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athena_query.py
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import boto3
import argparse
import numpy as np
import pandas as pd
parser = argparse.ArgumentParser(description='Get query args and AWS credentials.')
parser.add_argument('-p', '--profile', default='default', metavar='',
help='Name of the AWS profile to use (default="default").')
parser.add_argument('region', help='Name of AWS region.')
parser.add_argument('database', help='Name of Athena Database containing the table to query.')
parser.add_argument('workgroup', help='Name of Athena workgroup.')
parser.add_argument('output_location', help='S3 location where to save query results.')
parser.add_argument('ramin', type=float, help='Minimum of ra range to be queried.')
parser.add_argument('ramax', type=float, help='Maximum of ra range to be queried.')
parser.add_argument('decmin', type=float, help='Minimum of dec range to be queried.')
parser.add_argument('decmax', type=float, help='Maximum of dec range to be queried.')
parser.add_argument('radius', type=float, help='Radius used to determine the zone to be searched.')
parser.add_argument('-l', '--querylife', default=10, type=int, metavar='',
help='Maximum number of seconds query should be allowed to run before stopping/cancelling (default=10).')
parser.add_argument('-w', '--wait', default=0.1, type=int, metavar='',
help='Time to wait between checks to see if a query is still running (default=0.1 seconds).')
args = parser.parse_args()
assert 0 <= args.ramin <= 360, '0<= RA min <= 360.'
assert 0 <= args.ramax <= 360, '0<= RA max <= 360.'
assert 0 <= args.decmin <= 360, '0<= DEC min <= 360.'
assert 0 <= args.decmax <= 360, '0<= DEC max <= 360.'
assert args.radius > 0, 'Radius must be greater than 0.'
assert args.ramin <= args.ramax, 'RA min must be less than or equal to RA max.'
assert args.decmin <= args.decmax, 'DEC min must be less than or equal to DEC max.'
ra_partitions = [
'0<=ra<36',
'36<=ra<72',
'72<=ra<108',
'108<=ra<144',
'144<=ra<180',
'180<=ra<216',
'216<=ra<252',
'252<=ra<288',
'288<=ra<324',
'324<=ra<=360'
]
def get_min_max_zoneids(dec, radius):
zoneHeight = 30.0/3600.0
min_zoneid = np.floor((dec - radius + 90.0) / zoneHeight)
max_zoneid = np.floor((dec + radius + 90.0) / zoneHeight)
return (min_zoneid, max_zoneid)
def get_ra_partition_index(ra_value):
ra_factor = 36
return int((ra_value/ra_factor))
if __name__ == '__main__':
# ==============================
# query 1: create external table
# query 2: select data
# query 3: delete external table
# ==============================
sess = boto3.Session(profile_name=args.profile,
region_name=args.region)
athena_client = sess.client('athena')
s3_client = sess.client('s3')
#s3://trossbach-gphoton-bucket/athena/results/13b94fee-5e47-46cc-8b15-6b1c08e6311f.csv
min_zoneid, max_zoneid = get_min_max_zoneids(args.decmin, args.radius)
min_ra_partition_index = get_ra_partition_index(args.ramin)
max_ra_partition_index = get_ra_partition_index(args.ramax)
print('min: {}, max: {}'.format(min_ra_partition_index, max_ra_partition_index))
# endpoint of ra range is not inclusive, except for the last range (i.e. 324<=ra<=360)
if min_ra_partition_index == max_ra_partition_index:
if min_ra_partition_index == len(ra_partitions):
min_ra_partition_index -= 1
selected_ra_partitions = ra_partitions[min_ra_partition_index]
else:
if args.ramax < 360:
max_ra_partition_index += 1
selected_ra_partitions = ra_partitions[min_ra_partition_index:max_ra_partition_index]
queries = {
'create': '''
CREATE EXTERNAL TABLE gPhoton (
zoneID INT,
time BIGINT,
cx DOUBLE,
cy DOUBLE,
cz DOUBLE,
x DOUBLE,
y DOUBLE,
xa INT,
ya INT,
q INT,
xi DOUBLE,
eta DOUBLE,
ra DOUBLE,
dec DOUBLE,
flag TINYINT
) STORED AS PARQUET
LOCATION 's3://trossbach-gphoton-bucket/{}/{}'
tblproperties ("parquet.compress"="SNAPPY")
''',
'select': '''
SELECT COUNT(*)
FROM gPhoton
WHERE ra BETWEEN {} AND {};
''',
'delete': '''
DROP TABLE `gphoton`;
'''
}
query_args = {
'select': (args.ramin, args.ramax),
'delete': (None,)
}
execution_ids = []
for zoneid in range(min_zoneid, max_zoneid):
for ra_partition in selected_ra_partitions:
query_args['create'] = (zoneid, ra_partition)
for query in ['create', 'select', 'delete']:
response = athena_client.start_query_execution(
QueryString=queries[query].format(*query_args[query].values()),
QueryExecutionContext={
'Database': args.database
},
ResultConfiguration={
'OutputLocation': args.output_location
},
WorkGroup=args.workgroup
)
rsp = athena_client.get_query_execution(QueryExecutionId=response['QueryExecutionId'])
succeeded_query = True if rsp['QueryExecution']['Status']['State'] == 'SUCCEEDED' else False
num_sec_query_has_been_running = 0
# check to see if the query has succeeded
while not succeeded_query:
if num_sec_query_has_been_running >= args.querylife:
print('QUERY CANCELLED: Query {} has been running for ~{} seconds.'.format(response['QueryExecutionId'],
num_sec_query_has_been_running))
_ = athena_client.stop_query_execution(QueryExecutionId=response['QueryExecutionId'])
break
if num_sec_query_has_been_running % 60 == 0 and num_sec_query_has_been_running:
duration = int(num_sec_query_has_been_running/60)
word = 'minutes' if duration > 1 else 'minute'
print('...Query has been running for ~{} {}.'.format(duration, word))
# wait until query has succeeded to start the next query
if num_sec_query_has_been_running + args.wait > args.querylife:
sleep_time = args.querylife - num_sec_query_has_been_running
else:
sleep_time = args.wait
time.sleep(sleep_time)
num_sec_query_has_been_running += sleep_time
rsp = athena_client.get_query_execution(QueryExecutionId=response['QueryExecutionId'])
succeeded_query = True if rsp['QueryExecution']['Status']['State'] == 'SUCCEEDED' else False
if query == 'SELECT':
execution_ids.append(response['QueryExecutionId'])
# accumulate the CSVs from the different SELECT statements
dfs = []
for cnt, execution_id in enumerate(execution_ids):
path_to_csv = s3_path + execution_id + '.csv'
s3_client.download_file(bucket, path_to_csv, where_to_save)
dfs.append(pd.read_csv(where_to_save))
df = pd.concat(dfs)