import datetime
import ciso8601
import uuid
+import math
-from arvados_cwl.util import get_current_container, get_intermediate_collection_info
+import arvados_cwl.util
import ruamel.yaml as yaml
from cwltool.errors import WorkflowException
class ArvadosContainer(JobBase):
"""Submit and manage a Crunch container request for executing a CWL CommandLineTool."""
- def __init__(self, runner,
+ def __init__(self, runner, job_runtime,
builder, # type: Builder
joborder, # type: Dict[Text, Union[Dict[Text, Any], List, Text]]
make_path_mapper, # type: Callable[..., PathMapper]
):
super(ArvadosContainer, self).__init__(builder, joborder, make_path_mapper, requirements, hints, name)
self.arvrunner = runner
+ self.job_runtime = job_runtime
self.running = False
self.uuid = None
# ArvadosContainer object by CommandLineTool.job() before
# run() is called.
+ runtimeContext = self.job_runtime
+
container_request = {
"command": self.command_line,
"name": self.name,
}
runtime_constraints = {}
- if self.arvrunner.project_uuid:
- container_request["owner_uuid"] = self.arvrunner.project_uuid
+ if runtimeContext.project_uuid:
+ container_request["owner_uuid"] = runtimeContext.project_uuid
if self.arvrunner.secret_store.has_secret(self.command_line):
raise WorkflowException("Secret material leaked on command line, only file literals may contain secrets")
resources = self.builder.resources
if resources is not None:
- runtime_constraints["vcpus"] = resources.get("cores", 1)
- runtime_constraints["ram"] = resources.get("ram") * 2**20
+ runtime_constraints["vcpus"] = math.ceil(resources.get("cores", 1))
+ runtime_constraints["ram"] = math.ceil(resources.get("ram") * 2**20)
mounts = {
self.outdir: {
"kind": "tmp",
- "capacity": resources.get("outdirSize", 0) * 2**20
+ "capacity": math.ceil(resources.get("outdirSize", 0) * 2**20)
},
self.tmpdir: {
"kind": "tmp",
- "capacity": resources.get("tmpdirSize", 0) * 2**20
+ "capacity": math.ceil(resources.get("tmpdirSize", 0) * 2**20)
}
}
secret_mounts = {}
vwd = arvados.collection.Collection(api_client=self.arvrunner.api,
keep_client=self.arvrunner.keep_client,
num_retries=self.arvrunner.num_retries)
- generatemapper = NoFollowPathMapper([self.generatefiles], "", "",
+ generatemapper = NoFollowPathMapper(self.generatefiles["listing"], "", "",
separateDirs=False)
sorteditems = sorted(generatemapper.items(), None, key=lambda n: n[1].target)
keepemptydirs(vwd)
if not runtimeContext.current_container:
- runtimeContext.current_container = get_current_container(self.arvrunner.api, self.arvrunner.num_retries, logger)
- info = get_intermediate_collection_info(self.name, runtimeContext.current_container, runtimeContext.intermediate_output_ttl)
+ runtimeContext.current_container = arvados_cwl.util.get_current_container(self.arvrunner.api, self.arvrunner.num_retries, logger)
+ info = arvados_cwl.util.get_intermediate_collection_info(self.name, runtimeContext.current_container, runtimeContext.intermediate_output_ttl)
vwd.save_new(name=info["name"],
- owner_uuid=self.arvrunner.project_uuid,
+ owner_uuid=runtimeContext.project_uuid,
ensure_unique_name=True,
trash_at=info["trash_at"],
properties=info["properties"])
docker_req = {"dockerImageId": "arvados/jobs"}
container_request["container_image"] = arv_docker_get_image(self.arvrunner.api,
- docker_req,
- runtimeContext.pull_image,
- self.arvrunner.project_uuid)
+ docker_req,
+ runtimeContext.pull_image,
+ runtimeContext.project_uuid)
api_req, _ = self.get_requirement("http://arvados.org/cwl#APIRequirement")
if api_req:
runtime_req, _ = self.get_requirement("http://arvados.org/cwl#RuntimeConstraints")
if runtime_req:
if "keep_cache" in runtime_req:
- runtime_constraints["keep_cache_ram"] = runtime_req["keep_cache"] * 2**20
+ runtime_constraints["keep_cache_ram"] = math.ceil(runtime_req["keep_cache"] * 2**20)
if "outputDirType" in runtime_req:
if runtime_req["outputDirType"] == "local_output_dir":
