ try:
+ log_msg = record.getMessage()
+ if '\n' in log_msg:
+ # If the logged message is multi-line, use its first line as status
+ # and the rest as detail.
+ status, detail = log_msg.split('\n', 1)
+ self.runtime_status_update(
+ kind,
+ "%s: %s" % (record.name, status),
+ detail
+ )
+ else:
+ self.runtime_status_update(
+ kind,
+ "%s: %s" % (record.name, record.getMessage())
+ )
+ finally:
+ self.updatingRuntimeStatus = False
+
class ArvCwlExecutor(object):
"""Execute a CWL tool or workflow, submit work (using either jobs or
arvargs.output_name = None
arvargs.output_tags = None
arvargs.thread_count = 1
+ arvargs.collection_cache_size = None
self.api = api_client
self.processes = {}
self.thread_count = arvargs.thread_count
self.poll_interval = 12
self.loadingContext = None
+ self.should_estimate_cache_size = True
if keep_client is not None:
self.keep_client = keep_client
else:
self.keep_client = arvados.keep.KeepClient(api_client=self.api, num_retries=self.num_retries)
- self.collection_cache = CollectionCache(self.api, self.keep_client, self.num_retries)
+ if arvargs.collection_cache_size:
+ collection_cache_size = arvargs.collection_cache_size*1024*1024
+ self.should_estimate_cache_size = False
+ else:
+ collection_cache_size = 256*1024*1024
+
+ self.collection_cache = CollectionCache(self.api, self.keep_client, self.num_retries,
+ cap=collection_cache_size)
self.fetcher_constructor = partial(CollectionFetcher,
api_client=self.api,
raise Exception("Unsupported API '%s', expected one of %s" % (arvargs.work_api, expected_api))
if self.work_api == "jobs":
- logger.warn("""
+ logger.warning("""
*******************************
Using the deprecated 'jobs' API.
# Add a custom logging handler to the root logger for runtime status reporting
# if running inside a container
- if get_current_container(self.api, self.num_retries, logger):
+ if arvados_cwl.util.get_current_container(self.api, self.num_retries, logger):
root_logger = logging.getLogger('')
+
+ # Remove existing RuntimeStatusLoggingHandlers if they exist
+ handlers = [h for h in root_logger.handlers if not isinstance(h, RuntimeStatusLoggingHandler)]
+ root_logger.handlers = handlers
+
handler = RuntimeStatusLoggingHandler(self.runtime_status_update)
root_logger.addHandler(handler)
self.runtimeContext.make_fs_access = partial(CollectionFsAccess,
collection_cache=self.collection_cache)
+ validate_cluster_target(self, self.runtimeContext)
+
def arv_make_tool(self, toolpath_object, loadingContext):
if "class" in toolpath_object and toolpath_object["class"] == "CommandLineTool":
return ArvadosCommandTool(self, toolpath_object, loadingContext)
elif "class" in toolpath_object and toolpath_object["class"] == "Workflow":
return ArvadosWorkflow(self, toolpath_object, loadingContext)
+ elif "class" in toolpath_object and toolpath_object["class"] == "ExpressionTool":
+ return ArvadosExpressionTool(self, toolpath_object, loadingContext)
else:
- return cwltool.workflow.default_make_tool(toolpath_object, loadingContext)
+ raise Exception("Unknown tool %s" % toolpath_object.get("class"))
def output_callback(self, out, processStatus):
with self.workflow_eval_lock:
def start_run(self, runnable, runtimeContext):
- self.task_queue.add(partial(runnable.run, runtimeContext))
+ self.task_queue.add(partial(runnable.run, runtimeContext),
+ self.workflow_eval_lock, self.stop_polling)
def process_submitted(self, container):
with self.workflow_eval_lock:
with self.workflow_eval_lock:
j = self.processes[uuid]
logger.info("%s %s is %s", self.label(j), uuid, record["state"])
- self.task_queue.add(partial(j.done, record))
+ self.task_queue.add(partial(j.done, record),
+ self.workflow_eval_lock, self.stop_polling)
del self.processes[uuid]
def runtime_status_update(self, kind, message, detail=None):
activity statuses, for example in the RuntimeStatusLoggingHandler.
