I am looking into using EventBridge as our platform for events/messaging. One concern is the lack of support for FIFO within EventBridge. This can be resolved by using an SQS FIFO source combined with an EventBridge pipe.
I would like to know if messages are archived and then replayed, will the replay maintain the original FIFO ordering of the messages or will the replay simply blast out events in "random" order.
Any real life experience would be appreciated.
Related
I have a multiple publishers publishing events for a shipment entity on an SQS queue and I have multiple listeners on it for parallel processing. But I want events for a particular shipment (having some identifier) to be processed sequentially in order. Is there any in-built feature to support this?
ActiveMQ has a similar concept of Exclusive Consumer which is not exactly what I need but could be adapted
Yes, there is; they are called FIFO (First-In-First-Out) queues
FIFO (First-In-First-Out) queues are designed to enhance messaging between applications when the order of operations and events is critical, or where duplicates can't be tolerated.
You will need to ensure that the messages you want processed in the correct order belong to the same Message Group ID:-
The tag that specifies that a message belongs to a specific message group. Messages that belong to the same message group are always processed one by one, in a strict order relative to the message group (however, messages that belong to different message groups might be processed out of order).
Hope that helps!
We have a use case in the Streaming mode where we want to keep track of a counter on BigTable from the pipeline (something #items finished processing) for which we need the increment operation. From looking at https://cloud.google.com/bigtable/docs/dataflow-hbase, I see that append/increment operations of the HBase API are not supported by this client. The reason stated is the retry logic on batch mode but if Dataflow guarantees exactly-once, why would supporting it be a bad idea since I know for sure the increment was called only-once? I want to understand what part I am missing.
Also, is CloudBigTableIO usable in Streaming mode or is it tied to Batch mode only? I guess we could use the BigTable HBase client directly in the pipeline but the connector seems to have nice properties like Connection-pooling which we would like to leverage and hence the question.
The way that Dataflow (and other systems) offer the appearence of exactly-once execution in the presence of failures and retries is by requiring that side-effects (such as mutating BigTable) are idempotent. A "write" is idempotent because it is overwritten on retry. Inserts can be made idempotent by including a deterministic "insert ID" that deduplicates the insert.
For an increment, that is not the case. It is not supported because it would not be idempotent when retried, so it would not support exactly-once execution.
CloudBigTableIO is usable in streaming mode. We had to implement a DoFn rather than a Sink in order to support that via the Dataflow SDK.
Iam sending messages to the queue and using amazon sqs queuing system in a rails application. But since the queue follows FIFO process, it will get the next items in the same fashion. Suppose if I have 100 items in a queue, how can I retrieve the 35th item from the queue and process it. As far as I know, there is no such method that amazon sqs provides for doing it. So is there any other method/workaround where I can achieve the this functionality.
There is no method to do that; SQS does not guarantee order of items in the queue due to its geographically redundant nature; it can't even guarantee FIFO. If you absolutely must process things in order, and need the ability to 'look ahead' in the queue, SQS may not be your best choice. Perhaps a custom made queue in something like DynamoDB may be work better.
SQS is designed to guarantee at-least-once delivery and does not take into account the order of messages. So the simple answer to your question on whether you can do that, is no.
A work around would depend on your use-case:
To split work among different processes handling queue messages and making sure they don't both process the same item - Different queues is one approach, or prefixing every message with an identifier denoting which process is supposed to work on it. For example, if I have 4 daemons's running, I could prefix every message in the queue with the ID of the process which should work on it - 1,2,3 or 4. Every process would only process messages with the number corresponding to it's ID.
Order of arrival is critical - In this case, you're better off not using SQS because it wasn't to be used this way. CloudAMQP is a cloud based service that is based off RabbitMQ which is a true FIFO queue and would suit this case better than SQS.
I'm using an Amazon SQS queue to send notifications to an external system.
If the HTTP request fails when using SQS' SendMessage, I don't know whether the message has been queued or not. My default policy would be to retry posting the message to the queue, but there's a risk to post the message twice, which might not be acceptable depending on the use case.
Is there a way to have SQS refuse the message if there is a duplicate on the message body (or some kind of message metadata, such as a unique ID we could provide) so that we could retry until the message is accepted, and be confident that there won't be a duplicate if the first request had been already queued, but the response had been lost?
No, there's no such mechanism in SQS. Going further, it is also possible that a message will be delivered twice or more (at-least-once delivery semantics). So even if such a mechanism existed, you wouldn't be able to guarantee that the message isn't delivered multiple times.
