def _get_custom_arg(str_key, str_variable_name, job_id, custom_arg_dict):
"""
Extract a value at the given key from the given dict, or return None
if not found. Attempt to read from environmental variables, if known.
"""
value = None
if str_key in custom_arg_dict:
value = custom_arg_dict[str_key]
if value is None:
if str_key in util.properties:
value = util.properties[str_key]
# treat empty strings as None
if str == type(value) and 0 == len(value):
value = None
# echo in job status and in log file
msg = 'CQLExecutionTask: {0} == {1}'.format(str_variable_name, value)
data_access.update_job_status(job_id, util.conn_string,
data_access.IN_PROGRESS, msg)
# write msg to log file
log(msg)
return value
def _get_custom_arg(str_key, str_variable_name, job_id, custom_arg_dict):
"""
Extract a value at the given key from the given dict, or return None
if not found.
"""
value = None
if str_key in custom_arg_dict:
value = custom_arg_dict[str_key]
# echo in job status and in log file
msg = '{0}: {1}'.format(str_variable_name, value)
data_access.update_job_status(job_id, util.conn_string,
data_access.IN_PROGRESS, msg)
# write msg to log file
print(msg)
return value
def run(self):
print('dependencies done; run phenotype reconciliation')
client = MongoClient(util.mongo_host, util.mongo_port)
try:
data_access.update_job_status(str(self.job), util.conn_string,
data_access.IN_PROGRESS,
"Finished Pipelines")
phenotype = data_access.query_phenotype(int(self.phenotype),
util.conn_string)
print(phenotype)
db = client[util.mongo_db]
data_access.update_job_status(str(self.job), util.conn_string,
data_access.IN_PROGRESS,
"Filtering Results")
with self.output().open('w') as outfile:
phenotype_helper.write_phenotype_results(
db, self.job, phenotype, self.phenotype, self.phenotype)
data_access.update_job_status(str(self.job), util.conn_string,
data_access.COMPLETED,
"Job completed successfully")
outfile.write("DONE!")
outfile.write('\n')
except BulkWriteError as bwe:
print(bwe.details)
data_access.update_job_status(str(self.job), util.conn_string,
data_access.WARNING,
str(bwe.details))
except Exception as ex:
traceback.print_exc(file=sys.stdout)
data_access.update_job_status(str(self.job), util.conn_string,
data_access.FAILURE, str(ex))
print(ex)
finally:
client.close()
def run(self):
log('dependencies done; run phenotype reconciliation')
client = util.mongo_client()
try:
data_access.update_job_status(str(self.job), util.conn_string,
data_access.IN_PROGRESS,
"Finished Pipelines")
phenotype = data_access.query_phenotype(int(self.phenotype),
util.conn_string)
# log(phenotype)
db = client[util.mongo_db]
data_access.update_job_status(str(self.job), util.conn_string,
data_access.IN_PROGRESS,
"Filtering Results")
stats = phenotype_stats(str(self.job), True)
intermediate_stats = phenotype_stats(str(self.job), False)
data_access.update_job_status(
str(self.job), util.conn_string,
data_access.STATS + "_INTERMEDIATE_RESULTS",
str(intermediate_stats["results"]))
data_access.update_job_status(
str(self.job), util.conn_string,
data_access.STATS + "_INTERMEDIATE_SUBJECTS",
str(intermediate_stats["subjects"]))
data_access.update_job_status(str(self.job), util.conn_string,
data_access.STATS + "_FINAL_RESULTS",
str(stats["results"]))
data_access.update_job_status(
str(self.job), util.conn_string,
data_access.STATS + "_FINAL_SUBJECTS", str(stats["subjects"]))
log("writing job stats....")
