The UnicastProcessor requests Long.MAX_VALUE elements on subscription and there is no way to set this while creating the processor.
I want to limit the number of requested items (to say 1) and only request next item once the previous items have been replayed to the subscriber. Also, the processor should only keep 1 subscriber and disconnect on second subscription, just like UnicastProcessor.
Related
When using StreamMessageListenerContainer a subscription for a consumer group can be created by calling:
receive(consumer, readOffset, streamListener)
Is there a way to configure the container/subscription so that it will always attempt to re-process any PENDING messages before moving on to polling for new messages?
The goal would be to keep retrying any message that wasn't acknowledged until it succeeds, to ensure that the stream of events is always processed in exactly the order it was produced.
My understanding is if we specify the readOffset as '>' then on every poll it will use '>' and it will never see any messages from the PENDING list.
If we provide a specific message id, then it can see messages from the PENDING list, but the way the subscription updates the lastMessageId is like this:
pollState.updateReadOffset(raw.getId().getValue());
V record = convertRecord(raw);
listener.onMessage(record);
So even if the listener throws an exception, or just doesn't acknowledge the message id, the lastMessageId in pollState is still updated to this message id and won't be seen again on the next poll.
Using Redis stream we can have pending items which aren't finished by some consumers.
I can find such items using xpending command.
Let we have two pending items:
1) 1) "1-0"
2) "local-dev"
3) (integer) 9599
4) (integer) 1
2) 1) "2-0"
2) "local-dev"
3) (integer) 9599
4) (integer) 1
The problem that by using xpending we can set filters based on id only. I have a couple of service nodes (A, B) which make zombie check: XPENDING mystream test_group - 5 1
Each of them receives "1-0" item and they make xclaim and only one of them (for example A) becomes the owner and starts processing this item. But B runs xpending again to get new items but it receives again "1-0" because it hasn't been processed yet (A is working) and it looks like all my queue is blocked.
Is there any solution how I can avoid it and process pending items concurrently?
You want to see the documentation, in particular Recovering from permanent failures.
The way this is normally used is:
You allow the same consumer to consume its messages from PEL after recovering.
You only XCLAIM from another consumer when a reasonably large time elapsed, that suggests the original consumer is in permanent failure.
You use delivery count to detect poison pills or death letters. If a message has been retried many times, maybe it's better to report it to an admin for analysis.
So normally all you need is to see the oldest age in PEL from other consumers for the Permanent Failure Recovery logic, and you consume one by one.
I am using the taskqueue API to send multiple emails is small groups with mailgun. My code looks more or less like this:
class CpMsg(ndb.Model):
group = ndb.KeyProperty()
sent = ndb.BooleanProperty()
#Other properties
def send_mail(messages):
"""Sends a request to mailgun's API"""
# Some code
pass
class MailTask(TaskHandler):
def post(self):
p_key = utils.key_from_string(self.request.get('p'))
msgs = CpMsg.query(
CpMsg.group==p_key,
CpMsg.sent==False).fetch(BATCH_SIZE)
if msgs:
send_mail(msgs)
for msg in msgs:
msg.sent = True
ndb.put_multi(msgs)
#Call the task again in COOLDOWN seconds
The code above has been working fine, but according to the docs, the taskqueue API guarantees that a task is delivered at least once, so tasks should be idempotent. Now, most of the time this would be the case with the above code, since it only gets messages that have the 'sent' property equal to False. The problem is that non ancestor ndb queries are only eventually consistent, which means that if the task is executed twice in quick succession the query may return stale results and include the messages that were just sent.
I thought of including an ancestor for the messages, but since the sent emails will be in the thousands I'm worried that may mean having large entity groups, which have a limited write throughput.
Should I use an ancestor to make the queries? Or maybe there is a way to configure mailgun to avoid sending the same email twice? Should I just accept the risk that in some rare cases a few emails may be sent more than once?
One possible approach to avoid the eventual consistency hurdle is to make the query a keys_only one, then iterate through the message keys to get the actual messages by key lookup (strong consistency), check if msg.sent is True and skip sending those messages in such case. Something along these lines:
msg_keys = CpMsg.query(
CpMsg.group==p_key,
CpMsg.sent==False).fetch(BATCH_SIZE, keys_only=True)
if not msg_keys:
return
msgs = ndb.get_multi(msg_keys)
msgs_to_send = []
for msg in msgs:
if not msg.sent:
msgs_to_send.append(msg)
if msgs_to_send:
send_mail(msgs_to_send)
for msg in msgs_to_send:
msg.sent = True
ndb.put_multi(msgs_to_send)
You'd also have to make your post call transactional (with the #ndb.transactional() decorator).