See: http://docs.aws.amazon.com/AWSSimpleQueueService/latest/SQSDeveloperGuide/DistributedQueues.html
For exactly-once deliveries, you need some form of transactions (and HTTP isn't a transactional protocol) both on the sending and receiving end.
AFAIK, right now SQS does support what was asked!
Please see the "What's new" post entitled Amazon SQS Introduces FIFO Queues with Exactly-Once Processing and Lower Prices for Standard Queues
According to SQS FAQ:
FIFO queues provide exactly-once processing, which means that each message is delivered once and remains available until a consumer processes it and deletes it. Duplicates are not introduced into the queue.
There's also an AWS Blog post with a bit more insight on the subject:
These queues are designed to guarantee that messages are processed exactly once, in the order that they are sent, and without duplicates.
......
Exactly-once processing applies to both single-consumer and multiple-consumer scenarios. If you use FIFO queues in a multiple-consumer environment, you can configure your queue to make messages visible to other consumers only after the current message has been deleted or the visibility timeout expires. In this scenario, at most one consumer will actively process messages; the other consumers will be waiting until the first consumer finishes or fails.
Duplicate messages can sometimes occur when a networking issue outside of SQS prevents the message sender from learning the status of an action and causes the sender to retry the call. FIFO queues use multiple strategies to detect and eliminate duplicate messages. In addition to content-based deduplication, you can include a MessageDeduplicationId when you call SendMessage for a FIFO queue. The ID can be up to 128 characters long, and, if present, takes higher precedence than content-based deduplication.
According to the documentation:
Q: How many times will I receive each message?
Amazon SQS is
engineered to provide “at least once” delivery of all messages in its
queues. Although most of the time each message will be delivered to
your application exactly once, you should design your system so that
processing a message more than once does not create any errors or
inconsistencies.
Is there any good practice to achieve the exactly-once delivery?
I was thinking about using the DynamoDB “Conditional Writes” as distributed locking mechanism but... any better idea?
Some reference to this topic:
At-least-once delivery (Service Behavior)
Exactly-once delivery (Service Behavior)
FIFO queues are now available and provide ordered, exactly once out of the box.
https://aws.amazon.com/sqs/faqs/#fifo-queues
Check your region for availability.
The best solution really depends on exactly how critical it is that you not perform the action suggested in the message more than once. For some actions such as deleting a file or resizing an image it doesn't really matter if it happens twice, so it is fine to do nothing. When it is more critical to not do the work a second time I use an identifier for each message (generated by the sender) and the receiver tracks dups by marking the ids as seen in memchachd. Fine for many things, but probably not if life or money depends on it, especially if there a multiple consumers.
Conditional writes sound like a clever solution, but it has me wondering if perhaps AWS isn't such a great solution for your problem if you need a bullet proof exactly-once solution.
Another alternative for distributed locking is Redis cluster, which can also be provisioned with AWS ElasticCache. Redis supports transactions which guarantee that concurrent calls will get executed in sequence.
One of the advantages of using cache is that you can set expiration timeouts, so if your message processing fails the lock will get timed release.
In this blog post the usage of a low-latency control database like Amazon DynamoDB is also recommended:
https://aws.amazon.com/blogs/compute/new-for-aws-lambda-sqs-fifo-as-an-event-source/
Amazon SQS FIFO queues ensure that the order of processing follows the
message order within a message group. However, it does not guarantee
only once delivery when used as a Lambda trigger. If only once
delivery is important in your serverless application, it’s recommended
to make your function idempotent. You could achieve this by tracking a
unique attribute of the message using a scalable, low-latency control
database like Amazon DynamoDB.
In short - we can put item or update item in dynamodb table with condition expretion attribute_not_exists(for put) or if_not_exists(for update), please check example here
https://stackoverflow.com/a/55110463/9783262
If we get an exception during put/update operations, we have to return from a lambda without further processing, if not get it then process the message (https://aws.amazon.com/premiumsupport/knowledge-center/lambda-function-idempotent/)
The following resources were helpful for me too:
https://ably.com/blog/sqs-fifo-queues-message-ordering-and-exactly-once-processing-guaranteed
https://aws.amazon.com/blogs/aws/introducing-amazon-sns-fifo-first-in-first-out-pub-sub-messaging/
https://youtu.be/8zysQqxgj0I