"""
with self.workflow_eval_lock:
- current = get_current_container(self.api, self.num_retries, logger)
+ current = arvados_cwl.util.get_current_container(self.api, self.num_retries, logger)
if current is None:
return
runtime_status = current.get('runtime_status', {})
if self.stop_polling.is_set():
break
with self.workflow_eval_lock:
- keys = list(self.processes.keys())
+ keys = list(self.processes)
if not keys:
remain_wait = self.poll_interval
continue
elif self.work_api == "jobs":
table = self.poll_api.jobs()
- try:
- proc_states = table.list(filters=[["uuid", "in", keys]]).execute(num_retries=self.num_retries)
- except Exception as e:
- logger.warn("Error checking states on API server: %s", e)
- remain_wait = self.poll_interval
- continue
+ pageSize = self.poll_api._rootDesc.get('maxItemsPerResponse', 1000)
- for p in proc_states["items"]:
- self.on_message({
- "object_uuid": p["uuid"],
- "event_type": "update",
- "properties": {
- "new_attributes": p
- }
- })
+ while keys:
+ page = keys[:pageSize]
+ keys = keys[pageSize:]
+ try:
+ proc_states = table.list(filters=[["uuid", "in", page]]).execute(num_retries=self.num_retries)
+ except Exception:
+ logger.exception("Error checking states on API server: %s")
+ remain_wait = self.poll_interval
+ continue
+
+ for p in proc_states["items"]:
+ self.on_message({
+ "object_uuid": p["uuid"],
+ "event_type": "update",
+ "properties": {
+ "new_attributes": p
+ }
+ })
finish_poll = time.time()
remain_wait = self.poll_interval - (finish_poll - begin_poll)
except:
for i in self.intermediate_output_collections:
try:
self.api.collections().delete(uuid=i).execute(num_retries=self.num_retries)
- except:
- logger.warn("Failed to delete intermediate output: %s", sys.exc_info()[1], exc_info=(sys.exc_info()[1] if self.debug else False))
- if sys.exc_info()[0] is KeyboardInterrupt or sys.exc_info()[0] is SystemExit:
+ except Exception:
+ logger.warning("Failed to delete intermediate output: %s", sys.exc_info()[1], exc_info=(sys.exc_info()[1] if self.debug else False))
+ except (KeyboardInterrupt, SystemExit):
break
def check_features(self, obj):
"Option 'dockerOutputDirectory' must be an absolute path.")
