def cron_delete_old_bot_events():
"""Deletes very old BotEvent entites."""
count = 0
start = utils.utcnow()
try:
# Run for 4.5 minutes and schedule the cron job every 5 minutes. Running for
# 9.5 minutes (out of 10 allowed for a cron job) results in 'Exceeded soft
# private memory limit of 512 MB with 512 MB' even if this loop should be
# fairly light on memory usage.
time_to_stop = start + datetime.timedelta(seconds=int(4.5 * 60))
# Order is by key, so it is naturally ordered by bot, which means the
# operations will mainly operate on one root entity at a time.
q = BotEvent.query(default_options=ndb.QueryOptions(
keys_only=True)).filter(
BotEvent.ts <= start - _OLD_BOT_EVENTS_CUT_OFF)
more = True
cursor = None
while more:
keys, cursor, more = q.fetch_page(10, start_cursor=cursor)
ndb.delete_multi(keys)
count += len(keys)
if utils.utcnow() >= time_to_stop:
break
return count
except runtime.DeadlineExceededError:
pass
finally:
logging.info('Deleted %d entities', count)
def get_high_scores(self, request):
"""Return ordered high scores based on 1.more won 2.less guesses number"""
qo = ndb.QueryOptions(limit=request.limitation)
scoreQuery = Score.query().order(-Score.won, Score.guesses)
scoreList = scoreQuery.fetch(10, options=qo)
return ScoreForms(items=[score.to_form() for score in scoreList])
def ajax_reports():
offset = request.args.get('start', type=int)
limit = request.args.get('length', type=int)
search_term = request.args.get('search[value]')
order_index = request.args.get('order[0][column]', type=int)
order_dir = request.args.get('order[0][dir]')
fields = [
EmailReport.date_reported, EmailReport.reported_by,
EmailReport.report_type, EmailReport.subject, EmailReport.status
]
query = EmailReport.domain_query(g.domain)
total_count = query.count()
# Setup the correct ordering
order_field = EmailReport.key
if order_index > 0:
order_field = fields[order_index - 1]
if order_dir == 'desc':
order_field = -order_field
query_options = ndb.QueryOptions(limit=limit, offset=offset)
results = query.order(order_field).fetch(options=query_options,
projection=fields)
results_json = [result.to_dict() for result in results]
return jsonify({
'draw': int(request.args.get('draw')),
'recordsTotal': total_count,
'recordsFiltered': total_count,
'data': results_json
})
def removePlayers():
playerKeys = Player.query(ancestor=ndb.Key('GameStatus', 'Bball'),
default_options=ndb.QueryOptions(keys_only=True))
if playerKeys.count():
ndb.delete_multi(playerKeys)
setGameStatus(False)
return True
def list(self, request):
"""Provides list of known bots.
Deleted bots will not be listed.
"""
logging.debug('%s', request)
now = utils.utcnow()
# Disable the in-process local cache. This is important, as there can be up
# to a thousand entities loaded in memory, and this is a pure memory leak,
# as there's no chance this specific instance will need these again,
# therefore this leads to 'Exceeded soft memory limit' AppEngine errors.
q = bot_management.BotInfo.query(default_options=ndb.QueryOptions(
use_cache=False))
try:
q = bot_management.filter_dimensions(q, request.dimensions)
q = bot_management.filter_availability(
q, swarming_rpcs.to_bool(request.quarantined),
swarming_rpcs.to_bool(request.in_maintenance),
swarming_rpcs.to_bool(request.is_dead),
swarming_rpcs.to_bool(request.is_busy))
except ValueError as e:
raise endpoints.BadRequestException(str(e))
bots, cursor = datastore_utils.fetch_page(q, request.limit,
request.cursor)
return swarming_rpcs.BotList(
cursor=cursor,
death_timeout=config.settings().bot_death_timeout_secs,
items=[message_conversion.bot_info_to_rpc(bot) for bot in bots],
now=now)
def make_directed_ndb_query(self, kind_class, keys_only=False):
"""Construct an NDB query for this key range, including the scan direction.
Args:
kind_class: An ndb.Model subclass.
keys_only: bool, default False, use keys_only on Query?
