| #!/usr/bin/env python |
| |
| # Licensed to the Apache Software Foundation (ASF) under one |
| # or more contributor license agreements. See the NOTICE file |
| # distributed with this work for additional information |
| # regarding copyright ownership. The ASF licenses this file |
| # to you under the Apache License, Version 2.0 (the |
| # "License"); you may not use this file except in compliance |
| # with the License. You may obtain a copy of the License at |
| # |
| # http://www.apache.org/licenses/LICENSE-2.0 |
| # |
| # Unless required by applicable law or agreed to in writing, software |
| # distributed under the License is distributed on an "AS IS" BASIS, |
| # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. |
| # See the License for the specific language governing permissions and |
| # limitations under the License. |
| |
| import mesos |
| import random |
| import sys |
| import time |
| import os |
| import pickle |
| |
| CPUS = 1 |
| MEM = 50*1024*1024 |
| |
| config1 = [ (1,20) ] |
| |
| config2 = [ (1,20), (1,240) ] |
| |
| config = [ (50, 120), |
| (50, 120), |
| (50, 120), |
| (50, 120), |
| (50, 120), |
| (50, 120), |
| (50, 120), |
| (50, 120), |
| (50, 120), |
| (50, 120) ] |
| |
| class ScalingScheduler(mesos.Scheduler): |
| def __init__(self, master): |
| mesos.Scheduler.__init__(self) |
| self.tid = 0 |
| self.master = master |
| print self.master |
| self.running = {} |
| |
| def getFrameworkName(self, driver): |
| return "Scaling Framework" |
| |
| def getExecutorInfo(self, driver): |
| execPath = os.path.join(os.getcwd(), "scaling_exec") |
| return mesos.ExecutorInfo(execPath, "") |
| |
| def registered(self, driver, fid): |
| print "Scaling Scheduler Registered!" |
| |
| def resourceOffer(self, driver, oid, offers): |
| # Make sure the nested schedulers can actually run their tasks. |
| # if len(offers) <= len(config) and len(config) != self.tid: |
| # print "Need at least one spare agent to do this work ... exiting!" |
| # driver.stop() |
| # return |
| |
| # Farm out the schedulers! |
| tasks = [] |
| for offer in offers: |
| if len(config) != self.tid: |
| (todo, duration) = config[self.tid] |
| arg = pickle.dumps((self.master, (todo, duration))) |
| pars = {"cpus": "%d" % CPUS, "mem": "%d" % MEM} |
| task = mesos.TaskInfo(self.tid, offer.slaveId, |
| "task %d" % self.tid, pars, arg) |
| tasks.append(task) |
| self.running[self.tid] = (todo, duration) |
| self.tid += 1 |
| print "Launching (%d, %d) on agent %s" % (todo, duration, offer.slaveId) |
| driver.launchTasks(oid, tasks) |
| |
| def statusUpdate(self, driver, status): |
| # For now, we are expecting our tasks to be lost ... |
| if status.state == mesos.TASK_LOST: |
| todo, duration = self.running[status.taskId] |
| print "Finished %d todo at %d secs" % (todo, duration) |
| del self.running[status.taskId] |
| if self.tid == len(config) and len(self.running) == 0: |
| driver.stop() |
| |
| |
| if __name__ == "__main__": |
| if sys.argv[1] == "local" or sys.argv[1] == "localquiet": |
| print "Cannot do scaling experiments with 'local' or 'localquiet'!" |
| sys.exit(1) |
| |
| mesos.MesosSchedulerDriver(ScalingScheduler(sys.argv[1]), sys.argv[1]).run() |