This should address the duplicates caused by the query eventual consistency. However there still is room for duplicates caused by transaction retries due to datastore contention (or any other reason) - as the send_mail() call isn't idempotent. Sending one message at a time (maybe using the task queue) could reduce the chance of that happening. See also GAE/P: Transaction safety with API calls
I have a telegram bot that for any received message runs a program in the server and sends its result back. But there is a problem! If a user sends too many messages to my bot(spamming), it will make server so busy!
Is there any way to block the people whom send more than 5 messages in a second and don't receive their messages anymore? (using telegram api!!)
Firstly I have to say that Telegram Bot API does not have such a capability itself, Therefore you will need to implement it on your own and all you need to do is:
Count the number of the messages that a user sends within a second which won't be so easy without having a database. But if you have a database with a table called Black_List and save all the messages with their sent-time in another table, you'll be able to count the number of messages sent via one specific ChatID in a pre-defined time period(In your case; 1 second) and check if the count is bigger than 5 or not, if the answer was YES you can insert that ChatID to the Black_List table.
Every time the bot receives a message it must run a database query to see that the sender's chatID exists in the Black_List table or not. If it exists it should continue its own job and ignore the message(Or even it can send an alert to the user saying: "You're blocked." which I think can be time consuming).
Note that as I know the current telegram bot API doesn't have the feature to stop receiving messages but as I mentioned above you can ignore the messages from spammers.
In order to save time, You should avoid making a database connection
every time the bot receives an update(message), instead you can load
the ChatIDs that exist in the Black_List to a DataSet and update the
DataSet right after the insertion of a new spammer ChatID to the
Black_List table. This way the number of the queries will reduce
noticeably.
I have achieved it by this mean:
# Using the ttlcache to set a time-limited dict. you can adjust the ttl.
ttl_cache = cachetools.TTLCache(maxsize=128, ttl=60)
def check_user_msg_frequency(message):
print(ttl_cache)
msg_cnt = ttl_cache[message.from_user.id]
if msg_cnt > 3:
now = datetime.now()
until = now + timedelta(seconds=60*10)
bot.restrict_chat_member(message.chat.id, message.from_user.id, until_date=until)
def set_user_msg_frequency(message):
if not ttl_cache.get(message.from_user.id):
ttl_cache[message.from_user.id] = 1
else:
ttl_cache[message.from_user.id] += 1
With these to functions above, you can record how many messages sent by any user in the period. If a user's messages sent more than expected, he would be restricted.
Then, every handler you called should call these two functions:
#bot.message_handler(commands=['start', 'help'])
def handle_start_help(message):
set_user_msg_frequency(message)
check_user_msg_frequency(message)
I'm using pyTelegramBotAPI this module to handle.
I know I'm late to the party, but here is another simple solution that doesn't use a Db:
Create a ConversationState class to attach to each telegram Id when they start to chat with the bot
Then add a LastMessage DateTime variable to the ConversationState class
Now every time you receive a message check if enought time has passed from the LasteMessage DateTime, if not enought time has passed answer with a warning message.
You can also implement a timer that deletes the conversation state class if you are worried about performance.
In beanstalkd
telnet localhost 11300
USING foo
put 0 100 120 5
hello
INSERTED 1
How can I know what is the priority of this job when I reserve it? And can I release it by making the new priority equals to current priority +100?
Beanstalkd doesn't return the priority with the data - but you could easily add it as metadata in your own message body. for example, with Json as a message wrapper:
{'priority':100,'timestamp':1302642381,'job':'download http://example.com/'}
The next message that will be reserved will be the next available entry from the selected tubes, according to priority and time - subject to any delay that you had requested when you originally sent the message to the queue.
Addition: You can get the priority of a beanstalk job (as well as a number of other pieces of information, such as how many times it has previously been reserved), but it's an additional call - to the stats-job command. Called with the jobId, it returns about a dozen different pieces of information. See the protocol document, and your libraries docs.