Returns:
An ndb.Query instance.
Raises:
KeyRangeError: if self.direction is not in (KeyRange.ASC, KeyRange.DESC).
"""
assert issubclass(kind_class, ndb.Model)
if keys_only:
default_options = ndb.QueryOptions(keys_only=True)
else:
default_options = None
query = kind_class.query(app=self._app,
namespace=self.namespace,
default_options=default_options)
query = self.filter_ndb_query(query)
if self.__get_direction(True, False):
query = query.order(kind_class._key)
else:
query = query.order(-kind_class._key)
return query
def cron_delete_old_bot():
"""Deletes stale BotRoot entity groups."""
start = utils.utcnow()
# Run for 4.5 minutes and schedule the cron job every 5 minutes. Running for
# 9.5 minutes (out of 10 allowed for a cron job) results in 'Exceeded soft
# private memory limit of 512 MB with 512 MB' even if this loop should be
# fairly light on memory usage.
time_to_stop = start + datetime.timedelta(seconds=int(4.5 * 60))
total = 0
deleted = []
try:
q = BotRoot.query(default_options=ndb.QueryOptions(keys_only=True))
for bot_root_key in q:
# Check if it has any BotEvent left. If not, it means that the entity is
# older than _OLD_BOT_EVENTS_CUF_OFF, so the whole thing can be deleted
# now.
# In particular, ignore the fact that BotInfo may still exist, since if
# there's no BotEvent left, it's probably a broken entity or a forgotten
# dead bot.
if BotEvent.query(ancestor=bot_root_key).count(limit=1):
continue
deleted.append(bot_root_key.string_id())
# Delete the whole group. An ancestor query will retrieve the entity
# itself too, so no need to explicitly delete it.
keys = ndb.Query(ancestor=bot_root_key).fetch(keys_only=True)
ndb.delete_multi(keys)
total += len(keys)
if utils.utcnow() >= time_to_stop:
break
return total
except runtime.DeadlineExceededError:
pass
finally:
logging.info('Deleted %d entities from the following bots:\n%s', total,
', '.join(sorted(deleted)))
def get_game_props(weekday=None):
'''Return a GameProperties object for the current day of the week'''
q = GameProperties.query(default_options=ndb.QueryOptions(keys_only=True))
if weekday is None:
weekday = today().weekday()
dayKeys = q.filter(GameProperties.weekDay == weekday)
if dayKeys.count():
for dayProp in dayKeys:
try:
day = dayProp.get()
except BadValueError as e:
dayProp.delete()
continue
return day
logging.info('no properties for today, initializing to default')
day = GameProperties(
weekDay=weekday,
minNumPlayers=8,
maxNumPlayers=12,
provisionalNumPlayers=12,
# openRosterHoursPrior = DEFAULT_ROSTER_OPEN_HOURS,
# rosterStartTime = DEFAULT_ROSTER_START_TIME,
# rosterOpenTime = DEFAULT_ROSTER_OPEN_TIME,
# isGameDay = weekday in DEFAULT_GAME_DAYS
)
day.put()
return day
def yield_expired_task_to_run():
"""Yields the expired TaskToRun still marked as available."""
# The query fetches tasks that reached expiration time recently
# to avoid fetching all past tasks. It uses a large batch size
# since the entities are very small and to reduce RPC overhead.
opts = ndb.QueryOptions(batch_size=256)
now = utils.utcnow()
# The backsearch here is just to ensure that we find entities that we forgot
# about before because the cron job couldn't keep up. In practice
# expiration_ts should not be more than 1 minute old (as the cron job runs
# every minutes) but keep it high in case there's an outage.
cut_off = now - datetime.timedelta(hours=24)
q = TaskToRun.query(TaskToRun.expiration_ts < now,
TaskToRun.expiration_ts > cut_off,
default_options=opts)
total = 0
skipped = 0
try:
for task in q:
if not task.queue_number:
skipped += 1
logging.info(
'%s/%s: queue_number is None, but expiration_ts is %s.',
task.task_id, task.task_slice_index, task.expiration_ts)
# Flush it, otherwise we'll keep on looping on it.
task.expiration_ts = None
task.put()
else:
yield task
total += 1
finally:
logging.debug('Yielded %d tasks; skipped %d', total, skipped)
def yield_expired_task_to_run():
"""Yields the expired TaskToRun still marked as available."""
