def deferred_ratings():
""" This is the deferred ratings table calculation process """
# Disable the in-context cache to save memory
# (it doesn't give any speed advantage for this processing)
Context.disable_cache()
t0 = time.time()
try:
_create_ratings()
except DeadlineExceededError as ex:
# Hit deadline: save the stuff we already have and
# defer a new task to continue where we left off
logging.error(u"Deadline exceeded in ratings, failing permamently")
# Normal return prevents this task from being run again
raise deferred.PermanentTaskFailure()
except Exception as ex:
logging.error(
u"Exception in ratings, failing permanently: {0}".format(ex))
# Avoid having the task retried
raise deferred.PermanentTaskFailure()
t1 = time.time()
logging.info(u"Ratings calculation finished in {0:.2f} seconds".format(t1 -
t0))
StatsModel.log_cache_stats()
StatsModel.clear_cache(
) # Do not maintain the cache in memory between runs
def deferred_update():
""" Update all users in the datastore with lowercase nick and full name """
logging.info("Deferred user update starting")
CHUNK_SIZE = 200
count = 0
offset = 0
Context.disable_cache()
try:
q = UserModel.query()
while True:
ulist = []
chunk = 0
for um in q.fetch(CHUNK_SIZE, offset = offset):
chunk += 1
if um.nick_lc is None:
try:
um.nick_lc = um.nickname.lower()
um.name_lc = um.prefs.get("full_name", "").lower() if um.prefs else ""
ulist.append(um)
except Exception as e:
logging.info("Exception in deferred_update() when setting nick_lc: {0}".format(e))
if ulist:
try:
ndb.put_multi(ulist)
count += len(ulist)
except Exception as e:
logging.info("Exception in deferred_update() when updating ndb: {0}".format(e))
if chunk < CHUNK_SIZE:
break
offset += CHUNK_SIZE
except Exception as e:
logging.info("Exception in deferred_update(): {0}, already updated {1} records".format(e, count))
# Do not retry the task
raise deferred.PermanentTaskFailure()
logging.info("Completed updating {0} user records".format(count))
def deferred_ratings():
""" This is the deferred ratings table calculation process """
# Disable the in-context cache to save memory
# (it doesn't give any speed advantage for this processing)
Context.disable_cache()
t0 = time.time()
try:
_create_ratings()
except DeadlineExceededError as ex:
# Hit deadline: save the stuff we already have and
# defer a new task to continue where we left off
logging.error(u"Deadline exceeded in ratings, failing permamently")
# Normal return prevents this task from being run again
raise deferred.PermanentTaskFailure()
except Exception as ex:
logging.error(u"Exception in ratings, failing permanently: {0}".format(ex))
# Avoid having the task retried
raise deferred.PermanentTaskFailure()
t1 = time.time()
logging.info(u"Ratings calculation finished in {0:.2f} seconds".format(t1 - t0))
StatsModel.log_cache_stats()
StatsModel.clear_cache() # Do not maintain the cache in memory between runs
def deferred_update():
""" Update all users in the datastore with lowercase nick and full name """
logging.info("Deferred user update starting")
CHUNK_SIZE = 200
count = 0
offset = 0
Context.disable_cache()
try:
q = UserModel.query()
while True:
ulist = []
chunk = 0
for um in q.fetch(CHUNK_SIZE, offset = offset):
chunk += 1
if um.nick_lc is None:
try:
um.nick_lc = um.nickname.lower()
um.name_lc = um.prefs.get("full_name", "").lower() if um.prefs else ""
ulist.append(um)
except Exception as e:
logging.info("Exception in deferred_update() when setting nick_lc: {0}".format(e))
if ulist:
try:
ndb.put_multi(ulist)
count += len(ulist)
except Exception as e:
logging.info("Exception in deferred_update() when updating ndb: {0}".format(e))
if chunk < CHUNK_SIZE:
break
offset += CHUNK_SIZE
except Exception as e:
logging.info("Exception in deferred_update(): {0}, already updated {1} records".format(e, count))
# Do not retry the task
raise deferred.PermanentTaskFailure()
logging.info("Completed updating {0} user records".format(count))
def deferred_ratings(timestamp):
""" This is the deferred ratings table calculation process """
# Disable the in-context cache to save memory
# (it doesn't give any speed advantage for this processing)
Context.disable_cache()
t0 = time.time()
_create_ratings(timestamp)
t1 = time.time()
logging.info(u"Ratings calculation finished in {0:.2f} seconds".format(t1 - t0))
def deferred_stats(from_time, to_time):
""" This is the deferred stats collection process """
# Disable the in-context cache to save memory
# (it doesn't give any speed advantage for this processing)
Context.disable_cache()
t0 = time.time()
_run_stats(from_time, to_time)
t1 = time.time()
logging.info(u"Stats calculation finished in {0:.2f} seconds".format(t1 - t0))
def deferred_stats(from_time, to_time):
""" This is the deferred stats collection process """
# Disable the in-context cache to save memory
# (it doesn't give any speed advantage for this processing)
Context.disable_cache()
t0 = time.time()
_run_stats(from_time, to_time)
t1 = time.time()
logging.info(u"Stats calculation finished in {0:.2f} seconds".format(t1 -
t0))
def deferred_ratings(timestamp):
""" This is the deferred ratings table calculation process """
# Disable the in-context cache to save memory
# (it doesn't give any speed advantage for this processing)
Context.disable_cache()
t0 = time.time()
_create_ratings(timestamp)
t1 = time.time()
logging.info(u"Ratings calculation finished in {0:.2f} seconds".format(t1 -
t0))