-
Notifications
You must be signed in to change notification settings - Fork 0
/
example.py
195 lines (192 loc) · 8.44 KB
/
example.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
"""
:Date: 2023-08-04
:Version: 1.0
:Authors: Patrick K. Erdelt
Performs experiment by running custom SQL queries.
"""
from bexhoma import *
from dbmsbenchmarker import *
import logging
import urllib3
import logging
import argparse
import time
from timeit import default_timer
import datetime
# queue
import redis
import subprocess
import psutil
urllib3.disable_warnings()
logging.basicConfig(level=logging.ERROR)
if __name__ == '__main__':
description = """Performs experiment by running custom SQL queries."""
# argparse
parser = argparse.ArgumentParser(description=description)
parser.add_argument('mode', help='profile the import or run the TPC-H queries', choices=['run'])
parser.add_argument('-aws', '--aws', help='fix components to node groups at AWS', action='store_true', default=False)
parser.add_argument('-dbms', help='DBMS to run the experiment on', choices=['Dummy'])
parser.add_argument('-db', '--debug', help='dump debug informations', action='store_true')
parser.add_argument('-cx', '--context', help='context of Kubernetes (for a multi cluster environment), default is current context', default=None)
parser.add_argument('-e', '--experiment', help='sets experiment code for continuing started experiment', default=None)
parser.add_argument('-m', '--monitoring', help='activates monitoring', action='store_true')
parser.add_argument('-mc', '--monitoring-cluster', help='activates monitoring for all nodes of cluster', action='store_true', default=False)
parser.add_argument('-ms', '--max-sut', help='maximum number of parallel DBMS configurations, default is no limit', default=None)
parser.add_argument('-dt', '--datatransfer', help='activates datatransfer', action='store_true', default=False)
parser.add_argument('-md', '--monitoring-delay', help='time to wait [s] before execution of the runs of a query', default=10)
parser.add_argument('-nr', '--num-run', help='number of runs per query', default=1)
parser.add_argument('-nc', '--num-config', help='number of runs per configuration', default=1)
parser.add_argument('-ne', '--num-query-executors', help='comma separated list of number of parallel clients', default="1")
parser.add_argument('-t', '--timeout', help='timeout for a run of a query', default=180)
parser.add_argument('-rr', '--request-ram', help='request ram', default='16Gi')
parser.add_argument('-rc', '--request-cpu', help='request cpus', default='4')
parser.add_argument('-rct', '--request-cpu-type', help='request node having node label cpu=', default='')
parser.add_argument('-rg', '--request-gpu', help='request number of gpus', default=1)
parser.add_argument('-rgt', '--request-gpu-type', help='request node having node label gpu=', default='a100')
parser.add_argument('-rst', '--request-storage-type', help='request persistent storage of certain type', default=None, choices=[None, '', 'local-hdd', 'shared'])
parser.add_argument('-rss', '--request-storage-size', help='request persistent storage of certain size', default='10Gi')
parser.add_argument('-rnn', '--request-node-name', help='request a specific node', default=None)
parser.add_argument('-tr', '--test-result', help='test if result fulfills some basic requirements', action='store_true', default=False)
parser.add_argument('-rcp', '--recreate-parameter', help='recreate parameter for randomized queries', default=None)
# evaluate args
args = parser.parse_args()
if args.debug:
logging.basicConfig(level=logging.DEBUG)
#logging.basicConfig(level=logging.DEBUG)
if args.debug:
logger_bexhoma = logging.getLogger('bexhoma')
logger_bexhoma.setLevel(logging.DEBUG)
logger_loader = logging.getLogger('load_data_asynch')
logger_loader.setLevel(logging.DEBUG)
# set parameter
monitoring = args.monitoring
monitoring_cluster = args.monitoring_cluster
mode = str(args.mode)
timeout = int(args.timeout)
numRun = int(args.num_run)
num_experiment_to_apply = int(args.num_config)
cpu = str(args.request_cpu)
memory = str(args.request_ram)
cpu_type = str(args.request_cpu_type)
gpu_type = str(args.request_gpu_type)
gpus = str(args.request_gpu)