# The query fetches tasks that reached expiration time recently
# to avoid fetching all past tasks. It uses a large batch size
# since the entities are very small and to reduce RPC overhead.
def expire(q):
total = 0
try:
for task in q:
yield task
total += 1
finally:
logging.debug('Yielded %d tasks', total)
opts = ndb.QueryOptions(batch_size=256)
now = utils.utcnow()
# The backsearch here is just to ensure that we find entities that we forgot
# about before because the cron job couldn't keep up. In practice
# expiration_ts should not be more than 1 minute old (as the cron job runs
# every minutes) but keep it high in case there's an outage.
cut_off = now - datetime.timedelta(hours=24)
q = TaskToRun.query(TaskToRun.expiration_ts < now,
TaskToRun.expiration_ts > cut_off,
default_options=opts)
for task in expire(q):
yield task
def post(self):
# Got client ID from environ
user_id = request.environ['USER_ID']
client_id = user_id.get().detail_id
print request.json['id']
screen = Screen_Layout.get_by_id(request.json['id'])
screen.name = request.json['name']
prev_client_id = screen.client_id
print client_id
if prev_client_id != client_id: # Later this is to be changed with token.
return jsonify({"code": 400, "message": "Not authorized."})
screen.location = request.json['location']
prev_rows = screen.max_rows
prev_cols = screen.max_columns
if prev_rows != int(request.json['max_rows']) or prev_cols != int(
request.json['max_columns']):
screen.max_rows = int(request.json['max_rows'])
screen.max_columns = int(request.json['max_columns'])
# Deleting the categories of a seat after changing the screen structure.
options = ndb.QueryOptions(keys_only=True)
prev_categories = Category.query().filter(
Category.screen_id == ndb.Key('Screen_Layout',
request.json['id'])).fetch(
options=options)
ndb.delete_multi(prev_categories)
# We should add the new seat list for new seat grid and new categories for the updated Layout..
seats = []
categories = request.json['categories']
print categories
try:
for each in categories:
category = Category()
category.screen_id = ndb.Key('Screen',
int(request.json['id']))
category.name = each['name']
category.seats = each['seats']
map(lambda seat: seats.append(seat), each['seats'])
category.put(
) # Create categories for seat for a particular screen.
# Adding seats for the screen fetched from categories
screen.seats = seats
res = screen.put()
return jsonify({
"code":
200,
"id":
res.id(),
"message":
"Success changed layout and other informations."
})
except:
return jsonify({"code": 500, "message": "server error"})
return jsonify({
"code": 200,
"message": "Success changed some minor informations."
})
def nuke(self, Entity): Entity_qry = Entity.query() ent_count = 1 while ent_count > 0: qo = ndb.QueryOptions(keys_only=True) ent_count = Entity_qry.count(limit=1000, options=qo) if (ent_count): ndb.delete_multi(Entity_qry.fetch(ent_count, options=qo))
def get(self):
old_cutoff = utils.utcnow() - on_error.ERROR_TIME_TO_LIVE
items = models.Error.query(
models.Error.created_ts < old_cutoff,
default_options=ndb.QueryOptions(keys_only=True))
out = len(ndb.delete_multi(items))
self.response.headers['Content-Type'] = 'text/plain; charset=utf-8'
self.response.write(str(out))
def cron_delete_old_bot_events():
"""Deletes very old BotEvent entities."""
