def post(self):
if self.request.get("fsm_cleanup"):
if fsm_calculate_run_time():
self.redirect("/subset")
else:
self.response.out.write("Error calculating run time of FSM/subset")
if self.request.get("reset_fsm_count"):
for c in SSFSMSimpleCounterShard.all():
c.delete()
self.redirect('/subset')
return
if self.request.get("reset_mr_count"):
for c in SSMRSimpleCounterShard.all():
c.delete()
self.redirect('/subset')
return
if self.request.get("reset_pl_count"):
for c in SSPLSimpleCounterShard.all():
c.delete()
self.redirect('/subset')
return
if self.request.get("compute"):
engine = self.request.get("engine")
dataset = self.request.get("dataset")
user = self.request.get('user')
data = SubSetDataSet.get_by_key_name(dataset)
record = Record(engine_type=engine,
dataset=dataset,
benchmark="subset",
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 SSFSMSimpleCounterShard.all():
c.delete()
context = {}
context['user'] = str(user)
context['num_entries'] = int(data.num_entries)
fsm.startStateMachine('SubSet', [context])
self.redirect('/subset')
elif engine == "pipeline":
for c in SSPLSimpleCounterShard.all():
c.delete()
mypipeline = SubSetPipeline(data.num_entries)
mypipeline.start()
record.pipeline_id = mypipeline.pipeline_id
record.put()
self.redirect('/subset')
#self.redirect(mypipeline.base_path + "/status?root=" + mypipeline.pipeline_id)
elif engine == "mr":
for c in SSMRSimpleCounterShard.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="subset.mr.subset_mapper",
reader_spec="mapreduce.input_readers.DatastoreInputReader",
mapper_parameters={
"entity_kind": "data.subset."+kind,
"processing_rate": 500
},
mapreduce_parameters={model.MapreduceSpec.PARAM_DONE_CALLBACK:
'/subset/mr/callback'},
shard_count=shards,
queue_name="default",
)
record.mr_id = mapreduce_id
record.put()
self.redirect('/subset')
def post(self):
""" Generate data sets here """
if self.request.get("fsm_cleanup"):
if fsm_calculate_run_time():
self.redirect('/grep')
else:
self.response.out.write("Error calculating fsm/grep")
return
if self.request.get("compute"):
engine = self.request.get("engine")
dataset = self.request.get("dataset")
user = self.request.get('user')
needle = self.request.get('needle')
data = GrepDataSet.get_by_key_name(dataset)
record = Record(engine_type=engine,
dataset=dataset,
benchmark="grep",
num_entities=data.num_entries,
#shard_count=data.num_pipelines,
entries_per_pipe=data.entries_per_pipe,
user=user,
char_per_word=data.char_per_word,
state="Running")
if engine == "fsm":
record.put()
context = {}
context['user'] = str(user)
context['num_entries'] = int(data.num_entries)
context['needle'] = needle
fsm.startStateMachine('Grep', [context])
self.redirect('/grep')
elif engine == "pipeline":
mypipeline = GrepPipelineLoop(data.num_entries, needle)
mypipeline.start()
record.pipeline_id = mypipeline.pipeline_id
record.put()
self.redirect('/grep')
#self.redirect(mypipeline.base_path + "/status?root=" + mypipeline.pipeline_id)
return
elif engine == "mr":
# Why 1k each per shard or less? is this ideal?
if data.num_entries > 1000:
shards = data.num_entries/1000
shards = min(256, shards)
else: shards = 1
kind = getKindString(data.num_entries)
mapreduce_id = control.start_map(
name="Grep",
handler_spec="grep.mr.grep_mapper",
reader_spec="mapreduce.input_readers.DatastoreInputReader",
mapper_parameters={
"entity_kind": "data.grep."+kind,
"processing_rate": 500,
"needle":needle,
},
mapreduce_parameters={model.MapreduceSpec.PARAM_DONE_CALLBACK:
'/grep/mr/callback'},
shard_count=shards,
queue_name="default",
)
record.mr_id = mapreduce_id
record.put()
self.redirect('/grep')