Azure servicebus ReceiveBatch only returns 2 messages - azure

I am trying to periodically receive all messages in a servicebus queue. But when I call ReceiveBatch(1000) I max get 2 messages back.
This question is kind of related to this question, except he would get a lot more by calling ReceiveBatch multiple times, I do not.
How do I get all messages on a servicebus queue?

The name ReceiveBatch(maximumNumber) is somewhat misleading. You don't get a batch, you get a collection of up-to maximum number of messages. This means you can receive less than maximuNumber as well. If you wish to receive a specific amount, you'd need to loop through the receiving operation until you get that number of messages (and potentially slightly more).

Related

Google PubSub: drop nacked message after n retries

Is there way to configure pull subscription in the way that messages which caused error and were nacked, were re-queued (and so that redelivered) no more than n times?
Ideally on the last processing if it also failed I would like to handle this case (for example, log that this message is given up to process and will be dropped).
Or probably it's possible to find out, how much times received message was tried to be processed before?
I use node.js. I can see a lot of different options in the source code by am not sure how should I achieve desired behaviour.
Cloud Pub/Sub supports Dead Letter Queues that can be used to drop nacked messages after a configurable number of retries.
Currently, there is no way in Google Cloud Pub/Sub to automatically drop messages that were redelivered some designated number of times. The message will stop being delivered once the retention deadline has passed for that message (by default, seven days). Likewise, Pub/Sub does not keep track of or report the number of times a message was delivered.
If you want to handle these kinds of messages, you'd need to maintain a persistent storage keyed by message ID that you could use to keep track of the delivery count. If the delivery count exceeds your desired threshold, you could write the message to a separate topic that you use as a dead letter queue and then acknowledge original message.

AWS SQS: Moving to dead letter queue when error happens in consumer

I have tried using npm packages like sqs-queue-parallel & sqs-consumer for consuming messages of SQS in node
But lately I have mechanism where when error happens for a particular message while processing, it should be moved to dead letter queue
But as of now it keeps on retrying the message by maximum receive count times
Is it possible with some other npm package, were whenever an error happens it should be moved directly to dead letter queue?
Know this is a bit late but think OP is trying to ask for a dynamic policy. I.e.:
on normal errors -> retry as per redrive-policy.
However, for certain failures you might know you can't recover even if you try it a hundred items. In that case -> move message directly to dead letter queue.
How to do the latter if presumably what is asked.
Answer is probably to manually copy message to deadletter queue (it behaves just like any other queue in that regard) and remove message from source queue afterwards.
Don't believe there's a 'special' way to do this.
You can configure your SQS queue to move messages to your Dead Letter Queue after any number of failed message receives between 1 and 1000.
To have a message moved to the Dead Letter Queue after only one failed receive, then modify your queue's configuration and set the "Maximum Receives" value to 1. This would be part of your queue's "Redrive Policy".
See the following AWS documentation on configuring your queue:
http://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/SQSDeadLetterQueue.html
You dont need to use a new npm for that its automatically happens when you finish dealing with a message. for example if you been using node-consumer when you finish with the message you do:
done() //in order to remove from queue due to for success probably
or
done(err) //in order to keep in queue
so now in order to move message from queue to dead letter queue you dont need to do anything else in your code but only in you sqs console manager :
create a new queue
call it dead-messages (or whatever)
set the "Maximum Receives" value to 1 (that means after one call to
"done(error)" the message will removed from your queue and go to the dead queue.
refresh!!!!
go back to your source queue (original one)
go to configure queue
set retrieve policy
put the name that you gave to the dead letter queue
thats it! good luck and i have to say the sqs is great way to scale tasks.
I think OP is asking if there is a way to move messages to DLQ after "A SINGLE FAILURE" in processing the message. As per these 2 SQS documentations I see these 2 points:
if the source queue has a redrive policy with maxReceiveCount set to 5, and the consumer of the source queue receives a message 6 times without ever deleting it, Amazon SQS moves the message to the dead-letter queue (https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/sqs-dead-letter-queues.html).
Maximum receives value must be between 1 and 100 (https://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/sqs-configure-dead-letter-queue.html)
Which means that even if you set Maximum receives value to 1, your consumer would still receive the message "AT-LEAST TWICE"
I am not able to find any solution where you can move the failed message to DLQ after a single failure. Would love to hear other people's thoughts on this

