def txn():
index = random.randint(0, NUM_SHARDS - 1)
shard_name = "shard" + str(index)
counter = PLSimpleCounterShard.get_by_key_name(shard_name)
if counter is None:
counter = PLSimpleCounterShard(key_name=shard_name)
counter.count += value
counter.put()
def post(self):
if self.request.get("fsm_cleanup"):
if fsm_calculate_run_time():
self.redirect("/agg")
else:
self.response.out.write("Error calculating run time of FSM/aggregate")
if self.request.get("reset_fsm_count"):
for c in FSMSimpleCounterShard.all():
c.delete()
self.redirect('/agg')
return
if self.request.get("reset_mr_count"):
for c in MRSimpleCounterShard.all():
c.delete()
self.redirect('/agg')
return
if self.request.get("reset_pl_count"):
for c in PLSimpleCounterShard.all():
c.delete()
self.redirect('/agg')
return
if self.request.get("compute"):
engine = self.request.get("engine")
dataset = self.request.get("dataset")
user = self.request.get('user')
data = AggDataSet.get_by_key_name(dataset)
record = Record(engine_type=engine,
dataset=dataset,
benchmark="aggregate",
num_entities=data.num_entries,
entries_per_pipe=data.entries_per_pipe,
user=user,
state="Running")
if engine == "fsm":
record.put()
# reset count
for c in FSMSimpleCounterShard.all():
c.delete()
context = {}
context['user'] = str(user)
context['num_entries'] = int(data.num_entries)
fsm.startStateMachine('Aggregate', [context])
self.redirect('/agg')
elif engine == "fsm_fan_in":
""" This one uses fan in """
record.put()
# reset count
for c in FSMSimpleCounterShard.all():
c.delete()
context = {}
context['user'] = str(user)
context['num_entries'] = int(data.num_entries)
fsm.startStateMachine('Aggregate2', [context])
self.redirect('/agg')
elif engine == "pipeline":
for c in PLSimpleCounterShard.all():
c.delete()
mypipeline = AggregatePipeline(data.num_entries)
mypipeline.start()
record.pipeline_id = mypipeline.pipeline_id
record.put()
self.redirect('/agg')
#self.redirect(mypipeline.base_path + "/status?root=" + mypipeline.pipeline_id)
elif engine == "mr":
for c in MRSimpleCounterShard.all():
c.delete()
# Why 1k each per shard or less? is this ideal?
if data.num_entries > 1000: shards = data.num_entries/1000
else: shards = 1
kind = get_class(data.num_entries)
mapreduce_id = control.start_map(
name="Wordcount with just mappers",
handler_spec="aggregate.mr.aggregate_mapper",
reader_spec="mapreduce.input_readers.DatastoreInputReader",
mapper_parameters={
"entity_kind": "data.aggregate."+kind,
"processing_rate": 500
},
mapreduce_parameters={model.MapreduceSpec.PARAM_DONE_CALLBACK:
'/agg/mr/callback'},
shard_count=shards,
queue_name="default",
)
record.mr_id = mapreduce_id
record.put()
self.redirect('/agg')