log(json.dumps(stats, indent=4))
# data_access.update_job_status(str(self.job), util.conn_string, data_access.STATS + "_CACHE_QUERY_COUNTS",
# str(util.get_cache_query_count()))
# data_access.update_job_status(str(self.job), util.conn_string,data_access.STATS + "_CACHE_COMPUTE_COUNTS",
# str(util.get_cache_compute_count()))
# data_access.update_job_status(str(self.job), util.conn_string, data_access.STATS + "_CACHE_HIT_RATIO",
# str(util.get_cache_hit_ratio()))
for k in util.properties.keys():
data_access.update_job_status(str(self.job), util.conn_string,
data_access.PROPERTIES + "_" + k,
util.properties[k])
with self.output().open('w') as outfile:
phenotype_helper.write_phenotype_results(
db, self.job, phenotype, self.phenotype, self.phenotype)
# do tuple processing now that all tasks have completed
succeeded = tuple_processor.process_tuples(
db['phenotype_results'], int(self.job))
if not succeeded:
log('*** ERROR: tuple processing failed ***')
# force all mongo writes to complete by calling fsync on the admin db, then releasing the lock
wrote_docs = False
for tries in range(1, _MAX_ATTEMPTS):
try:
with ILock(_LOCK_NAME, timeout=_LOCK_WAIT_SECS):
# only a SINGLE ClarityNLP process can execute this code at any time
# force writes to disk by locking the Mongo admin database
log('*** Job {0}: FORCING MONGO WRITES ***'.format(
self.job))
admin_db = client['admin']
fsync_result = admin_db.command('fsync', lock=True)
assert 1 == fsync_result['lockCount']
unlock_result = admin_db.command('fsyncUnlock')
assert 0 == unlock_result['lockCount']
log('*** Job {0}: ALL MONGO WRITES COMPLETED ***'.
format(self.job))
wrote_docs = True
except ILockException:
# timed out before acquiring the lock, will try again
pass
if wrote_docs:
break
if not wrote_docs:
log('Job {0} failed to lock the Mongo admin database.'.
format(self.job))
data_access.update_job_status(str(self.job), util.conn_string,
data_access.COMPLETED,
"Job completed successfully")
outfile.write("DONE!")
outfile.write('\n')
log("job {} done!".format(self.job))
except BulkWriteError as bwe:
log(bwe.details)
data_access.update_job_status(str(self.job), util.conn_string,
data_access.WARNING,
str(bwe.details))
except Exception as ex:
traceback.print_exc(file=sys.stdout)
data_access.update_job_status(str(self.job), util.conn_string,
data_access.FAILURE, str(ex))
log(ex)
finally:
client.close()
def run(self):
log('dependencies done; run phenotype reconciliation')
client = util.mongo_client()
try:
data_access.update_job_status(str(self.job), util.conn_string,
data_access.IN_PROGRESS,
"Finished Pipelines")
phenotype = data_access.query_phenotype(int(self.phenotype),
util.conn_string)
# log(phenotype)
db = client[util.mongo_db]
data_access.update_job_status(str(self.job), util.conn_string,
data_access.IN_PROGRESS,
"Filtering Results")
stats = phenotype_stats(str(self.job), True)
intermediate_stats = phenotype_stats(str(self.job), False)
data_access.update_job_status(
str(self.job), util.conn_string,
data_access.STATS + "_INTERMEDIATE_RESULTS",
str(intermediate_stats["results"]))
data_access.update_job_status(
str(self.job), util.conn_string,
data_access.STATS + "_INTERMEDIATE_SUBJECTS",
str(intermediate_stats["subjects"]))
data_access.update_job_status(str(self.job), util.conn_string,
data_access.STATS + "_FINAL_RESULTS",
str(stats["results"]))
data_access.update_job_status(
str(self.job), util.conn_string,
data_access.STATS + "_FINAL_SUBJECTS", str(stats["subjects"]))
log("writing job stats....")