if obj.get("class") == "http://commonwl.org/cwltool#Secrets" and self.work_api != "containers":
raise SourceLine(obj, "class", UnsupportedRequirement).makeError("Secrets not supported with --api=jobs")
- for v in obj.itervalues():
+ for v in viewvalues(obj):
self.check_features(v)
elif isinstance(obj, list):
for i,v in enumerate(obj):
num_retries=self.num_retries)
for k,v in generatemapper.items():
- if k.startswith("_:"):
- if v.type == "Directory":
+ if v.type == "Directory" and v.resolved.startswith("_:"):
continue
- if v.type == "CreateFile":
- with final.open(v.target, "wb") as f:
- f.write(v.resolved.encode("utf-8"))
+ if v.type == "CreateFile" and (k.startswith("_:") or v.resolved.startswith("_:")):
+ with final.open(v.target, "wb") as f:
+ f.write(v.resolved.encode("utf-8"))
continue
- if not k.startswith("keep:"):
+ if not v.resolved.startswith("keep:"):
raise Exception("Output source is not in keep or a literal")
- sp = k.split("/")
+ sp = v.resolved.split("/")
srccollection = sp[0][5:]
try:
reader = self.collection_cache.get(srccollection)
logger.error("Creating CollectionReader for '%s' '%s': %s", k, v, e)
raise
except IOError as e:
- logger.warn("While preparing output collection: %s", e)
+ logger.error("While preparing output collection: %s", e)
+ raise
def rewrite(fileobj):
fileobj["location"] = generatemapper.mapper(fileobj["location"]).target
adjustFileObjs(outputObj, rewrite)
with final.open("cwl.output.json", "w") as f:
- json.dump(outputObj, f, sort_keys=True, indent=4, separators=(',',': '))
+ res = str(json.dumps(outputObj, sort_keys=True, indent=4, separators=(',',': '), ensure_ascii=False))
+ f.write(res)
final.save_new(name=name, owner_uuid=self.project_uuid, storage_classes=storage_classes, ensure_unique_name=True)
def set_crunch_output(self):
if self.work_api == "containers":
- current = get_current_container(self.api, self.num_retries, logger)
+ current = arvados_cwl.util.get_current_container(self.api, self.num_retries, logger)
if current is None:
return
try:
body={
'is_trashed': True
}).execute(num_retries=self.num_retries)
- except Exception as e:
- logger.info("Setting container output: %s", e)
+ except Exception:
+ logger.exception("Setting container output")
+ return
elif self.work_api == "jobs" and "TASK_UUID" in os.environ:
self.api.job_tasks().update(uuid=os.environ["TASK_UUID"],
body={
uuid=existing_uuid,
submit_runner_ram=runtimeContext.submit_runner_ram,
name=runtimeContext.name,
- merged_map=merged_map)
+ merged_map=merged_map,
+ loadingContext=loadingContext)
tmpl.save()
# cwltool.main will write our return value to stdout.
return (tmpl.uuid, "success")
if runtimeContext.priority < 1 or runtimeContext.priority > 1000:
raise Exception("--priority must be in the range 1..1000.")
+ if self.should_estimate_cache_size:
+ visited = set()
+ estimated_size = [0]
+ def estimate_collection_cache(obj):
+ if obj.get("location", "").startswith("keep:"):
+ m = pdh_size.match(obj["location"][5:])
+ if m and m.group(1) not in visited:
+ visited.add(m.group(1))
+ estimated_size[0] += int(m.group(2))
+ visit_class(job_order, ("File", "Directory"), estimate_collection_cache)
+ runtimeContext.collection_cache_size = max(((estimated_size[0]*192) // (1024*1024))+1, 256)
+ self.collection_cache.set_cap(runtimeContext.collection_cache_size*1024*1024)
+
+ logger.info("Using collection cache size %s MiB", runtimeContext.collection_cache_size)
+
runnerjob = None
if runtimeContext.submit:
