Unacked message rabbitmq что это

Unacked message rabbitmq что это

This tutorial assumes RabbitMQ is installed and running on localhost on the standard port ( 5672 ). In case you use a different host, port or credentials, connections settings would require adjusting.

Where to get help

If you’re having trouble going through this tutorial you can contact us through the mailing list or RabbitMQ community Slack.

Prerequisites

As with other Python tutorials, we will use the Pika RabbitMQ client version 1.0.0.

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What This Tutorial Focuses On

In the first tutorial we wrote programs to send and receive messages from a named queue. In this one we’ll create a Work Queue that will be used to distribute time-consuming tasks among multiple workers.

The main idea behind Work Queues (aka: Task Queues) is to avoid doing a resource-intensive task immediately and having to wait for it to complete. Instead we schedule the task to be done later. We encapsulate a task as a message and send it to the queue. A worker process running in the background will pop the tasks and eventually execute the job. When you run many workers the tasks will be shared between them.

This concept is especially useful in web applications where it’s impossible to handle a complex task during a short HTTP request window.

We will slightly modify the send.py code from our previous example, to allow arbitrary messages to be sent from the command line. This program will schedule tasks to our work queue, so let’s name it new_task.py :

Our old receive.py script also requires some changes: it needs to fake a second of work for every dot in the message body. It will pop messages from the queue and perform the task, so let’s call it worker.py :

Round-robin dispatching

One of the advantages of using a Task Queue is the ability to easily parallelise work. If we are building up a backlog of work, we can just add more workers and that way, scale easily.

First, let’s try to run two worker.py scripts at the same time. They will both get messages from the queue, but how exactly? Let’s see.

In the third one we’ll publish new tasks. Once you’ve started the consumers you can publish a few messages:

Let’s see what is delivered to our workers:

By default, RabbitMQ will send each message to the next consumer, in sequence. On average every consumer will get the same number of messages. This way of distributing messages is called round-robin. Try this out with three or more workers.

Message acknowledgment

Doing a task can take a few seconds. You may wonder what happens if one of the consumers starts a long task and dies with it only partly done. With our current code once RabbitMQ delivers message to the consumer it immediately marks it for deletion. In this case, if you kill a worker we will lose the message it was just processing. We’ll also lose all the messages that were dispatched to this particular worker but were not yet handled.

But we don’t want to lose any tasks. If a worker dies, we’d like the task to be delivered to another worker.

In order to make sure a message is never lost, RabbitMQ supports message acknowledgments. An ack(nowledgement) is sent back by the consumer to tell RabbitMQ that a particular message had been received, processed and that RabbitMQ is free to delete it.

If a consumer dies (its channel is closed, connection is closed, or TCP connection is lost) without sending an ack, RabbitMQ will understand that a message wasn’t processed fully and will re-queue it. If there are other consumers online at the same time, it will then quickly redeliver it to another consumer. That way you can be sure that no message is lost, even if the workers occasionally die.

A timeout (30 minutes by default) is enforced on consumer delivery acknowledgement. This helps detect buggy (stuck) consumers that never acknowledge deliveries. You can increase this timeout as described in Delivery Acknowledgement Timeout.

Manual message acknowledgments are turned on by default. In previous examples we explicitly turned them off via the auto_ack=True flag. It’s time to remove this flag and send a proper acknowledgment from the worker, once we’re done with a task.

Using this code we can be sure that even if you kill a worker using CTRL+C while it was processing a message, nothing will be lost. Soon after the worker dies all unacknowledged messages will be redelivered.

Acknowledgement must be sent on the same channel that received the delivery. Attempts to acknowledge using a different channel will result in a channel-level protocol exception. See the doc guide on confirmations to learn more.

Forgotten acknowledgment

In order to debug this kind of mistake you can use rabbitmqctl to print the messages_unacknowledged field:

On Windows, drop the sudo:

Message durability

We have learned how to make sure that even if the consumer dies, the task isn’t lost. But our tasks will still be lost if RabbitMQ server stops.

When RabbitMQ quits or crashes it will forget the queues and messages unless you tell it not to. Two things are required to make sure that messages aren’t lost: we need to mark both the queue and messages as durable.

