def main():
setupLogging()
args = parseArguments()
job_id = args.jobid
# Create the REST API client
engine_client = EngineApiClient(args.host, BASE_URL, args.port)
# Get all the buckets up to now
logging.info("Get result buckets for job " + job_id)
(http_status_code, response) = engine_client.getAllBuckets(job_id,
include_records=False,
anomaly_score_filter_value=args.anomalyScore,
normalized_probability_filter_value=args.normalizedProbability)
if http_status_code != 200:
print (http_status_code, json.dumps(response))
return
printHeader()
printBuckets(response)
if args.continue_poll:
if len(response) > 0:
next_bucket_id = int(response[-1]['id']) + 1
else:
next_bucket_id = None
while True:
# Wait POLL_INTERVAL_SECS then query for any new buckets
time.sleep(POLL_INTERVAL_SECS)
(http_status_code, response) = engine_client.getBucketsByDate(job_id=job_id,
start_date=str(next_bucket_id), end_date=None,
include_records=False,
anomaly_score_filter_value=args.anomalyScore,
normalized_probability_filter_value=args.normalizedProbability)
if http_status_code != 200:
print (http_status_code, json.dumps(response))
break
printBuckets(response)
if len(response) > 0:
next_bucket_id = int(response[-1]['id']) + 1
def main():
setupLogging()
args = parseArguments()
host = args.host
port = args.port
base_url = BASE_URL
job_id = args.jobid
# Create the REST API client
engine_client = EngineApiClient(host, base_url, port)
# Get all the buckets up to now
logging.info("Get result buckets for job " + job_id)
(http_status_code, response) = engine_client.getAllBuckets(job_id)
if http_status_code != 200:
print (http_status_code, json.dumps(response))
return
print "Date,BucketId,AnomalyScore"
for bucket in response:
print "{0},{1},{2}".format(bucket['timestamp'], bucket['id'], bucket['anomalyScore'])
if len(response) > 0:
next_bucket_id = int(response[-1]['id']) + 1
else:
next_bucket_id = None
# Wait POLL_INTERVAL_SECS then query for any new buckets
while True:
time.sleep(POLL_INTERVAL_SECS)
(http_status_code, response) = engine_client.getBucketsByDate(job_id=job_id,
start_date=str(next_bucket_id), end_date=None)
if http_status_code != 200:
print (http_status_code, json.dumps(response))
break
for bucket in response:
print "{0},{1},{2}".format(bucket['timestamp'], bucket['id'], bucket['anomalyScore'])
if len(response) > 0:
next_bucket_id = int(response[-1]['id']) + 1
def main():
args = parseArguments()
start_date = datetime(2014, 05, 18, 0, 0, 0, 0, UtcOffset())
# interval between the generated timestamps for the records
interval = timedelta(seconds=300)
if args.duration <= 0:
end_date = datetime.now(UtcOffset())
else:
duration = timedelta(hours=args.duration)
end_date = start_date + duration
job_config = '{\
"analysisConfig" : {\
"bucketSpan":3600,\
"detectors" :[\
{"fieldName":"In Discards","byFieldName":"host"},\
{"fieldName":"In Octets","byFieldName":"host"},\
{"fieldName":"Out Discards","byFieldName":"host"},\
{"fieldName":"Out Octets","byFieldName":"host"} \
]\
},\
"dataDescription" : {\
"fieldDelimiter":",",\
"timeField":"time",\
"timeFormat":"yyyy-MM-dd\'T\'HH:mm:ssXXX"\
}\
}'
engine_client = EngineApiClient(args.host, BASE_URL, args.port)
(http_status_code, response) = engine_client.createJob(job_config)
if http_status_code != 201:
print (http_status_code, json.dumps(response))
return
job_id = response['id']
print 'Job created with Id = ' + job_id
# get the csv header (the first record generated)
record_generator = generateRecords(args.file, start_date, interval, end_date)
header = ','.join(next(record_generator))
header += '\n'
count = 0
try:
# for the results
next_bucket_id = 1
print
print "Date,Anomaly Score,Max Normalized Probablility"
data = header
for record in record_generator:
# format as csv and append new line
csv = ','.join(record) + '\n'
data += csv
# print data
count += 1
if count == 100:
(http_status_code, response) = engine_client.upload(job_id, data)
if http_status_code != 202:
print (http_status_code, json.dumps(response))