request_storage_type = args.request_storage_type
request_storage_size = args.request_storage_size
request_node_name = args.request_node_name
datatransfer = args.datatransfer
test_result = args.test_result
recreate_parameter = args.recreate_parameter
# start with old experiment?
code = args.experiment
# set cluster
aws = args.aws
if aws:
cluster = clusters.aws(context=args.context)
# scale up
node_sizes = {
'auxiliary': 1,
'sut-mid': 1,
'benchmarker': 1
}
#cluster.scale_nodegroups(node_sizes)
else:
cluster = clusters.kubernetes(context=args.context)
cluster_name = cluster.contextdata['clustername']
if args.max_sut is not None:
cluster.max_sut = int(args.max_sut)
# set experiment
if code is None:
code = cluster.code
experiment = experiments.example(cluster=cluster, timeout=timeout, code=code, num_experiment_to_apply=num_experiment_to_apply, queryfile='queries.config')
#cluster.set_experiments_configfolder('experiments/example')
experiment.prometheus_interval = "10s"
experiment.prometheus_timeout = "10s"
# remove running dbms
#experiment.clean()
if mode == 'run':
pass
if monitoring:
# we want to monitor resource consumption
experiment.set_querymanagement_monitoring(numRun=numRun, delay=10, datatransfer=datatransfer)
else:
# we want to just run the queries
experiment.set_querymanagement_quicktest(numRun=numRun, datatransfer=datatransfer)
if monitoring_cluster:
# monitor all nodes of cluster (for not missing any component)
cluster.start_monitoring_cluster()
# set resources for dbms
experiment.set_resources(
requests = {
'cpu': cpu,
'memory': memory,
'gpu': 0
},
limits = {
'cpu': 0,
'memory': 0
},
nodeSelector = {
'cpu': cpu_type,
'gpu': '',
})
if request_node_name is not None:
experiment.set_resources(
nodeSelector = {
'cpu': cpu_type,
'gpu': '',
'kubernetes.io/hostname': request_node_name
})
# persistent storage
experiment.set_storage(
storageClassName = request_storage_type,
storageSize = request_storage_size,#'100Gi',
keep = True
)
cluster.start_dashboard()
cluster.start_messagequeue()
if aws:
# set node labes for components
experiment.set_nodes(
sut = 'sut',
loading = 'auxiliary',
monitoring = 'auxiliary',
benchmarking = 'auxiliary',
)
cluster.max_sut = 1 # can only run 1 in same cluster because of fixed service
# add configs
if args.dbms == "Dummy":
# Dummy DBMS
name_format = 'Dummy-{cluster}'
config = configurations.default(experiment=experiment, docker='Dummy', configuration=name_format.format(cluster=cluster_name), dialect='PostgreSQL', alias='DBMS A1')
config.loading_finished = True
# wait for necessary nodegroups to have planned size
if aws:
#cluster.wait_for_nodegroups(node_sizes)
pass
# configure number of clients per config
list_clients = args.num_query_executors.split(",")
if len(list_clients) > 0:
list_clients = [int(x) for x in list_clients]
experiment.add_benchmark_list(list_clients)
# total time of experiment
start = default_timer()
start_datetime = str(datetime.datetime.now())
print("Experiment starts at {} ({})".format(start_datetime, start))
# run workflow
experiment.work_benchmark_list()
# total time of experiment
end = default_timer()
end_datetime = str(datetime.datetime.now())
duration_experiment = end - start
print("Experiment ends at {} ({}): {}s total".format(end_datetime, end, duration_experiment))
##################
experiment.evaluate_results()
experiment.stop_benchmarker()
experiment.stop_sut()
#experiment.zip() # OOM? exit code 137
if test_result:
test_result_code = experiment.test_results()
if test_result_code == 0:
print("Test successful!")
cluster.restart_dashboard()
exit()