kafka-exactly-once | Usage examples for the Kafka createDirectStream

 by   koeninger Scala Version: Current License: No License

kandi X-RAY | kafka-exactly-once Summary

kandi X-RAY | kafka-exactly-once Summary

kafka-exactly-once is a Scala library typically used in Big Data, Kafka, Spark applications. kafka-exactly-once has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.

Master corresponds to Spark 2.0 / Kafka 0.10. If you’re looking for earlier versions, see the [Spark 1.6 branch] For more detail, see the [presentation] or the [blog post] or the [slides] or the [jira ticket] If you want to try running this,. schema.sql contains postgres schemas for the tables used. src/main/resources/application.conf contains jdbc and kafka config info. The examples are indifferent to the exact kafka topic or message format used, although IdempotentExample assumes each message body is unique.
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              kafka-exactly-once has a low active ecosystem.
              It has 248 star(s) with 92 fork(s). There are 19 watchers for this library.
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              It had no major release in the last 6 months.
              There are 4 open issues and 8 have been closed. On average issues are closed in 62 days. There are no pull requests.
              It has a neutral sentiment in the developer community.
              The latest version of kafka-exactly-once is current.

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              kafka-exactly-once has no bugs reported.

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              kafka-exactly-once has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

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              kafka-exactly-once does not have a standard license declared.
              Check the repository for any license declaration and review the terms closely.
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              Without a license, all rights are reserved, and you cannot use the library in your applications.

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              kafka-exactly-once releases are not available. You will need to build from source code and install.

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            kafka-exactly-once Examples and Code Snippets

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            Community Discussions

            QUESTION

            Kafka: isolation level implications
            Asked 2020-Feb-27 at 15:43

            I have a use case where I need 100% reliability, idempotency (no duplicate messages) as well as order-preservation in my Kafka partitions. I'm trying to set up a proof of concept using the transactional API to achieve this. There is a setting called 'isolation.level' that I'm struggling to understand.

            In this article, they talk about the difference between the two options

            There are now two new isolation levels in Kafka consumer:

            read_committed: Read both kind of messages that are not part of a transaction and that are, after the transaction is committed. Read_committed consumer uses end offset of a partition, instead of client-side buffering. This offset is the first message in the partition belonging to an open transaction. It is also known as “Last Stable Offset” (LSO). A read_committed consumer will only read up till the LSO and filter out any transactional messages which have been aborted.

            read_uncommitted: Read all messages in offset order without waiting for transactions to be committed. This option is similar to the current semantics of a Kafka consumer.

            The performance implication here is obvious but I'm honestly struggling to read between the lines and understand the functional implications/risk of each choice. It seems like read_committed is 'safer' but I want to understand why.

            ...

            ANSWER

            Answered 2019-May-08 at 20:23

            If you are not using transactions in your producer, the isolation level does not matter. If you are, then you must use read_committed if you want the consumers to honor the transactional nature. Here are some additional references:

            https://www.confluent.io/blog/transactions-apache-kafka/ https://docs.google.com/document/d/11Jqy_GjUGtdXJK94XGsEIK7CP1SnQGdp2eF0wSw9ra8/edit

            Source https://stackoverflow.com/questions/56047968

            QUESTION

            Confused about preventing duplicates with new Kafka idempotent producer API
            Asked 2019-Aug-24 at 11:05

            My app has 5+ consumers consuming off of five partitions on a kafka topic.(using kafka version 11) My consumer's each produce a message to another topic then save some state to the database, then do a manual_ immediate acknowledgement and move onto the next message.

            I'm trying to solve the scenario when they emit successful to the outbound topic. then we have a failure/lose the consumer. When another consumer takes over the partition it will emit ANOTHER message to the outbound topic. This is bad :(

            I discovered that kafka now has idempotent producers but from what I read it only guarantees for a producers session.

            "When producer restarts, new PID gets assigned. So the idempotency is promised only for a single producer session" - (blog) - https://hevodata.com/blog/kafka-exactly-once

            This seems largely useless to me. In my use-case the whole point is when I replay a message on another consumer it does not duplicate the outbound message.

            Is there something i'm missing?

            ...

            ANSWER

            Answered 2018-Aug-14 at 14:52

            When using transactions, you shouldn't use ANY consumer-based mechanism, manual or otherwise, to commit the offsets.

            Instead, you use the producer to send the offsets to the transaction so the offset commit is part of the transaction.

            If configured with a KafkaTransactionManager, or ChainedKafkaTransactionManager the Spring listener container will send the offsets to the transaction when the listener exits normally.

            If you don't use a Kafka transaction manager, you need to use the KafkaTemplate (or Producer if you are using the native APIs) to send the offsets to the transaction.

            Using the consumer to commit the offset is not part of the transaction, so things will not work as expected.

            When using a transaction manager, the listener container binds the Producer to the thread so any downstream KafkaTemplate operations participate in the transaction that the consumer starts. See the documentation.

            Source https://stackoverflow.com/questions/51832074

            QUESTION

            Exactly-once semantics in spring Kafka
            Asked 2019-May-28 at 17:39

            I need to apply transactions in a system that comprises of below components:

            1. A Kafka producer, this is some external application which would publish messages on a kafka topic.
            2. A Kafka consumer, this is a spring boot application where I have configured the kafka listener and after processing the message, it needs to be saved to a NoSQL database.

            I have gone through several blogs like this & this, and all of them talks about the transactions in context of streaming application, where the messages would be read-processed-written back to a Kafka topic.

            I don't see any clear example or blog around achieving transactionality in the use case similar to mine i.e. producing-processing-writing to a DB in a single atomic transaction. I believe it to be very common scenario & there must be some support for it as well.

            Can someone please guide me on how to achieve this? Any relevant code snippet would be greatly appreciated.

            ...

            ANSWER

            Answered 2019-Apr-04 at 14:38

            in a single atomic transaction.

            There is no way to do it; Kafka doesn't support XA transactions (nor do most NoSQL DBs). You can use Spring's transaction synchronization for best-effort 1PC.

            See the documentation.

            Spring for Apache Kafka implements normal Spring transaction synchronization.

            It provides "best efforts 1PC" - see Distributed transactions in Spring, with and without XA for more understanding and the limitations.

            Source https://stackoverflow.com/questions/55510121

            Community Discussions, Code Snippets contain sources that include Stack Exchange Network

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