break
# get the latest results...
(http_status_code, response) = engine_client.getBucketsByDate(job_id=job_id,
start_date=str(next_bucket_id), end_date=None)
if http_status_code != 200:
print (http_status_code, json.dumps(response))
break
# and print them
for bucket in response:
print "{0},{1},{2},{3}".format(bucket['timestamp'],
bucket['anomalyScore'], bucket['maxNormalizedProbability'])
if len(response) > 0:
next_bucket_id = int(response[-1]['id']) + 1
# must send the header every time
data = header
count = 0
# sleep a little while (optional this can be removed)
#time.sleep(0.1)
except KeyboardInterrupt:
print "Keyboard interrupt closing job..."
(http_status_code, response) = engine_client.close(job_id)
if http_status_code != 202:
print (http_status_code, json.dumps(response))
def main():
args = parseArguments()
start_date = datetime(2014, 05, 18, 0, 0, 0, 0, UtcOffset())
# interval between the generated timestamps for the records
interval = timedelta(seconds=300)
if args.duration <= 0:
end_date = datetime.now(UtcOffset())
else:
duration = timedelta(hours=args.duration)
end_date = start_date + duration
job_config = '{\
"analysisConfig" : {\
"bucketSpan":3600,\
"detectors" :[\
{"fieldName":"In Discards","byFieldName":"host"},\
{"fieldName":"In Octets","byFieldName":"host"},\
{"fieldName":"Out Discards","byFieldName":"host"},\
{"fieldName":"Out Octets","byFieldName":"host"} \
]\
},\
"dataDescription" : {\
"fieldDelimiter":",",\
"timeField":"time",\
"timeFormat":"yyyy-MM-dd\'T\'HH:mm:ssXXX"\
}\
}'
engine_client = EngineApiClient(args.host, BASE_URL, args.port)
(http_status_code, response) = engine_client.createJob(job_config)
if http_status_code != 201:
print(http_status_code, json.dumps(response))
return
job_id = response['id']
print 'Job created with Id = ' + job_id
# get the csv header (the first record generated)
record_generator = generateRecords(args.file, start_date, interval,
end_date)
header = ','.join(next(record_generator))
header += '\n'
count = 0
try:
# for the results
next_bucket_id = 1
print
print "Date,Bucket ID,Anomaly Score,Max Normalized Probablility"
data = header
for record in record_generator:
# format as csv and append new line
csv = ','.join(record) + '\n'
data += csv
# print data
count += 1
if count == 100:
(http_status_code,
response) = engine_client.upload(job_id, data)
if http_status_code != 202:
print(http_status_code, json.dumps(response))
break
# get the latest results...
(http_status_code, response) = engine_client.getBucketsByDate(
job_id=job_id,
start_date=str(next_bucket_id),
end_date=None)
if http_status_code != 200:
print(http_status_code, json.dumps(response))
break
# and print them
for bucket in response:
print "{0},{1},{2},{3}".format(
bucket['timestamp'], bucket['id'],
bucket['anomalyScore'],
bucket['maxNormalizedProbability'])
if len(response) > 0:
next_bucket_id = int(response[-1]['id']) + 1
# must send the header every time
data = header
count = 0
# sleep a little while (optional this can be removed)
#time.sleep(0.1)
except KeyboardInterrupt:
print "Keyboard interrupt closing job..."
(http_status_code, response) = engine_client.close(job_id)
if http_status_code != 202:
print(http_status_code, json.dumps(response))
