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