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However, it complicates mailbox management, despite the fact that proper mailbox managing is critical due to the loss of essential information secured in it. While checking for emails and the most recent emails in your MS Outlook inbox are duplicates of the same email, it’s frustrating. If our application is using Relational DB with transaction support, it’s easy to implement to introduce a new table, for example, PROCESSED_MESSAGE where we would store all message ids which is already processed.Summary: Nowadays, as we all know that Outlook is well-known for its refined features and useful techniques. We should avoid any attempt to reduce the customer credit balance twice or more. 2.2 Track all received messages and discard duplicatedĪs we already highlighted, that some of the commands couldn’t be completed in an idempotent manner.
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We need to come up with another way which is considered below. In this message handler, we should reduce a customer credit balance and this operation couldn’t be completed in an idempotent manner by its nature. Let’s assume, besides ORDER_CREATE, ORDER_MODIFY, and ORDER_CANCEL, we have a command ORDER_PAYMENT. Unfortunately, it’s not applicable for all cases. It’s like a PUT operation in RESTful API, which we should develop in an idempotent manner. For example, modify an already modified Order with the same payload should give the same result. The message handler is idempotent if calling it multiple times with the same payload has no additional effect.
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It’s the easiest way to have a deal with duplicate messages.
![remove duplicate messages remove duplicate messages](https://windows-cdn.softpedia.com/screenshots/Remove-Duplicate-Messages-for-Outlook_3.png)
There’re a couple of ways to handle duplicate messages: Therefore, we should keep in mind during the development that a Consumer may accept multiple times the same message. But it may handle some messages in batch and crash before sending acknowledge message to move offset, in this case, Kafka will resend all messages again and the consumer may handle one message twice But it’s not what we’re expecting to develop.įigure 4 - Consumer explicitly requests Kafka to move offset as soon as all messages are processed. In this case, Kafka guarantees that each message sends only once. If you set to true, it means that Kafka shifts offset as soon as it sends batched messages to Consumer - and doesn’t take care of whether Consumers handled messages or not. Kafka has a special configuration that defines how the offset should be changed. All messages behind offset are considered as handled and not delivered anymore to the particular consumer group. How does it work in Kafka? Kafka under the hood has a special cursor (offset). It means that if some failure happens during message processing, the message broker may deliver the same message several times. Instead, most message brokers promise to deliver a message at least once. For example, Consumer gets a message but shut down before making all necessary operations against DB, it leads that we leave some messages unhandled. Ideally, the message broker should send each message only once, but different failures may occur in Consumers during processing those messages. There’re different strategies for how messages should be delivered to a Consumer. For example, if you have 2 partitions and each message belongs to a particular client, you may divide all messages that all clients whose surname starts from letter belongs to range A-M should go to the first partition and for clients whose surname starts from N-Z should go to the second partition. In our case, I believe that the better choice for the key will be orderIdwhich is unique and stable and all commands across one order will be guaranty completed in one Consumer in an expected order.Īnother way to distribute messages across Partitions is to explicitly define to which partitions send the message. This means if we assign the same key for all commands ORDER_CREATE, ORDER_MODIFY, and ORDER_CANCEL, all of them will be sent to one partition and all of them will be sent to one Consumer in the same order. Kafka distributes them according to key hash: hashCode(key) % N where N - is a count of partitions. One of the ways is to assign a special key to the message. Kafka actually has several ways to define to which partition sends a message. Therefore, we should only take care that all commands ORDER_CREATE, ORDER_MODIFY, ORDER_CANCEL should be put in one Partition associated with the particular Order. In Kafka, the ordering is guaranteed for all messages in one Partition.