First, we need to make sure that the queue will survive a RabbitMQ node restart. In order to do so, we need to declare it as durable:

This queue_declare change needs to be applied to both the producer and consumer code.

Note on message persistence

Fair dispatch

You might have noticed that the dispatching still doesn’t work exactly as we want. For example in a situation with two workers, when all odd messages are heavy and even messages are light, one worker will be constantly busy and the other one will do hardly any work. Well, RabbitMQ doesn’t know anything about that and will still dispatch messages evenly.

This happens because RabbitMQ just dispatches a message when the message enters the queue. It doesn’t look at the number of unacknowledged messages for a consumer. It just blindly dispatches every n-th message to the n-th consumer.

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In order to defeat that we can use the Channel#basic_qos channel method with the prefetch_count=1 setting. This uses the basic.qos protocol method to tell RabbitMQ not to give more than one message to a worker at a time. Or, in other words, don’t dispatch a new message to a worker until it has processed and acknowledged the previous one. Instead, it will dispatch it to the next worker that is not still busy.

Note about queue size

If all the workers are busy, your queue can fill up. You will want to keep an eye on that, and maybe add more workers, or use message TTL.

Putting it all together

Using message acknowledgments and prefetch_count you can set up a work queue. The durability options let the tasks survive even if RabbitMQ is restarted.

Now we can move on to tutorial 3 and learn how to deliver the same message to many consumers.

Production [Non-]Suitability Disclaimer

Please keep in mind that this and other tutorials are, well, tutorials. They demonstrate one new concept at a time and may intentionally oversimplify some things and leave out others. For example topics such as connection management, error handling, connection recovery, concurrency and metric collection are largely omitted for the sake of brevity. Such simplified code should not be considered production ready.

Please take a look at the rest of the documentation before going live with your app. We particularly recommend the following guides: Publisher Confirms and Consumer Acknowledgements, Production Checklist and Monitoring.

Getting Help and Providing Feedback

If you have questions about the contents of this tutorial or any other topic related to RabbitMQ, don’t hesitate to ask them on the RabbitMQ mailing list.

Help Us Improve the Docs 1 «Hello World!»

The simplest thing that does something

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2 Work queues

Distributing tasks among workers (the competing consumers pattern)

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3 Publish/Subscribe

Sending messages to many consumers at once

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4 Routing

Receiving messages selectively

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5 Topics

Receiving messages based on a pattern (topics)

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6 RPC

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7 Publisher Confirms

Reliable publishing with publisher confirms

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View rabbitmq unacked message

We have a rabbitmq cluster that receives messages from one application that then get picked up by a second application. We have ran into an issue where we have a large number of ‘unacked’ messages in our queue. We have three total servers that run the second app and have restarted all of them but the unacked messages are not picked up. We receive an error that looks like an issue with our code (which we are looking into separately).

After doing some research we’ve realized these messages could have potentially already been sent but not acknowledged properly. We are wondering if there is a way to view the unacked messages similar to ones in the ready queue so we can investigate further.

1 Answer 1

We found a few things that helped us with this.

First, we created a catchall queue to collect all events and keep them in the ready queue so we could figure out what was going on. It turned out one producer was sending invalid messages. We shut this producer down and observed all new messages looked good and were processing.

Second, we shutdown all consumers (fine in our environment) for a short time. This caused all of the messages to move from unacked to ready. At this point we could view and see they were all invalid. Since they were in the ready queue we were able to flush the queue.

Not the answer you’re looking for? Browse other questions tagged linux rabbitmq or ask your own question.

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RabbitMQ How to Remove Unacked Message

When using RabbitMQ there are situations where you might want to remove unacked messages. You could end up with a polluted environment if you don’t get things cleaned up. It can also be an indicator of something that is broken such as a stuck consumer.

To remove unacked messages in RabbitMQ:

We’re going to show you how to do this from the command line and from the management GUI.

Show queues with unacked connections like this.

To find the channel with unacked messages you can use the following command. It will also show the connection that is associated with the channel.

