73c1206e81
Reviewers: mferencevic, buda Reviewed By: buda Subscribers: mislav.bradac, pullbot Differential Revision: https://phabricator.memgraph.io/D988
120 lines
4.3 KiB
Python
120 lines
4.3 KiB
Python
#!/usr/bin/env python3
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# -*- coding: utf-8 -*-
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'''
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Large scale stress test. Tests only node creation.
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The idea is to run this test on machines with huge amount of memory e.g. 2TB.
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'''
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import logging
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import multiprocessing
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import random
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import time
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from collections import defaultdict
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from common import connection_argument_parser, argument_session
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def parse_args():
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'''
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Parses user arguments
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:return: parsed arguments
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'''
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parser = connection_argument_parser()
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# specific
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parser.add_argument('--worker-count', type=int,
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default=multiprocessing.cpu_count(),
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help='Number of concurrent workers.')
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parser.add_argument("--logging", default="INFO",
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choices=["INFO", "DEBUG", "WARNING", "ERROR"],
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help="Logging level")
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parser.add_argument('--vertex-count', type=int, default=100,
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help='Number of created vertices.')
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parser.add_argument('--max-property-value', type=int, default=1000,
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help='Maximum value of property - 1. A created node '
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'will have a property with random value from 0 to '
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'max_property_value - 1.')
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parser.add_argument('--create-pack-size', type=int, default=1,
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help='Number of CREATE clauses in a query')
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return parser.parse_args()
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log = logging.getLogger(__name__)
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args = parse_args()
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def create_worker(worker_id):
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'''
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Creates nodes and checks that all nodes were created.
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:param worker_id: worker id
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:return: tuple (worker_id, create execution time, time unit)
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'''
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assert args.vertex_count > 0, 'Number of vertices has to be positive int'
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generated_xs = defaultdict(int)
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create_query = ''
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with argument_session(args) as session:
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# create vertices
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start_time = time.time()
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for i in range(0, args.vertex_count):
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random_number = random.randint(0, args.max_property_value - 1)
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generated_xs[random_number] += 1
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create_query += 'CREATE (:Label_T%s {x: %s}) ' % \
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(worker_id, random_number)
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# if full back or last item -> execute query
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if (i + 1) % args.create_pack_size == 0 or \
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i == args.vertex_count - 1:
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session.run(create_query).consume()
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create_query = ''
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create_time = time.time()
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# check total count
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result_set = session.run('MATCH (n:Label_T%s) RETURN count(n) AS cnt' %
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worker_id).data()[0]
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assert result_set['cnt'] == args.vertex_count, \
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'Create vertices Expected: %s Created: %s' % \
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(args.vertex_count, result_set['cnt'])
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# check count per property value
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for i, size in generated_xs.items():
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result_set = session.run('MATCH (n:Label_T%s {x: %s}) '
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'RETURN count(n) AS cnt'
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% (worker_id, i)).data()[0]
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assert result_set['cnt'] == size, "Per x count isn't good " \
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"(Label: Label_T%s, prop x: %s" % (worker_id, i)
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return (worker_id, create_time - start_time, "s")
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def create_handler():
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'''
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Initializes processes and starts the execution.
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'''
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# instance cleanup
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with argument_session(args) as session:
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session.run("MATCH (n) DETACH DELETE n").consume()
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# concurrent create execution & tests
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with multiprocessing.Pool(args.worker_count) as p:
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for worker_id, create_time, time_unit in \
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p.map(create_worker, [i for i in range(args.worker_count)]):
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log.info('Worker ID: %s; Create time: %s%s' %
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(worker_id, create_time, time_unit))
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# check total count
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expected_total_count = args.worker_count * args.vertex_count
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total_count = session.run(
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'MATCH (n) RETURN count(n) AS cnt').data()[0]['cnt']
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assert total_count == expected_total_count, \
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'Total vertex number: %s Expected: %s' % \
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(total_count, expected_total_count)
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if __name__ == '__main__':
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logging.basicConfig(level=args.logging)
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if args.logging != "DEBUG":
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logging.getLogger("neo4j").setLevel(logging.WARNING)
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create_handler()
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