Is there any issue with resending a message back to the Azure queue

I've got a scheduler and some workers in Azure. The scheduler puts messages into a queue and the workers pull those messages and work on them. I've now just come into a scenario where I will need to move some data from table storage to our database once a certain threshold has been reached. These items need to be processed in order, oldest first. Once that threshold is met all the other items are processed in order. The current message that triggered the transfer needs to be stuffed at the end of the line and be reprocessed.
So, to the meat of my question...
Is it fine to simply resend the message to the queue as is or is there a potential for that to cause problems?
queueProvider.SendMessage(message);
A co-worker mentioned that he "though he might have read something about needing to do something special." I haven't seen anything to confirm his suspicions yet however so I thought I would pose the question here just to be safe.
The short answer is that it is fine. If you have a CloudQueueMessage, you can just send it to any queue (it is just a REST request at the end of the day). Every time you AddMessage(), it creates a new ID (might be same pop receipt but that doesn't matter). That being said, there are some things you might want to take care of and or investigate:
If you push a message onto one queue, pop it, and push to another queue or same queue, you should probably delete the first message off the queue. Merely popping it means that you have set the invisibility time out, but that it will reappear soon (and you now have identical message content on each queue). So, if I pop a message and immediately push it again, I now have 2 messages in the queue with identical content.
You can now update messages. This might be appropriate for you if you need ordering. You can indicate on the message itself in metadata or content what stage of processing it is in and you get some ordering here with a thoughtful implementation.
It is recommended that all logic inside the consumer of the queue be idempotent since a message can actually be picked up more than once. We have to keep in mind that the queue service guarantees that a message will be delivered, AT LEAST ONCE - so you could end up duplicating messages with this approach.

does multiple Azure worker role polling same Queue causes Dead Lock or Poison message

Scenario:
if I've spin off multiple Worker roles or ONE Worker role with multiple threads, which polls the new messages in Azure Queue.
Could someone please confirm if the this the correct design approach? The reason I would like to have many worker roles is to speed up the PROCESSJOB. Our application should be near real time, i.e. as soon as there are messages we should get, apply complex business rules and commit to AZURE DB. We are expecting 11,000 message per 3min.
Thank you.
You may have as many queue-readers as you like. It's very common to scale out worker role instances, as they can all read from the same queue, giving you much greater work throughput.
When you read a queue message, it's marked "invisible" for a period of time, to prevent others from reading and doing the same work. The owner of the message must delete it before the time period expires, otherwise the message becomes visible again, and an exception will be thrown when the original reader attempts to delete it. This means your operations must be idempotent.
There's no direct poison-message handling, but it's easy to implement, as each message has a dequeue count. Just check it and remove poison messages after being read 3-4 times. You can also dynamically adjust the timeout period based on dequeue count, as maybe the processing fails due to too-short a time window.
Here's the MSDN documentation for DequeueCount.
EDIT: As far as processing 11,000 messages in 3 minutes: the scalability target for queues is 500 2,000 TPS, or up to 360,000 transactions in 3 minutes (far beyond the 11,000 message requirement you have). You can speed things up further by combining messages into a single queue message, as well as reading multiple messages at a time, which will also reduce your transaction count. You can also look at the ApproximateMessageCount property of a queue to see if your queue is backing up (and then scaling out to additional intstances to help consume queue items).

Azure Queue unique message

I would like to make sure that I don't insert a message to the queue multiple times. Is there any ID/Name I can use to enforce uniqueness?
vtortola pretty much covered it, but I wanted to add a bit more detail into why it's at least once delivery.
When you read a queue item, it's not removed from the queue; instead, it becomes invisible but stays in the queue. That invisibility period defaults to 30 seconds (max: 2 hours). During that time, the code that got the item off the queue has that much time to process whatever command was in the queue message and delete the queue item.
Assuming the queue item is deleted before the timeout period is reached, all is well. However: Once the timeout period is reached, the queue item becomes visible again, and the code holding the queue item may no longer delete it. In this case, someone else can read the same queue message and re-process that message.
Because of the fact a queue message can timeout, and can re-appear:
Your queue processing must be idempotent - operations on a queue message must result in the same outcome (such as rendering a thumbnail for a photo).
You need to think about timeout adjustments. You might find that commands are valid but processing is taking too long (maybe your 45-second thumbnail rendering code worked just fine until someone uploaded a 25MP image)
You need to think about poison messages - those that will never process correctly. Maybe they cause an exception to be thrown or have some invalid condition that causes the message processor to abort processing, which leads to the message eventually re-appearing in the queue. There's a property callded DequeueCount - consider viewing that property upon reading a queue item and, if equal to, say, 3, push the message into a table or blob and send yourself a notification to spend some time debugging that message offline.
More details on the get-queue low-level REST API is here. This will give you more insight into Windows Azure queue message handling.
Azure queues doesn't ensure message order and either message uniqueness. Messages will be processed "at least once", but nothing ensures it won't be processed twice, so it doesn't ensure "at most once".
You should get ready to receive the same message twice. You can put an ID in the body of the message as part of your data.

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