kafka-exactly-once | Usage examples for the Kafka createDirectStream
kandi X-RAY | kafka-exactly-once Summary
kandi X-RAY | kafka-exactly-once Summary
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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QUESTION
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 20:23If 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
QUESTION
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 14:52When 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.
QUESTION
I need to apply transactions in a system that comprises of below components:
- A Kafka producer, this is some external application which would publish messages on a kafka topic.
- 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 14:38in 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.
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