You can close the channel like this. Specify the connection that was associated with the channel found above. The last parameter is a message that will be sent to the consumer and will appear in the consumer’s error message.

As an alternative to the step above you could just manually kill the process for the consumer that is associated with the channel.

You can use the following command to verify that you no longer have any unacked messages but these same messages should be in the “Ready” state.

If you want the messages to be removed from the queue this can be done by purging them with either of the following commands.

You can complete these same steps using the management GUI.

You can view channels and unacked messages here on the “Channels” tab but you will want to go to the “Connections” tab to actually close them.

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To start off you can see all of your connections on the “Connections” tab like this. Just click on one of them to view it.

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When you view a specific connection you can see the number of unacked messages on each of its channels. Just click the “Force Close” button to close the connection.

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Next you can go to the “Queues” tab. Here you should be able to see that there are no unacked messages. The messages that were previously in an unacked state should now be in a “Ready” state. Select a queue to purge.

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Click on the “Purge Messages” button to clear all messages from the queue.

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RabbitMQ Unacked Message Cause

One thing that can cause unacked messages to build up for a consumer is forgetting to ack messages. If auto_ack is not turned on then an ack needs to be sent manually. If this is forgotten or just not done it will cause unacked messages to build up. Here is an example of broken consumer code that omits the ack line from the call back function.

You can fix this by placing a call to “basic_ack” at the end of the callback function like this:

You can also fix this by enabling “auto_ack” which may or may not be the right thing to do depending on the situation:

Extra Info

You can close a channel programmatically like this:

When you close a connection all channels on that connection will also be closed. You can close a connection programmatically like this:

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Troubleshooting RabbitMQ

You can troubleshoot RabbitMQ by viewing the log files under the Roaming AppData. Additionally, you can use the RabbitMQ management UI to view information about the topics and subscriptions used for distributing messages.

This page contains the following information:

RabbitMQ logging/service management

RabbitMQ creates its own file for logging under the Roaming AppData of the user who installed RabbitMQ:

By default, RabbitMQ logs at the info level and logs service events such as incoming connections and service start-up and shutdown.

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To start or stop your RabbitMQ service, use either the shortcuts RabbitMQ creates upon installation or open up a command prompt to RabbitMQ’s sbin.

Note: Run the shortcuts as an administrator.

If you choose to use the command prompt, use the commands rabbitmqctl start_app and rabbitmqctl stop_app to start and stop respectively. For more information on other commands available within the command line, see commands on the RabbitMQ website.

Note: Use caution while running command line prompts against RabbitMQ. If you get into a state where you can neither stop or start the service, try a restart of the machine itself before attempting anything else.

Erlang crash dump logging

Erlang outputs a dump file when there is an issue starting the RabbitMQ service. The dump file is located where the data directory is set, by default C:/Users/ /AppData/Roaming/RabbitMQ, and is named erl_crash.dump. The quickest way to identify the issue is within the first few lines next to the property called ‘Slogan’.

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The Slogan is the reason why the dump file was taken in the first place. In the case above, you can see that there was an application start failure for RabbitMQ where it could not start a listener on port 5672. For more information on the other data in the dump file and some common messages that may appear in the dump file, see How to Interpret the Erlang Crash Dumps.

RabbitMQ management UI

RabbitMQ ships with the management plugin, but you must enable it before you can use the management operations in the Relativity service bus library. The management plugin provides an API for manipulating RabbitMQ entities like exchanges and queues. It also provides a web interface for managing and monitoring the RabbitMQ instance. Complete the following steps to enable the RabbitMQ management UI:

Overview tab

The overview tab provides a quick overview of your RabbitMQ cluster. It contains graphs on operations per second, info on nodes in the cluster, and context/connection information. This tab is a useful resource to get a basic overview of your current system to check if there is any activity in the instance.

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Connections, Channels, Exchanges, and Queues

The management UI has multiple tabs that contain information on who is connected to the RabbitMQ cluster. It also displays which exchanges and queues are defined along with real-time information on the messages contained within them.

Connection tab

The connection tab contains all active connections within the RabbitMQ cluster. Connections correspond to the AppDomain name. This is generally either the process name or the name of the Relativity agent.

