theodolite.py

#!/usr/bin/env python

import argparse
from lib.cli_parser import benchmark_parser
import logging  # logging
import os
import sys
from strategies.config import ExperimentConfig
import strategies.strategies.domain_restriction.lower_bound_strategy as lower_bound_strategy
import strategies.strategies.domain_restriction.no_lower_bound_strategy as no_lower_bound_strategy
import strategies.strategies.search.check_all_strategy as check_all_strategy
import strategies.strategies.search.linear_search_strategy as linear_search_strategy
import strategies.strategies.search.binary_search_strategy as binary_search_strategy
from strategies.experiment_execution import ExperimentExecutor
import strategies.subexperiment_execution.subexperiment_executor as subexperiment_executor
import strategies.subexperiment_evaluation.subexperiment_evaluator as subexperiment_evaluator


def load_variables():
    """Load the CLI variables given at the command line"""
    print('Load CLI variables')
    parser = benchmark_parser("Run theodolite benchmarking")
    args = parser.parse_args()
    print(args)
    if args.uc is None or args.loads is None or args.instances_list is None:
        print('The options --uc, --loads and --instances are mandatory.')
        print('Some might not be set!')
        sys.exit(1)
    return args


def main(uc, loads, instances_list, partitions, cpu_limit, memory_limit,
         commit_ms, duration, domain_restriction, search_strategy,
         prometheus_base_url ,reset, reset_only, namespace):

    print(f"Domain restriction of search space activated: {domain_restriction}")
    print(f"Chosen search strategy: {search_strategy}")

    if os.path.exists("exp_counter.txt"):
        with open("exp_counter.txt", mode="r") as read_stream:
            exp_id = int(read_stream.read())
    else:
        exp_id = 0

    # Store metadata
    separator = ","
    lines = [
            f"UC={uc}\n",
            f"DIM_VALUES={separator.join(map(str, loads))}\n",
            f"REPLICAS={separator.join(map(str, instances_list))}\n",
            f"PARTITIONS={partitions}\n",
            f"CPU_LIMIT={cpu_limit}\n",
            f"MEMORY_LIMIT={memory_limit}\n",
            f"KAFKA_STREAMS_COMMIT_INTERVAL_MS={commit_ms}\n",
            f"EXECUTION_MINUTES={duration}\n",
            f"DOMAIN_RESTRICTION={domain_restriction}\n",
            f"SEARCH_STRATEGY={search_strategy}"
            ]
    with open(f"exp{exp_id}_uc{uc}_meta.txt", "w") as stream:
        stream.writelines(lines)

    with open("exp_counter.txt", mode="w") as write_stream:
        write_stream.write(str(exp_id + 1))

    # domain restriction
    if domain_restriction:
        # domain restriction + linear-search
        if search_strategy == "linear-search":
            print(f"Going to execute at most {len(loads)+len(instances_list)-1} subexperiments in total..")
            experiment_config = ExperimentConfig(
                use_case=uc,
                exp_id=exp_id,
                dim_values=loads,
                replicass=instances_list,
                partitions=partitions,
                cpu_limit=cpu_limit,
                memory_limit=memory_limit,
                kafka_streams_commit_interval_ms=commit_ms,
                execution_minutes=duration,
                domain_restriction_strategy=lower_bound_strategy,
                search_strategy=linear_search_strategy,
                subexperiment_executor=subexperiment_executor,
                subexperiment_evaluator=subexperiment_evaluator)
        # domain restriction + binary-search
        elif search_strategy == "binary-search":
            experiment_config = ExperimentConfig(
                use_case=uc,
                exp_id=exp_id,
                dim_values=loads,
                replicass=instances_list,
                partitions=partitions,
                cpu_limit=cpu_limit,
                memory_limit=memory_limit,
                kafka_streams_commit_interval_ms=commit_ms,
                execution_minutes=duration,
                domain_restriction_strategy=lower_bound_strategy,
                search_strategy=binary_search_strategy,
                subexperiment_executor=subexperiment_executor,
                subexperiment_evaluator=subexperiment_evaluator)
        # domain restriction + check_all
        else:
            print(f"Going to execute {len(loads)*len(instances_list)} subexperiments in total..")
            experiment_config = ExperimentConfig(
                use_case=uc,
                exp_id=exp_id,
                dim_values=loads,
                replicass=instances_list,
                partitions=partitions,
                cpu_limit=cpu_limit,
                memory_limit=memory_limit,
                kafka_streams_commit_interval_ms=commit_ms,
                execution_minutes=duration,
                domain_restriction_strategy=lower_bound_strategy,
                search_strategy=check_all_strategy,
                subexperiment_executor=subexperiment_executor,
                subexperiment_evaluator=subexperiment_evaluator)
    # no domain restriction
    else:
        # no domain restriction + linear-search
        if search_strategy == "linear-search":
            print(f"Going to execute at most {len(loads)*len(instances_list)} subexperiments in total..")
            experiment_config = ExperimentConfig(
                use_case=uc,
                exp_id=exp_id,
                dim_values=loads,
                replicass=instances_list,
                partitions=partitions,
                cpu_limit=cpu_limit,
                memory_limit=memory_limit,
                kafka_streams_commit_interval_ms=commit_ms,
                execution_minutes=duration,
                domain_restriction_strategy=no_lower_bound_strategy,
                search_strategy=linear_search_strategy,
                subexperiment_executor=subexperiment_executor,
                subexperiment_evaluator=subexperiment_evaluator)
        # no domain restriction + binary-search
        elif search_strategy == "binary-search":
            experiment_config = ExperimentConfig(
                use_case=uc,
                exp_id=exp_id,
                dim_values=loads,
                replicass=instances_list,
                partitions=partitions,
                cpu_limit=cpu_limit,
                memory_limit=memory_limit,
                kafka_streams_commit_interval_ms=commit_ms,
                execution_minutes=duration,
                domain_restriction_strategy=no_lower_bound_strategy,
                search_strategy=binary_search_strategy,
                subexperiment_executor=subexperiment_executor,
                subexperiment_evaluator=subexperiment_evaluator)
        # no domain restriction + check_all
        else:
            print(f"Going to execute {len(loads)*len(instances_list)} subexperiments in total..")
            experiment_config = ExperimentConfig(
                use_case=uc,
                exp_id=exp_id,
                dim_values=loads,
                replicass=instances_list,
                partitions=partitions,
                cpu_limit=cpu_limit,
                memory_limit=memory_limit,
                kafka_streams_commit_interval_ms=commit_ms,
                execution_minutes=duration,
                domain_restriction_strategy=no_lower_bound_strategy,
                search_strategy=check_all_strategy,
                subexperiment_executor=subexperiment_executor,
                subexperiment_evaluator=subexperiment_evaluator)

    executor = ExperimentExecutor(experiment_config)
    executor.execute()


if __name__ == '__main__':
    logging.basicConfig(level=logging.INFO)
    args = load_variables()
    main(args.uc, args.loads, args.instances_list, args.partitions, args.cpu_limit,
         args.memory_limit, args.commit_ms, args.duration,
         args.domain_restriction, args.search_strategy, args.prometheus,
         args.reset, args.reset_only, args.namespace)