def test_convert_1_1_to_current(self):
"""Tests converting execution configuration 1.1 to current"""
old_dict = {
'version': '1.1',
'job_task': {
'settings': [{
'name': 'setting_1',
'value': 'value_1'
}],
'workspaces': [{
'name': 'name1',
'mode': 'ro'
}]
}
}
exe_config = ExecutionConfiguration(old_dict)
new_dict = exe_config.get_dict()
self.assertEqual(new_dict['version'], '2.0')
self.assertEqual(3, len(new_dict['tasks'])
) # Version 1.1 will auto-create pre and post tasks
self.assertEqual('main', new_dict['tasks'][1]['type'])
self.assertEqual(1, len(new_dict['tasks'][1]['settings']))
self.assertEqual('value_1',
new_dict['tasks'][1]['settings']['setting_1'])
def populate_job_configuration(apps, schema_editor):
from job.execution.configuration.json.exe_config import ExecutionConfiguration, MODE_RO, MODE_RW
from job.configuration.data.job_data import JobData
# Go through all of the job models that have job data and populate their configuration
Job = apps.get_model('job', 'Job')
ScaleFile = apps.get_model('storage', 'ScaleFile')
Workspace = apps.get_model('storage', 'Workspace')
total_count = Job.objects.all().count()
workspaces = {}
for workspace in Workspace.objects.all().iterator():
workspaces[workspace.id] = workspace
print 'Populating new configuration field for %s jobs' % str(total_count)
done_count = 0
batch_size = 1000
while done_count < total_count:
percent = (float(done_count) / float(total_count)) * 100.00
print 'Completed %s of %s jobs (%f%%)' % (done_count, total_count, percent)
batch_end = done_count + batch_size
for job in Job.objects.select_related('job_type').order_by('id')[done_count:batch_end]:
# Ignore jobs that don't have their job data populated yet
if not job.data:
continue
data = JobData(job.data)
input_file_ids = data.get_input_file_ids()
input_files = ScaleFile.objects.filter(id__in=input_file_ids).select_related('workspace').iterator()
input_workspaces = set()
for input_file in input_files:
input_workspaces.add(input_file.workspace.name)
configuration = ExecutionConfiguration()
for name in input_workspaces:
configuration.add_job_task_workspace(name, MODE_RO)
if not job.job_type.is_system:
for name in input_workspaces:
configuration.add_pre_task_workspace(name, MODE_RO)
# We add input workspaces to post task so it can perform a parse results move if requested by the
# job's results manifest
configuration.add_post_task_workspace(name, MODE_RW)
for workspace_id in data.get_output_workspace_ids():
workspace = workspaces[workspace_id]
if workspace.name not in input_workspaces:
configuration.add_post_task_workspace(workspace.name, MODE_RW)
elif job.job_type.name == 'scale-ingest':
ingest_id = data.get_property_values(['Ingest ID'])['Ingest ID']
from ingest.models import Ingest
ingest = Ingest.objects.select_related('workspace').get(id=ingest_id)
configuration.add_job_task_workspace(ingest.workspace.name, MODE_RW)
job.configuration = configuration.get_dict()
job.save()
done_count += batch_size
print 'All %s jobs completed' % str(total_count)