def process_pixel_log(log_path, fast=False):
"""Process an hourly pixel log file.
Extract data from raw hourly log and aggregate it and report it. Also
depending on the specific date and options, aggregate and report the day
and month. Setting fast=True is appropriate for backfilling as it
eliminates reduntant steps.
"""
if log_path.endswith('/*'):
log_dir = log_path[:-len('/*')]
date_fields = os.path.basename(log_dir).split('.', 1)[0].split('-')
else:
date_fields = os.path.basename(log_path).split('.', 1)[0].split('-')
year, month, day, hour = (int(i) for i in date_fields)
hour_date = '%s-%02d-%02d-%02d' % (year, month, day, hour)
day_date = '%s-%02d-%02d' % (year, month, day)
month_date = '%s-%02d' % (year, month)
# All logs from this day use the same jobflow
jobflow_name = 'Traffic Processing (%s)' % day_date
output_path = os.path.join(PROCESSED_DIR, 'hour', hour_date)
extract_hour(emr_connection, jobflow_name, log_path, output_path,
log_uri=AWS_LOG_DIR)
input_path = os.path.join(PROCESSED_DIR, 'hour', hour_date)
output_path = os.path.join(AGGREGATE_DIR, hour_date)
aggregate_interval(emr_connection, jobflow_name, input_path, output_path,
log_uri=AWS_LOG_DIR)
if not fast:
report_interval(hour_date)
if hour == 23 or (not fast and (hour == 0 or hour % 4 == 3)):
# Don't aggregate and report day on every hour
input_path = os.path.join(PROCESSED_DIR, 'hour', '%s-*' % day_date)
output_path = os.path.join(AGGREGATE_DIR, day_date)
aggregate_interval(emr_connection, jobflow_name, input_path,
output_path, log_uri=AWS_LOG_DIR)
if not fast:
report_interval(day_date)
if hour == 23:
# Special tasks for final hour of the day
input_path = os.path.join(PROCESSED_DIR, 'hour', '%s-*' % day_date)
output_path = os.path.join(PROCESSED_DIR, 'day', day_date)
coalesce_interval(emr_connection, jobflow_name, input_path,
output_path, log_uri=AWS_LOG_DIR)
terminate_jobflow(emr_connection, jobflow_name)
if not fast:
aggregate_month(month_date)
report_interval(month_date)
def process_pixel_log(log_path, fast=False):
"""Process an hourly pixel log file.
Extract data from raw hourly log and aggregate it and report it. Also
depending on the specific date and options, aggregate and report the day
and month. Setting fast=True is appropriate for backfilling as it
eliminates reduntant steps.
"""
if log_path.endswith('/*'):
log_dir = log_path[:-len('/*')]
date_fields = os.path.basename(log_dir).split('.', 1)[0].split('-')
else:
date_fields = os.path.basename(log_path).split('.', 1)[0].split('-')
year, month, day, hour = (int(i) for i in date_fields)
hour_date = '%s-%02d-%02d-%02d' % (year, month, day, hour)
day_date = '%s-%02d-%02d' % (year, month, day)
month_date = '%s-%02d' % (year, month)
# All logs from this day use the same jobflow
jobflow_name = 'Traffic Processing (%s)' % day_date
output_path = os.path.join(PROCESSED_DIR, 'hour', hour_date)
extract_hour(emr_connection,
jobflow_name,
log_path,
output_path,
log_uri=AWS_LOG_DIR)
input_path = os.path.join(PROCESSED_DIR, 'hour', hour_date)
output_path = os.path.join(AGGREGATE_DIR, hour_date)
aggregate_interval(emr_connection,
jobflow_name,
input_path,
output_path,
log_uri=AWS_LOG_DIR)
if not fast:
report_interval(hour_date)
if hour == 23 or (not fast and (hour == 0 or hour % 4 == 3)):
# Don't aggregate and report day on every hour
input_path = os.path.join(PROCESSED_DIR, 'hour', '%s-*' % day_date)
output_path = os.path.join(AGGREGATE_DIR, day_date)
aggregate_interval(emr_connection,
jobflow_name,
input_path,
output_path,
log_uri=AWS_LOG_DIR)
if not fast:
report_interval(day_date)
if hour == 23:
# Special tasks for final hour of the day
input_path = os.path.join(PROCESSED_DIR, 'hour', '%s-*' % day_date)
output_path = os.path.join(PROCESSED_DIR, 'day', day_date)
coalesce_interval(emr_connection,
jobflow_name,
input_path,
output_path,
log_uri=AWS_LOG_DIR)
terminate_jobflow(emr_connection, jobflow_name)
if not fast:
aggregate_month(month_date)
report_interval(month_date)