start = utils.utcnow()
# Run for 4.5 minutes and schedule the cron job every 5 minutes. Running for
# 9.5 minutes (out of 10 allowed for a cron job) results in 'Exceeded soft
# private memory limit of 512 MB with 512 MB' even if this loop should be
# fairly light on memory usage.
time_to_stop = start + datetime.timedelta(seconds=int(4.5 * 60))
end_ts = start - _OLD_BOT_EVENTS_CUT_OFF
more = True
cursor = None
count = 0
first_ts = None
try:
# Order is by key, so it is naturally ordered by bot, which means the
# operations will mainly operate on one root entity at a time.
q = BotEvent.query(default_options=ndb.QueryOptions(
keys_only=True)).filter(BotEvent.ts <= end_ts)
while more:
keys, cursor, more = q.fetch_page(10, start_cursor=cursor)
if not keys:
break
if not first_ts:
# Fetch the very first entity to get an idea of the range being
# processed.
while keys:
# It's possible that the query returns ndb.Key for entities that do
# not exist anymore due to an inconsistent index. Handle this
# explicitly.
e = keys[0].get()
if not e:
keys = keys[1:]
continue
first_ts = e.ts
break
ndb.delete_multi(keys)
count += len(keys)
if utils.utcnow() >= time_to_stop:
break
return count
except runtime.DeadlineExceededError:
pass
finally:
def _format_ts(t):
# datetime.datetime
return t.strftime(u'%Y-%m-%d %H:%M') if t else 'N/A'
def _format_delta(e, s):
# datetime.timedelta
return str(e - s).rsplit('.', 1)[0] if e and s else 'N/A'
logging.info(
'Deleted %d BotEvent entities; from %s\n'
'Cut off was %s; trailing by %s', count, _format_ts(first_ts),
_format_ts(end_ts), _format_delta(end_ts, first_ts))
def get_relays_for_recipient(user_id, offset, archived=False):
qo = ndb.QueryOptions(limit=10, offset=offset)
archive_clause = SentRelay.archived if archived else SentRelay.not_archived
sent_relays_iter = SentRelay.query().filter(
archive_clause == user_id, ).order(-SentRelay.timestamp).iter(
options=qo)
sent_relays = [item for item in sent_relays_iter]
logging.info('get_relay_for_recipient(%s) -> %s' %
(user_id, str(sent_relays)))
return sent_relays
def paginate(cls, *args, **kwargs):
query = cls.build_query(*args, **kwargs)
op = {}
if 'cursor' in kwargs:
op['start_cursor'] = ndb.Cursor(urlsafe=kwargs['cursor'])
query_option = ndb.QueryOptions(**op)
page_size = kwargs['per_page'] if 'per_page' in kwargs else 10
results, cursor, more = query.fetch_page(page_size,
options=query_option)
return PaginateModel(results, cursor, query_option.start_cursor, more)
def get_events_query(bot_id, order):
"""Returns an ndb.Query for most recent events in reverse chronological order.
"""
# Disable the in-process local cache. This is important, as there can be up to
# a thousand entities loaded in memory, and this is a pure memory leak, as
# there's no chance this specific instance will need these again, therefore
# this leads to 'Exceeded soft memory limit' AppEngine errors.
q = BotEvent.query(default_options=ndb.QueryOptions(use_cache=False),
ancestor=get_root_key(bot_id))
if order:
q = q.order(BotEvent.key)
return q
def _get_task_to_run_query(dimensions_hash):
"""Returns a ndb.Query of TaskToRun within this dimensions_hash queue."""
# dimensions_hash should be 32 bits but on AppEngine, which is using 32 bits
# python, it is silently upgraded to long.
assert isinstance(dimensions_hash, (int, long)), repr(dimensions_hash)
opts = ndb.QueryOptions(deadline=15)
# See _gen_queue_number() as of why << 31. This query cannot use the key
# because it is not a root entity.
return TaskToRun.query(default_options=opts).order(
TaskToRun.queue_number).filter(
TaskToRun.queue_number >= (dimensions_hash << 31),
TaskToRun.queue_number < ((dimensions_hash + 1) << 31))
def _getNameForEmail(email):
q = PlayerStatus.query(ancestor=ndb.Key('GameStatus', 'Bball'),
default_options=ndb.QueryOptions(keys_only=True))
playerKeys = q.filter(PlayerStatus.email == email.lower())
for player in playerKeys:
try:
player = player.get()
except:
continue
else:
if player and player.name:
return player.name
return None
def yield_expired_task_to_run():
"""Yields all the expired TaskToRun still marked as available."""