# Submit a runner job to run the workflow for us.
if self.work_api == "containers":
- if tool.tool["class"] == "CommandLineTool" and runtimeContext.wait:
+ if tool.tool["class"] == "CommandLineTool" and runtimeContext.wait and (not runtimeContext.always_submit_runner):
runtimeContext.runnerjob = tool.tool["id"]
- runnerjob = tool.job(job_order,
- self.output_callback,
- runtimeContext).next()
else:
- runnerjob = RunnerContainer(self, tool, job_order, runtimeContext.enable_reuse,
+ tool = RunnerContainer(self, tool, loadingContext, runtimeContext.enable_reuse,
self.output_name,
self.output_tags,
submit_runner_ram=runtimeContext.submit_runner_ram,
intermediate_output_ttl=runtimeContext.intermediate_output_ttl,
merged_map=merged_map,
priority=runtimeContext.priority,
- secret_store=self.secret_store)
+ secret_store=self.secret_store,
+ collection_cache_size=runtimeContext.collection_cache_size,
+ collection_cache_is_default=self.should_estimate_cache_size)
elif self.work_api == "jobs":
- runnerjob = RunnerJob(self, tool, job_order, runtimeContext.enable_reuse,
+ tool = RunnerJob(self, tool, loadingContext, runtimeContext.enable_reuse,
self.output_name,
self.output_tags,
submit_runner_ram=runtimeContext.submit_runner_ram,
"state": "RunningOnClient"}).execute(num_retries=self.num_retries)
logger.info("Pipeline instance %s", self.pipeline["uuid"])
- if runnerjob and not runtimeContext.wait:
- submitargs = runtimeContext.copy()
- submitargs.submit = False
- runnerjob.run(submitargs)
+ if runtimeContext.cwl_runner_job is not None:
+ self.uuid = runtimeContext.cwl_runner_job.get('uuid')
+
+ jobiter = tool.job(job_order,
+ self.output_callback,
+ runtimeContext)
+
+ if runtimeContext.submit and not runtimeContext.wait:
+ runnerjob = next(jobiter)
+ runnerjob.run(runtimeContext)
return (runnerjob.uuid, "success")
- current_container = get_current_container(self.api, self.num_retries, logger)
- if current:
+ current_container = arvados_cwl.util.get_current_container(self.api, self.num_retries, logger)
+ if current_container:
logger.info("Running inside container %s", current_container.get("uuid"))
self.poll_api = arvados.api('v1', timeout=runtimeContext.http_timeout)
self.task_queue = TaskQueue(self.workflow_eval_lock, self.thread_count)
- if runnerjob:
- jobiter = iter((runnerjob,))
- else:
- if runtimeContext.cwl_runner_job is not None:
- self.uuid = runtimeContext.cwl_runner_job.get('uuid')
- jobiter = tool.job(job_order,
- self.output_callback,
- runtimeContext)
-
try:
self.workflow_eval_lock.acquire()
+
# Holds the lock while this code runs and releases it when
# it is safe to do so in self.workflow_eval_lock.wait(),
# at which point on_message can update job state and
else:
logger.error("Workflow is deadlocked, no runnable processes and not waiting on any pending processes.")
break
+
+ if self.stop_polling.is_set():
+ break
+
loopperf.__enter__()
loopperf.__exit__()
except:
if sys.exc_info()[0] is KeyboardInterrupt or sys.exc_info()[0] is SystemExit:
logger.error("Interrupted, workflow will be cancelled")
+ elif isinstance(sys.exc_info()[1], WorkflowException):
+ logger.error("Workflow execution failed:\n%s", sys.exc_info()[1], exc_info=(sys.exc_info()[1] if self.debug else False))
else:
- logger.error("Execution failed: %s", sys.exc_info()[1], exc_info=(sys.exc_info()[1] if self.debug else False))
+ logger.exception("Workflow execution failed")
+
if self.pipeline:
self.api.pipeline_instances().update(uuid=self.pipeline["uuid"],
body={"state": "Failed"}).execute(num_retries=self.num_retries)
- if runnerjob and runnerjob.uuid and self.work_api == "containers":
- self.api.container_requests().update(uuid=runnerjob.uuid,
+ if runtimeContext.submit and isinstance(tool, Runner):
+ runnerjob = tool
+ if runnerjob.uuid and self.work_api == "containers":
+ self.api.container_requests().update(uuid=runnerjob.uuid,
body={"priority": "0"}).execute(num_retries=self.num_retries)
finally:
self.workflow_eval_lock.release()
if self.final_output is None:
raise WorkflowException("Workflow did not return a result.")
- if runtimeContext.submit and isinstance(runnerjob, Runner):
- logger.info("Final output collection %s", runnerjob.final_output)
+ if runtimeContext.submit and isinstance(tool, Runner):
+ logger.info("Final output collection %s", tool.final_output)
else:
if self.output_name is None:
self.output_name = "Output of %s" % (shortname(tool.tool["id"]))
projects / arvados.git / blobdiff