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QUESTION
I am just curious does batch listener mode in Spring Kafka gives better performance than non-batch listener mode? If we are handling exceptions then we still need to process each record in Batch-listener mode. Non-batch seems less error prone, stable and customizable .
Please share your views on this as I didn't find any good comparison.
...ANSWER
Answered 2021-Jun-15 at 20:19It completely depends on what your listener is doing with the data.
If it processes each record in a loop then there is no benefit; you might as well just let the container iterate over the collection and send the listener one record at-a-time.
Batch mode will improve performance if you are processing the batch as a whole - e.g. a batch insert using JDBC in a single transaction.
This will often run much faster than storing one record at-a-time (using a new transaction for each record) because it requires fewer round trips to the DB server.
QUESTION
I have a Spring Boot app with a Kafka Listener implementing the BatchAcknowledgingMessageListener interface. When I receive what should be a single message from the topic, it's actually one message for each line in the original message, and I can't cast the message to a ConsumerRecord.
The code producing the record looks like this:
...ANSWER
Answered 2021-Jun-15 at 17:48You are missing the listener type configuration so the default conversion service sees you want a list and splits the string by commas.
QUESTION
I am trying to figure out is there any way to send failed records in Dead Letter topic in Spring Boot Kafka in Batch mode. I don't want to make the records being sent in duplicate as it's consuming in batch and few are already processed. I saw this link ofspring-kafka consumer batch error handling with spring boot version 2.3.7
I thought about a use case to stop container and start again without using DLT but again the issue of duplication will come in Batch mode.
@Garry Russel can you please provide a small code for batch error handling.
...ANSWER
Answered 2021-Jun-15 at 17:34The RetryingBatchErrorHandler
was added in spring-kafka version 2.5 (which comes with Boot 2.3).
The listener must throw an exception to indicate which record in the batch failed (either the complete record, or the index in the list).
Offsets for the records before the failed one are committed and the failed record can be retried and/or sent to the dead letter topic.
See https://docs.spring.io/spring-kafka/docs/current/reference/html/#recovering-batch-eh
There is a small example there.
The RetryingBatchErrorHandler
was added in 2.3.7, but it sends the entire batch to the dead letter topic, which is typically not what you want (hence we added the RetryingBatchErrorHandler
).
QUESTION
How can I execute the below in a transaction. My requirement is message offset should not be committed to Kafka if the DB calls fails .Kafka consumer configuration is here https://pastebin.com/kq5S9Jrx
...ANSWER
Answered 2021-Jun-15 at 13:38Move
QUESTION
This probably ins't typical setup, but due to higher decisions we endup having multiple kafka clusters within one app, multiple topics per each, and each might have different serializing strategy. Json/avro. And avro might be with confluent schema registry or using single object encoding.
Well I got it working somehow, by building my own abstractions and registry which analyzes the configuration and creates most of stuff manually, but I feel I needed to repeat stuff like topic names, schema registry url on several places multiple times just to create all needed beans. Ugly as hell.
I'd like to ask, if there is some better way and support for this I just might have overlooked.
I need to create N representations of kafka clusters, configuring it once. Configure topics respective to given kafka cluster, configure confluent schema registry for topics where applicable etc, so that I can create instance of Avro schema file, send it to KafkaTemplate and it will work.
...ANSWER
Answered 2021-Jun-15 at 13:28It depends on the complexity and how much different the configurations are, as to whether this will help, but you can override individual Kafka properties (such as bootstrap servers, deserializers, etc on the @KafkaListener
and in each KafkaTemplate
.
e.g.
QUESTION
I need a way to force the compaction of the __consumer_offsets topic. In a test environment I tried to delete the file cleaner-offset-checkpoint and then kafka deleted many segments as you can see below. Is it safe to delete this file in a production environment?
Before removing cleaner-offset-checkpoint:
...ANSWER
Answered 2021-Jun-15 at 13:24cleaner-offset-checkpoint
is in kafka logs directory. This file keeps the last cleaned offset
of the topic partitions in the broker like below.
QUESTION
We want to replace the path on /etc/fstab
file from
ANSWER
Answered 2021-Jun-15 at 06:45The following 'awk' could assist you here
QUESTION
I followed the instructions at Structured Streaming + Kafka and built a program that receives data streams sent from kafka as input, when I receive the data stream I want to pass it to SparkSession variable to do some query work with Spark SQL, so I extend the ForeachWriter class again as follows:
...ANSWER
Answered 2021-Jun-15 at 04:42do some query work with Spark SQL
You wouldn't use a ForEachWriter for that
QUESTION
I am using the SQL connector to capture CDC on a table that we only expose a subset of all columns on the table. The table has two unique indexes A & B on it. Neither index is marked as the PRIMARY INDEX but index A is logically the primary key in our product and what I want to use with the connector. Index B references a column we don't expose to CDC. Index B isn't truly used in our product as a unique key for the table and it is only marked UNIQUE as it is known to be unique and marking it gives us a performance benefit.
This seems to be resulting in the error below. I've tried using the message.key.columns
option on the connector to specify index A as the key for this table and hopefully ignore index B. However, the connector seems to still want to do something with index B
- How can I work around this situation?
- For my own understanding, why does the connector care about indexes that reference columns not exposed by CDC?
- For my own understanding, why does the connector care about any index besides what is configured on the CDC table i.e. see CDC.change_tables.index_name documentation
ANSWER
Answered 2021-Jun-14 at 17:35One of the contributors to Debezium seems to affirm this is a product bug https://gitter.im/debezium/user?at=60b8e96778e1d6477d7f40b5. I have created an issue https://issues.redhat.com/browse/DBZ-3597.
Edit:
A PR was published and approved to fix the issue. The fix is in the current 1.6 beta snapshot build.
There is a possible workaround. The names of indices are the key to the problem. It seems they are processed in alphabetical order. Only the first one is taken into consideration so if you can rename your indices to have the one with keys first then you should get unblocked.
QUESTION
spring-kafka
creates a ValueSerializer
instance in the AbstractConfig
class using a no-args constructor.
I can see that JsonSerializer
has an ObjectMapper
constructor which I would like to use to inject a preconfigured ObjectMapper
bean.
The default ObjectMapper
includes null
values in the response which I would like to remove. I added spring.jackson.default-property-inclusion: NON_EMPTY
to my properties.yml
but since Spring creates a default instance, this does not help me.
Could someone point me in the right direction?
...ANSWER
Answered 2021-Jun-14 at 14:16I think you are on the right lines but ay have set the property incorrectly. I think you wanted
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