# The reason it is done this way as an iteration over all the pending entities
# instead of using a composite index with 'queue_number' and 'expiration_ts'
# is that TaskToRun entities are very hot and it is important to not require
# composite indexes on it. It is expected that the number of pending task is
# 'relatively low', in the orders of 100,000 entities.
#
# Use a large batch size since the entities are very small and to reduce RPC
# overhead.
opts = ndb.QueryOptions(batch_size=256)
now = utils.utcnow()
for task in TaskToRun.query(TaskToRun.queue_number > 0,
default_options=opts):
if task.expiration_ts < now:
yield task
def removePlayer(person):
q = Player.query(ancestor=ndb.Key('GameStatus', 'Bball'),
default_options=ndb.QueryOptions(keys_only=True))
# Sanitize
name, email = emailParser(person)
if (email == None):
return False, None
if not name:
name = email
playerKeys = q.filter(Player.email == email)
if playerKeys.count():
ndb.delete_multi(playerKeys)
return True, name
return False, name
def metrics_api():
keys_only = ndb.QueryOptions(keys_only=True)
meeting_subscriptions = MeetingSubscription.query().fetch()
metrics = []
for subscription in meeting_subscriptions:
data = {
'title':
subscription.title,
'subscribed':
UserSubscriptionPreferences.query(
UserSubscriptionPreferences.subscription ==
subscription.key).count(options=keys_only),
'meetings':
Meeting.query().count(options=keys_only),
}
metrics.append(data)
return json.dumps(metrics)
def removeSubscriber(email):
try:
q = Subscriber.query(ancestor=ndb.Key('Subscribers', 'Bball'),
default_options=ndb.QueryOptions(keys_only=True))
except:
return False
# Sanitize
name, email = emailParser(email)
if (email == None):
return False
playerKeys = q.filter(Subscriber.email == email)
if playerKeys.count():
ndb.delete_multi(playerKeys)
return True
return False
def _loadPlayerList(isAlist=None, onlySendEmail=False):
'''isAlist=None means return all players'''
q = PlayerStatus.query(ancestor=ndb.Key('GameStatus', 'Bball'),
default_options=ndb.QueryOptions(keys_only=True))
if isAlist is None:
playerKeys = q
else:
playerKeys = q.filter(PlayerStatus.isAlist == isAlist)
emails = []
for player in playerKeys:
try:
player = player.get()
except:
continue
else:
if player is not None and (not onlySendEmail or player.sendEmail):
emails.append(
usernameEmailType(player.name, player.email.lower()))
return emails
def getPriorityScore(email):
if (email == None):
return 0
q = PlayerStatus.query(ancestor=ndb.Key('GameStatus', 'Bball'),
default_options=ndb.QueryOptions(keys_only=True))
playerKeys = q.filter(PlayerStatus.email == email)
if not playerKeys.count():
return 0
else:
for player in playerKeys:
try:
player = player.get()
except:
continue
return player.priorityScore
def delete_old(entity):
key_to_delete = None
if entity.key.parent():
# It is a TaskRequestShard, it is very old.
key_to_delete = entity.key.parent()
elif not task_pack.request_key_to_result_summary_key(entity.key).get(
use_cache=False, use_memcache=False):
# There's a TaskRequest without TaskResultSummary, delete it.
key_to_delete = entity.key
if key_to_delete:
logging.info('Deleting %s: %s', entity.task_id, key_to_delete)
total = 1
qo = ndb.QueryOptions(keys_only=True)
for k in ndb.Query(default_options=qo, ancestor=key_to_delete):
yield operation.db.Delete(k)
total += 1
yield operation.db.Delete(key_to_delete)
logging.info('Deleted %d entities', total)
def make_ascending_ndb_query(self, kind_class, keys_only=False):
"""Construct an NDB query for this key range, without the scan direction.
Args:
kind_class: An ndb.Model subclass.
keys_only: bool, default False, query only for keys.
Returns:
An ndb.Query instance.
