[Findit] Added algorithm to analysis

appengine/findit/waterfall/flake/recursive_flake_pipeline.py

 # Copyright 2016 The Chromium Authors. All rights reserved.
 # Use of this source code is governed by a BSD-style license that can be
 # found in the LICENSE file.
 
 from datetime import datetime

[chanli, 2016/08/11 23:59:39]

datetime should be in a separate group

[caiw, 2016/08/13 00:09:15]

Done.

-
 from common import appengine_util
 from common import constants
 from common.pipeline_wrapper import BasePipeline
 
 from model import analysis_status
 from model.flake.master_flake_analysis import MasterFlakeAnalysis
+from model.flake.flake_swarming_task import FlakeSwarmingTask
 from waterfall.trigger_flake_swarming_task_pipeline import (
     TriggerFlakeSwarmingTaskPipeline)
 from waterfall.process_flake_swarming_task_result_pipeline import (
     ProcessFlakeSwarmingTaskResultPipeline)
 
 
 class RecursiveFlakePipeline(BasePipeline):
 
   # Arguments number differs from overridden method - pylint: disable=W0221
   def run(self, master_name, builder_name, run_build_number, step_name,
-          test_name, master_build_number, queue_name=constants.DEFAULT_QUEUE):
+          test_name, master_build_number, algo_dict,
+          queue_name=constants.DEFAULT_QUEUE):

[chanli, 2016/08/11 23:59:39]

Could you add a docstring to explain the args? For example what's the difference
between run_build_number and master_build_number?

[caiw, 2016/08/13 00:09:15]

Done.

     # Call trigger pipeline (flake style).
-    task_id = yield TriggerFlakeSwarmingTaskPipeline(master_name, builder_name,
-                          run_build_number, step_name, [test_name])
+    task_id = yield TriggerFlakeSwarmingTaskPipeline(
+        master_name, builder_name, run_build_number, step_name, [test_name])
     # Pass the trigger pipeline into a process pipeline.
     test_result_future = yield ProcessFlakeSwarmingTaskResultPipeline(
         master_name, builder_name, run_build_number,
         step_name, task_id, master_build_number, test_name)
     yield NextBuildNumberPipeline(
-        master_name, builder_name, master_build_number,
-        step_name, test_name, test_result_future, queue_name)
+        master_name, builder_name, master_build_number, run_build_number,
+        step_name, test_name, test_result_future, queue_name, algo_dict)
+
 
 class NextBuildNumberPipeline(BasePipeline):
+
   # Arguments number differs from overridden method - pylint: disable=W0221
   # Unused argument - pylint: disable=W0613
-  def run(self, master_name, builder_name, master_build_number, step_name,
-          test_name, test_result_future, queue_name):
+  def run(self, master_name, builder_name, master_build_number,
+          run_build_number, step_name, test_name, test_result_future,
+          queue_name, algo_dict):
+
     # Get MasterFlakeAnalysis success list corresponding to parameters.
     master = MasterFlakeAnalysis.Get(master_name, builder_name,
                                      master_build_number, step_name, test_name)
+
+    # Don't call another pipeline if we fail.
+    flake_swarming_task = FlakeSwarmingTask.Get(
+        master_name, builder_name, run_build_number, step_name, test_name)
+    if flake_swarming_task.status == analysis_status.ERROR:
+      return
+
     # Figure out what build_number we should call, if any
     # This is a placeholder for testing:
-    next_run = False
-    if len(master.build_numbers) < 10:
-      # TODO(caiw): Develop algorithm to optimize this.
-      next_run = min(master.build_numbers) - 10
+
+    # Get the last result.
+    last_result = master.success_rates[-1]
+    if last_result < .02 or last_result > .98:

[lijeffrey, 2016/08/11 22:22:25]

move all these values to constants at the top of the file, under the TODO that
they should be part of config.

[caiw, 2016/08/13 00:09:15]

Done.

+      algo_dict['stable_in_a_row'] += 1
+      if algo_dict['stable_in_a_row'] > 4:
+        algo_dict['stabled_out'] = True
+      algo_dict['flakes_in_a_row'] = 0
+      step_size = algo_dict['stable_in_a_row'] + 1
+    else:
+      algo_dict['flakes_in_a_row'] += 1
+      if algo_dict['flakes_in_a_row'] > 4:
+        algo_dict['flaked_out'] = True
+      algo_dict['stable_in_a_row'] = 0
+      step_size = algo_dict['flakes_in_a_row'] + 1
+    next_run = min(master.build_numbers) - step_size
+
+    if (next_run < algo_dict['last_build_number'] or
+        (algo_dict['stabled_out'] and algo_dict['flaked_out'])):
+      next_run = False

[chanli, 2016/08/11 23:59:39]

Maybe set next_run to 0 or -1 instead of False?

[caiw, 2016/08/13 00:09:15]

Done.

+
     if next_run:
+      new_algo_dict = {

[lijeffrey, 2016/08/11 22:22:25]

it looks like this is a direct copy. You can do new_algo_dict (please come up
with a better name) = copy.deepcopy(algo_dict).

Alternatively i think dict(algo_dict) should also work but you'd have to try it
and make sure they're not just references to the same dict

[caiw, 2016/08/13 00:09:15]

Done.

+          'flakes_in_a_row': algo_dict['flakes_in_a_row'],
+          'stable_in_a_row': algo_dict['stable_in_a_row'],
+          'stabled_out': algo_dict['stabled_out'],
+          'flaked_out': algo_dict['flaked_out'],
+          'last_build_number': algo_dict['last_build_number']
+      }
       pipeline_job = RecursiveFlakePipeline(
           master_name, builder_name, next_run, step_name, test_name,
-          master_build_number)
-      #pylint: disable=W0201
+          master_build_number, algo_dict=new_algo_dict)
+      # pylint: disable=W0201
       pipeline_job.target = appengine_util.GetTargetNameForModule(
           constants.WATERFALL_BACKEND)
       pipeline_job.start(queue_name=queue_name)