diff options
Diffstat (limited to 'yardstick/network_services/traffic_profile/prox_binsearch.py')
| -rw-r--r-- | yardstick/network_services/traffic_profile/prox_binsearch.py | 138 |
1 files changed, 92 insertions, 46 deletions
diff --git a/yardstick/network_services/traffic_profile/prox_binsearch.py b/yardstick/network_services/traffic_profile/prox_binsearch.py index 1e926aca2..9457096c8 100644 --- a/yardstick/network_services/traffic_profile/prox_binsearch.py +++ b/yardstick/network_services/traffic_profile/prox_binsearch.py @@ -21,6 +21,7 @@ import time from yardstick.network_services.traffic_profile.prox_profile import ProxProfile from yardstick.network_services import constants +from yardstick.common import constants as overall_constants LOG = logging.getLogger(__name__) @@ -84,9 +85,14 @@ class ProxBinSearchProfile(ProxProfile): # success, the binary search will complete on an integer multiple # of the precision, rather than on a fraction of it. - theor_max_thruput = 0 + theor_max_thruput = actual_max_thruput = 0 result_samples = {} + rate_samples = {} + pos_retry = 0 + neg_retry = 0 + total_retry = 0 + ok_retry = 0 # Store one time only value in influxdb single_samples = { @@ -102,51 +108,91 @@ class ProxBinSearchProfile(ProxProfile): successful_pkt_loss = 0.0 line_speed = traffic_gen.scenario_helper.all_options.get( "interface_speed_gbps", constants.NIC_GBPS_DEFAULT) * constants.ONE_GIGABIT_IN_BITS - for test_value in self.bounds_iterator(LOG): - result, port_samples = self._profile_helper.run_test(pkt_size, duration, - test_value, - self.tolerated_loss, - line_speed) - self.curr_time = time.time() - diff_time = self.curr_time - self.prev_time - self.prev_time = self.curr_time - - if result.success: - LOG.debug("Success! Increasing lower bound") - self.current_lower = test_value - successful_pkt_loss = result.pkt_loss - samples = result.get_samples(pkt_size, successful_pkt_loss, port_samples) - - # store results with success tag in influxdb - success_samples = {'Success_' + key: value for key, value in samples.items()} - - success_samples["Success_rx_total"] = int(result.rx_total / diff_time) - success_samples["Success_tx_total"] = int(result.tx_total / diff_time) - success_samples["Success_can_be_lost"] = int(result.can_be_lost / diff_time) - success_samples["Success_drop_total"] = int(result.drop_total / diff_time) - self.queue.put(success_samples) - - # Store Actual throughput for result samples - result_samples["Result_Actual_throughput"] = \ - success_samples["Success_RxThroughput"] - else: - LOG.debug("Failure... Decreasing upper bound") - self.current_upper = test_value - samples = result.get_samples(pkt_size, successful_pkt_loss, port_samples) - - for k in samples: - tmp = samples[k] - if isinstance(tmp, dict): - for k2 in tmp: - samples[k][k2] = int(samples[k][k2] / diff_time) - - if theor_max_thruput < samples["TxThroughput"]: - theor_max_thruput = samples['TxThroughput'] - self.queue.put({'theor_max_throughput': theor_max_thruput}) - - LOG.debug("Collect TG KPIs %s %s", datetime.datetime.now(), samples) - self.queue.put(samples) + ok_retry = traffic_gen.scenario_helper.scenario_cfg["runner"].get("confirmation", 0) + for test_value in self.bounds_iterator(LOG): + pos_retry = 0 + neg_retry = 0 + total_retry = 0 + + rate_samples["MAX_Rate"] = self.current_upper + rate_samples["MIN_Rate"] = self.current_lower + rate_samples["Test_Rate"] = test_value + self.queue.put(rate_samples, True, overall_constants.QUEUE_PUT_TIMEOUT) + LOG.info("Checking MAX %s MIN %s TEST %s", + self.current_upper, self.lower_bound, test_value) + while (pos_retry <= ok_retry) and (neg_retry <= ok_retry): + + total_retry = total_retry + 1 + result, port_samples = self._profile_helper.run_test(pkt_size, duration, + test_value, + self.tolerated_loss, + line_speed) + if (total_retry > (ok_retry * 3)) and (ok_retry is not 0): + LOG.info("Failure.!! .. RETRY EXCEEDED ... decrease lower bound") + + successful_pkt_loss = result.pkt_loss + samples = result.get_samples(pkt_size, successful_pkt_loss, port_samples) + + self.current_upper = test_value + neg_retry = total_retry + elif result.success: + if (pos_retry < ok_retry) and (ok_retry is not 0): + neg_retry = 0 + LOG.info("Success! ... confirm retry") + + successful_pkt_loss = result.pkt_loss + samples = result.get_samples(pkt_size, successful_pkt_loss, port_samples) + + else: + LOG.info("Success! Increasing lower bound") + self.current_lower = test_value + + successful_pkt_loss = result.pkt_loss + samples = result.get_samples(pkt_size, successful_pkt_loss, port_samples) + + # store results with success tag in influxdb + success_samples = \ + {'Success_' + key: value for key, value in samples.items()} + + success_samples["Success_rx_total"] = int(result.rx_total) + success_samples["Success_tx_total"] = int(result.tx_total) + success_samples["Success_can_be_lost"] = int(result.can_be_lost) + success_samples["Success_drop_total"] = int(result.drop_total) + success_samples["Success_RxThroughput"] = samples["RxThroughput"] + success_samples["Success_RxThroughput_gbps"] = \ + (samples["RxThroughput"] / 1000) * ((pkt_size + 20)* 8) + LOG.info(">>>##>>Collect SUCCESS TG KPIs %s %s", + datetime.datetime.now(), success_samples) + self.queue.put(success_samples, True, overall_constants.QUEUE_PUT_TIMEOUT) + + # Store Actual throughput for result samples + actual_max_thruput = success_samples["Success_RxThroughput"] + + pos_retry = pos_retry + 1 + + else: + if (neg_retry < ok_retry) and (ok_retry is not 0): + + pos_retry = 0 + LOG.info("failure! ... confirm retry") + else: + LOG.info("Failure... Decreasing upper bound") + self.current_upper = test_value + + neg_retry = neg_retry + 1 + samples = result.get_samples(pkt_size, successful_pkt_loss, port_samples) + + if theor_max_thruput < samples["TxThroughput"]: + theor_max_thruput = samples['TxThroughput'] + self.queue.put({'theor_max_throughput': theor_max_thruput}) + + LOG.info(">>>##>>Collect TG KPIs %s %s", datetime.datetime.now(), samples) + self.queue.put(samples, True, overall_constants.QUEUE_PUT_TIMEOUT) + + LOG.info(">>>##>> Result Reached PktSize %s Theor_Max_Thruput %s Actual_throughput %s", + pkt_size, theor_max_thruput, actual_max_thruput) result_samples["Result_pktSize"] = pkt_size - result_samples["Result_theor_max_throughput"] = theor_max_thruput/(1000 * 1000) + result_samples["Result_theor_max_throughput"] = theor_max_thruput + result_samples["Result_Actual_throughput"] = actual_max_thruput self.queue.put(result_samples) |