"""
assert issubclass(kind_class, ndb.Model)
if keys_only:
default_options = ndb.QueryOptions(keys_only=True)
else:
default_options = None
query = kind_class.query(app=self._app,
namespace=self.namespace,
default_options=default_options)
query = self.filter_ndb_query(query)
query = query.order(kind_class._key)
return query
def get(self):
qo = ndb.QueryOptions(keys_only=True)
min_max_params = {'price': 'price', 'bed': 'bedrooms', 'bath': 'bathrooms'}
query_sets = []
#Should have just used redis :p
for p in min_max_params:
q = Listing.query()
add_to_sets = False
try:#Will only fail if self.request.get("max_" + p) is not an int
max_param = int(self.request.get("max_" + p))
q = q.filter(getattr(Listing, min_max_params[p]) <= max_param)
add_to_sets = True
except:
pass
try:#Will only fail if self.request.get("max_" + p) is not an int
min_param = int(self.request.get("min_" + p))
q = q.filter(getattr(Listing, min_max_params[p]) >= min_param)
add_to_sets = True
except:
pass
if add_to_sets:
query_sets = query_sets + [set(q.fetch(keys_only=True))]
if len(query_sets):
valid_buildings = ndb.get_multi(list(set.intersection(*query_sets)))
else:
valid_buildings = Listing.query().fetch()
all_features = []
for b in valid_buildings:
all_features = all_features + [Feature(geometry=Point((b.lat, b.lng)),
properties={"id": b.listing_id,
"price": b.price,
"street": b.street,
"bedrooms": b.bedrooms,
"bathrooms": b.bathrooms,
"sq_ft": b.sq_ft
})]
self.write((FeatureCollection(all_features)))
def getOrCreatePlayerStatus(name, email):
'''Get a player with email matching "email". If none is found,
create a new entry.'''
q = PlayerStatus.query(ancestor=ndb.Key('GameStatus', 'Bball'),
default_options=ndb.QueryOptions(keys_only=True))
playerKeys = q.filter(PlayerStatus.email == email)
if not playerKeys.count():
player = PlayerStatus(parent=ndb.Key('GameStatus', 'Bball'),
name=name,
email=email,
numSignups=0,
numEarlySignups=0,
lastSignup=today(),
gamesPlayed=0,
gamesPlayedM=0,
gamesPlayedW=0,
gamesPlayedF=0,
lastGame=None,
gamesCut=0,
lastCut=None,
averageSignupTime=0.0,
priorityScore=0,
isAlist=False,
sendEmail=True)
player.put()
return player
else:
for playerKey in playerKeys:
try:
player = playerKey.get()
except BadValueError:
continue
return player
def yield_next_available_task_to_dispatch(bot_dimensions, deadline):
"""Yields next available (TaskRequest, TaskToRun) in decreasing order of
priority.
Once the caller determines the task is suitable to execute, it must use
reap_task_to_run(task.key) to mark that it is not to be scheduled anymore.
Performance is the top most priority here.
Arguments:
- bot_dimensions: dimensions (as a dict) defined by the bot that can be
matched.
- deadline: UTC timestamp (as an int) that the bot must be able to
complete the task by. None if there is no such deadline.
"""
# List of all the valid dimensions hashed.
accepted_dimensions_hash = frozenset(
_hash_dimensions(utils.encode_to_json(i))
for i in _powerset(bot_dimensions))
now = utils.utcnow()