log(json.dumps(stats, indent=4))
# data_access.update_job_status(str(self.job), util.conn_string, data_access.STATS + "_CACHE_QUERY_COUNTS",
# str(util.get_cache_query_count()))
# data_access.update_job_status(str(self.job), util.conn_string,data_access.STATS + "_CACHE_COMPUTE_COUNTS",
# str(util.get_cache_compute_count()))
# data_access.update_job_status(str(self.job), util.conn_string, data_access.STATS + "_CACHE_HIT_RATIO",
# str(util.get_cache_hit_ratio()))
for k in util.properties.keys():
data_access.update_job_status(str(self.job), util.conn_string,
data_access.PROPERTIES + "_" + k,
util.properties[k])
with self.output().open('w') as outfile:
phenotype_helper.write_phenotype_results(
db, self.job, phenotype, self.phenotype, self.phenotype)
data_access.update_job_status(str(self.job), util.conn_string,
data_access.COMPLETED,
"Job completed successfully")
outfile.write("DONE!")
outfile.write('\n')
log("job {} done!".format(self.job))
except BulkWriteError as bwe:
log(bwe.details)
data_access.update_job_status(str(self.job), util.conn_string,
data_access.WARNING,
str(bwe.details))
except Exception as ex:
traceback.print_exc(file=sys.stdout)
data_access.update_job_status(str(self.job), util.conn_string,
data_access.FAILURE, str(ex))
log(ex)
finally:
client.close()
def run(self):
print('dependencies done; run phenotype reconciliation')
client = MongoClient(util.mongo_host, util.mongo_port)
try:
data_access.update_job_status(str(self.job), util.conn_string, data_access.IN_PROGRESS,
"Finished Pipelines")
phenotype = data_access.query_phenotype(int(self.phenotype), util.conn_string)
print(phenotype)
db = client[util.mongo_db]
data_access.update_job_status(str(self.job), util.conn_string, data_access.IN_PROGRESS,
"Filtering Results")
stats = phenotype_stats(str(self.job), True)
intermediate_stats = phenotype_stats(str(self.job), False)
data_access.update_job_status(str(self.job), util.conn_string, data_access.STATS + "_INTERMEDIATE_RESULTS",
str(intermediate_stats["results"]))
data_access.update_job_status(str(self.job), util.conn_string, data_access.STATS + "_INTERMEDIATE_SUBJECTS",
str(intermediate_stats["subjects"]))
data_access.update_job_status(str(self.job), util.conn_string, data_access.STATS + "_FINAL_RESULTS",
str(stats["results"]))
data_access.update_job_status(str(self.job), util.conn_string, data_access.STATS + "_FINAL_SUBJECTS",
str(stats["subjects"]))
data_access.update_job_status(str(self.job), util.conn_string, data_access.STATS + "_CACHE_QUERY_COUNTS",
str(util.get_cache_query_count()))
data_access.update_job_status(str(self.job), util.conn_string, data_access.STATS + "_CACHE_COMPUTE_COUNTS",
str(util.get_cache_compute_count()))
data_access.update_job_status(str(self.job), util.conn_string, data_access.STATS + "_CACHE_HIT_RATIO",
str(util.get_cache_hit_ratio()))
for k in util.properties.keys():
data_access.update_job_status(str(self.job), util.conn_string, data_access.PROPERTIES + "_" + k,
util.properties[k])
with self.output().open('w') as outfile:
phenotype_helper.write_phenotype_results(db, self.job, phenotype, self.phenotype, self.phenotype)
data_access.update_job_status(str(self.job), util.conn_string, data_access.COMPLETED,
"Job completed successfully")
outfile.write("DONE!")
outfile.write('\n')
except BulkWriteError as bwe:
print(bwe.details)
data_access.update_job_status(str(self.job), util.conn_string, data_access.WARNING, str(bwe.details))
except Exception as ex:
traceback.print_exc(file=sys.stdout)
data_access.update_job_status(str(self.job), util.conn_string, data_access.FAILURE, str(ex))
print(ex)
finally:
client.close()