# Currently the default behavior.
if self.timelimit is not None:
scheduling_parameters["max_run_time"] = self.timelimit
+ extra_submit_params = {}
+ if runtimeContext.submit_runner_cluster:
+ extra_submit_params["cluster_id"] = runtimeContext.submit_runner_cluster
+
container_request["output_name"] = "Output for step %s" % (self.name)
container_request["output_ttl"] = self.output_ttl
container_request["mounts"] = mounts
if runtimeContext.submit_request_uuid:
response = self.arvrunner.api.container_requests().update(
uuid=runtimeContext.submit_request_uuid,
- body=container_request
+ body=container_request,
+ **extra_submit_params
).execute(num_retries=self.arvrunner.num_retries)
else:
response = self.arvrunner.api.container_requests().create(
- body=container_request
+ body=container_request,
+ **extra_submit_params
).execute(num_retries=self.arvrunner.num_retries)
self.uuid = response["uuid"]
api_client=self.arvrunner.api,
keep_client=self.arvrunner.keep_client,
num_retries=self.arvrunner.num_retries)
- done.logtail(logc, logger.error, "%s (%s) error log:" % (self.arvrunner.label(self), record["uuid"]), maxlen=40)
+ label = self.arvrunner.label(self)
+ done.logtail(
+ logc, logger.error,
+ "%s (%s) error log:" % (label, record["uuid"]), maxlen=40)
if record["output_uuid"]:
if self.arvrunner.trash_intermediate or self.arvrunner.intermediate_output_ttl:
},
"secret_mounts": secret_mounts,
"runtime_constraints": {
- "vcpus": self.submit_runner_cores,
- "ram": 1024*1024 * self.submit_runner_ram,
+ "vcpus": math.ceil(self.submit_runner_cores),
+ "ram": 1024*1024 * (math.ceil(self.submit_runner_ram) + math.ceil(self.collection_cache_size)),
"API": True
},
"use_existing": self.enable_reuse,
"properties": {}
}
- if self.tool.tool.get("id", "").startswith("keep:"):
- sp = self.tool.tool["id"].split('/')
+ if self.embedded_tool.tool.get("id", "").startswith("keep:"):
+ sp = self.embedded_tool.tool["id"].split('/')
workflowcollection = sp[0][5:]
workflowname = "/".join(sp[1:])
workflowpath = "/var/lib/cwl/workflow/%s" % workflowname
"portable_data_hash": "%s" % workflowcollection
}
else:
- packed = packed_workflow(self.arvrunner, self.tool, self.merged_map)
+ packed = packed_workflow(self.arvrunner, self.embedded_tool, self.merged_map)
workflowpath = "/var/lib/cwl/workflow.json#main"
container_req["mounts"]["/var/lib/cwl/workflow.json"] = {
"kind": "json",
"content": packed
}
- if self.tool.tool.get("id", "").startswith("arvwf:"):
- container_req["properties"]["template_uuid"] = self.tool.tool["id"][6:33]
+ if self.embedded_tool.tool.get("id", "").startswith("arvwf:"):
+ container_req["properties"]["template_uuid"] = self.embedded_tool.tool["id"][6:33]
# --local means execute the workflow instead of submitting a container request
# --eval-timeout is the timeout for javascript invocation
# --parallel-task-count is the number of threads to use for job submission
# --enable/disable-reuse sets desired job reuse
+ # --collection-cache-size sets aside memory to store collections
command = ["arvados-cwl-runner",
"--local",
"--api=containers",
"--disable-validate",
"--eval-timeout=%s" % self.arvrunner.eval_timeout,
"--thread-count=%s" % self.arvrunner.thread_count,
- "--enable-reuse" if self.enable_reuse else "--disable-reuse"]
+ "--enable-reuse" if self.enable_reuse else "--disable-reuse",
+ "--collection-cache-size=%s" % self.collection_cache_size]
if self.output_name:
command.append("--output-name=" + self.output_name)
if self.arvrunner.project_uuid:
job_spec["owner_uuid"] = self.arvrunner.project_uuid
+ extra_submit_params = {}
+ if runtimeContext.submit_runner_cluster:
+ extra_submit_params["cluster_id"] = runtimeContext.submit_runner_cluster
+
if runtimeContext.submit_request_uuid:
response = self.arvrunner.api.container_requests().update(
uuid=runtimeContext.submit_request_uuid,
- body=job_spec
+ body=job_spec,
+ **extra_submit_params
).execute(num_retries=self.arvrunner.num_retries)
else:
response = self.arvrunner.api.container_requests().create(
- body=job_spec
+ body=job_spec,
+ **extra_submit_params
).execute(num_retries=self.arvrunner.num_retries)
self.uuid = response["uuid"]
self.arvrunner.process_submitted(self)
- logger.info("%s submitted container %s", self.arvrunner.label(self), response["uuid"])
+ logger.info("%s submitted container_request %s", self.arvrunner.label(self), response["uuid"])
def done(self, record):
try:
projects / arvados.git / blobdiff