broken = 0
cache_lookup = 0
expired = 0
hash_mismatch = 0
ignored = 0
no_queue = 0
real_mismatch = 0
too_long = 0
total = 0
# Be very aggressive in fetching the largest amount of items as possible. Note
# that we use the default ndb.EVENTUAL_CONSISTENCY so stale items may be
# returned. It's handled specifically.
# - 100/200 gives 2s~40s of query time for 1275 items.
# - 250/500 gives 2s~50s of query time for 1275 items.
# - 50/500 gives 3s~20s of query time for 1275 items. (Slower but less
# variance). Spikes in 20s~40s are rarer.
# The problem here are:
# - Outliers, some shards are simply slower at executing the query.
# - Median time, which we should optimize.
# - Abusing batching will slow down this query.
#
# TODO(maruel): Measure query performance with stats_framework!!
# TODO(maruel): Use fetch_page_async() + ndb.get_multi_async() +
# memcache.get_multi_async() to do pipelined processing. Should greatly reduce
# the effect of latency on the total duration of this function. I also suspect
# using ndb.get_multi() will return fresher objects than what is returned by
# the query.
opts = ndb.QueryOptions(batch_size=50, prefetch_size=500, keys_only=True)
try:
# Interestingly, the filter on .queue_number>0 is required otherwise all the
# None items are returned first.
q = TaskToRun.query(default_options=opts).order(
TaskToRun.queue_number).filter(TaskToRun.queue_number > 0)
for task_key in q:
duration = (utils.utcnow() - now).total_seconds()
if duration > 40.:
# Stop searching after too long, since the odds of the request blowing
# up right after succeeding in reaping a task is not worth the dangling
# task request that will stay in limbo until the cron job reaps it and
# retry it. The current handlers are given 60s to complete. By using
# 40s, it gives 20s to complete the reaping and complete the HTTP
# request.
return
total += 1
# Verify TaskToRun is what is expected. Play defensive here.
try:
validate_to_run_key(task_key)
except ValueError as e:
logging.error(str(e))
broken += 1
continue
# integer_id() == dimensions_hash.
if task_key.integer_id() not in accepted_dimensions_hash:
hash_mismatch += 1
continue
# Do this after the basic weeding out but before fetching TaskRequest.
if _lookup_cache_is_taken(task_key):
cache_lookup += 1
continue
# Ok, it's now worth taking a real look at the entity.
task = task_key.get(use_cache=False)
# DB operations are slow, double check memcache again.
if _lookup_cache_is_taken(task_key):
cache_lookup += 1
continue
# It is possible for the index to be inconsistent since it is not executed
# in a transaction, no problem.
if not task.queue_number:
no_queue += 1
continue
# It expired. A cron job will cancel it eventually. Since 'now' is saved
# before the query, an expired task may still be reaped even if
# technically expired if the query is very slow. This is on purpose so
# slow queries do not cause exagerate expirations.
if task.expiration_ts < now:
expired += 1
continue
# The hash may have conflicts. Ensure the dimensions actually match by
# verifying the TaskRequest. There's a probability of 2**-31 of conflicts,
# which is low enough for our purpose. The reason use_cache=False is
# otherwise it'll create a buffer bloat.
request = task.request_key.get(use_cache=False)
if not match_dimensions(request.properties.dimensions,
bot_dimensions):
real_mismatch += 1
continue
# If the bot has a deadline, don't allow it to reap the task unless it can
# be completed before the deadline. We have to assume the task takes the
# theoretical maximum amount of time possible, which is governed by
# execution_timeout_secs. An isolated task's download phase is not subject
# to this limit, so we need to add io_timeout_secs. When a task is
# signalled that it's about to be killed, it receives a grace period as
# well. grace_period_secs is given by run_isolated to the task execution
# process, by task_runner to run_isolated, and by bot_main to the
# task_runner. Lastly, add a few seconds to account for any overhead.
if deadline is not None:
if not request.properties.execution_timeout_secs:
# Task never times out, so it cannot be accepted.
too_long += 1
continue
max_task_time = (utils.time_time() +
request.properties.execution_timeout_secs +
(request.properties.io_timeout_secs or 600) +
3 *
(request.properties.grace_period_secs or 30) +
10)
if deadline <= max_task_time:
too_long += 1
continue
# It's a valid task! Note that in the meantime, another bot may have
# reaped it.
yield request, task
ignored += 1
finally:
duration = (utils.utcnow() - now).total_seconds()
logging.info(
'%d/%s in %5.2fs: %d total, %d exp %d no_queue, %d hash mismatch, '
'%d cache negative, %d dimensions mismatch, %d ignored, %d broken, '
'%d not executable by deadline (UTC %s)', opts.batch_size,
opts.prefetch_size, duration, total, expired, no_queue,
hash_mismatch, cache_lookup, real_mismatch, ignored, broken,
too_long, deadline)