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Clicking on a connection takes you to a page with additional information about that connection.

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Channels tab

This tab displays information about all currently active channels.

For Relativity, if there is a “C” under Mode, this generally indicates the channel is dedicated to sending messages. Similarly, a populated Prefetch value generally indicates the channel is dedicated to receiving messages.

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Clicking on a channel takes you to a page with additional information about that channel. This includes configuration values and any consumers.

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Exchanges and Queues tabs

The exchange and queue tab displays the topics and queues within the RabbitMQ cluster. You can use these tabs to view details about the topic or queue and real-time message statistics.

Exchanges tab

The exchange tab shows all the exchanges within the RabbitMQ cluster which translates to both topics and queues from the Relativity.ServiceBus library. The main table contains every name of topics and queues defined within the cluster and their respective deadletter queues which are identified by the characters «-DLE» appended to the end. If the exchange name ends in «-FE», it is an exchange for a filtered subscription; you can find what it is filtering on is in the exchange details under the binding’s routing keys. There are also metrics on the current message’s in and out rates.

Clicking on an exchange takes you to the exchange detail page where you can view a graph of the message rates and details about the exchange and its bindings. Bindings are what this exchange forwards the message to; the binding can either be another exchange or a queue (subscription in the Relativity.ServiceBus library). In the case of a fanout type exchange, it broadcasts all messages to everything it is bound to.With a direct exchange, messages are only forwarded to bindings for the routing key that they match. You can navigate to the queue or exchange that is bound to the exchange you are viewing by clicking on the name in the Bindings section.

From this page, you can perform actions like publishing a message or deleting the exchange.

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Queues tab

The queues tab is very similar to the exchanges tab. This page lists all the queues (subscriptions in Relativity.ServiceBus) that exist in the cluster. Queues ending in «-DLQ» are the deadletter subscriptions. The main differences are:

The State column shows whether the connection to that queue is active or not

You can view more details about the queue from the queue details page. You can also publish, receive, and purge all messages from the queue; inspect current consumers; move messages from the queue; and delete the queue itself.

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Admin tab

The admin page has multiple sub-tabs. These tabs are Users, Virtual Hosts, Policies, Limits, and Cluster.

Note: For more information, see the RabbitMQ website.

Common troubleshooting tasks for RabbitMQ

Use these common troubleshooting tasks to resolve issues with RabbitMQ.

Queue is not draining

Complete the following steps if the queue is not draining:

Relativity Web and/or Agent servers are unable to connect to RabbitMQ

Complete the following steps if Relativity Web and/or Agent servers are unable to connect to RabbitMQ:

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I have thousands of unacked messages in my dev environment which I can’t restart.
Is there a way to remove (purge) all messages even if they are unacknowledged?

8 Answers 8

Close the channel that the unacked messages reside on, which will nack them back into the queue, then call purge.

You have to make consumer ack them (or nack ) and only after that they will be removed. Alternatively you can shutdown consumers and purge the queue completely.

It looks like your consumer is the cause of the problem, so you have to adjust it (rewrite) to release message immediately after it processed or failed.

Once there are no «ready» messages in the queue, delete it and recreate.

YOU WILL LOSE THE QUEUE CONTENTS with this method.

You need to put messages back into the queue before you can purge them:

As an alternative, this doesn’t require to wait:

You need to call basic.recover to force all unacked messages to be re-enqueued to a channel that failed. Be aware of the errata concerning this function specifying that only the requeue mode is supported by RabbitMQ.

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For software developer use below code.

channel.purgeQueue(queue-name);

if we use this code the Queue will be clear and same queue will exist.

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Since the messages are never left in the Ready state, the Management Interface’s Get Message(s) button is unlikely work. What can work, if you have queue access, is to run a separate custom consumer instance, perhaps locally, but with the specific intent of removing and not requeuing the messages in question.

By RabbitMQ’s Fair Dispatch mechanism, your additional consumer will likely receive the messages in question and have the opportunity to perform your custom handling.

You might even write a custom utility to do this, with logic to filter, analyze, or deadletter the messages of interest.

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