123 lines
4.8 KiB
Python
123 lines
4.8 KiB
Python
# This Source Code Form is subject to the terms of the Mozilla Public
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# License, v. 2.0. If a copy of the MPL was not distributed with this
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# file, You can obtain one at http://mozilla.org/MPL/2.0/.
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from __future__ import absolute_import, print_function, unicode_literals
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import concurrent.futures as futures
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import requests
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import requests.adapters
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import json
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import os
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import logging
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from slugid import nice as slugid
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from taskgraph.util.time import (
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current_json_time,
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json_time_from_now
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)
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logger = logging.getLogger(__name__)
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# the maximum number of parallel createTask calls to make
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CONCURRENCY = 50
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def create_tasks(taskgraph, label_to_taskid, params):
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taskid_to_label = {t: l for l, t in label_to_taskid.iteritems()}
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session = requests.Session()
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# Default HTTPAdapter uses 10 connections. Mount custom adapter to increase
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# that limit. Connections are established as needed, so using a large value
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# should not negatively impact performance.
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http_adapter = requests.adapters.HTTPAdapter(pool_connections=CONCURRENCY,
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pool_maxsize=CONCURRENCY)
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session.mount('https://', http_adapter)
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session.mount('http://', http_adapter)
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decision_task_id = os.environ.get('TASK_ID')
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# when running as an actual decision task, we use the decision task's
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# taskId as the taskGroupId. The process that created the decision task
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# helpfully placed it in this same taskGroup. If there is no $TASK_ID,
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# fall back to a slugid
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task_group_id = decision_task_id or slugid()
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scheduler_id = 'gecko-level-{}'.format(params['level'])
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with futures.ThreadPoolExecutor(CONCURRENCY) as e:
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fs = {}
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# We can't submit a task until its dependencies have been submitted.
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# So our strategy is to walk the graph and submit tasks once all
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# their dependencies have been submitted.
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#
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# Using visit_postorder() here isn't the most efficient: we'll
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# block waiting for dependencies of task N to submit even though
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# dependencies for task N+1 may be finished. If we need to optimize
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# this further, we can build a graph of task dependencies and walk
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# that.
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for task_id in taskgraph.graph.visit_postorder():
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task_def = taskgraph.tasks[task_id].task
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attributes = taskgraph.tasks[task_id].attributes
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# if this task has no dependencies, make it depend on this decision
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# task so that it does not start immediately; and so that if this loop
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# fails halfway through, none of the already-created tasks run.
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if decision_task_id and not task_def.get('dependencies'):
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task_def['dependencies'] = [decision_task_id]
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task_def['taskGroupId'] = task_group_id
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task_def['schedulerId'] = scheduler_id
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# Wait for dependencies before submitting this.
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deps_fs = [fs[dep] for dep in task_def.get('dependencies', [])
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if dep in fs]
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for f in futures.as_completed(deps_fs):
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f.result()
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fs[task_id] = e.submit(_create_task, session, task_id,
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taskid_to_label[task_id], task_def)
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# Schedule tasks as many times as task_duplicates indicates
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for i in range(1, attributes.get('task_duplicates', 1)):
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# We use slugid() since we want a distinct task id
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fs[task_id] = e.submit(_create_task, session, slugid(),
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taskid_to_label[task_id], task_def)
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# Wait for all futures to complete.
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for f in futures.as_completed(fs.values()):
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f.result()
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def _create_task(session, task_id, label, task_def):
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# create the task using 'http://taskcluster/queue', which is proxied to the queue service
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# with credentials appropriate to this job.
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# Resolve timestamps
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now = current_json_time(datetime_format=True)
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task_def = resolve_timestamps(now, task_def)
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logger.debug("Creating task with taskId {} for {}".format(task_id, label))
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res = session.put('http://taskcluster/queue/v1/task/{}'.format(task_id),
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data=json.dumps(task_def))
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if res.status_code != 200:
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try:
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logger.error(res.json()['message'])
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except:
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logger.error(res.text)
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res.raise_for_status()
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def resolve_timestamps(now, task_def):
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def recurse(val):
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if isinstance(val, list):
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return [recurse(v) for v in val]
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elif isinstance(val, dict):
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if val.keys() == ['relative-datestamp']:
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return json_time_from_now(val['relative-datestamp'], now)
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else:
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return {k: recurse(v) for k, v in val.iteritems()}
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else:
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return val
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return recurse(task_def)
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