What is the impact on the performance of a large number of Kafka consumer groups?

Updated on technology 2024-08-06
2 answers
  1. Anonymous users2024-02-15

    Summary. If the consumption rate of Kafka is slow, you can try the following methods to tune it1Adjusting the Number of Consumer Instances Based on the Number of Topic PartitionsAs we all know, each partition of a topic can be consumed by only one instance in the consumer group in order to ensure the order of message consumption.

    If the number of partitions on your topic is 36, you can try to adjust the number of consumer instances to 36, of course, this is the case of consumer = 1. If you adjust the number of threads to n, your optimal number of consumer instances is. 2.

    If you enable Bulk Consumption, you can enable Bulk Consumption and set the number of Batch Consumption = 100, which is 5003 by defaultConsumers consume data in batches: Multithreaded processing: Consumers use thread pools to consume data in batches. It is recommended not to use execute, otherwise it is easy to get out of control, it is recommended to use submit and then get, and when get, it will wait for the thread to be executed, and this way will consume the batch and then consume it down.

    If the consumption rate of Kafka is slow, you can try the following methods to tune it1Adjusting the Number of Consumer Instances Based on the Number of Topic PartitionsAs we all know, each partition of a topic can be consumed by only one instance in the consumer group in order to ensure the order of message consumption. If the number of partitions on your topic is 36, you can try to adjust the number of consumer cases to 36, of course, this is the case of consumer = 1.

    If you adjust the number of threads to n, your optimal number of consumer instances is. 2.If you enable Bulk Consumption, you can enable Bulk Consumption and set the number of Batch Consumption = 100, which is 5003 by default

    Consumers consume data in batches: Multithreaded processing: Consumers use thread pools to consume data in batches. It is recommended not to use execute, otherwise it is easy to get out of control, it is recommended to use submit and then get, when get, it will laugh and wait for the thread to be executed, this way will consume the batch of this batch of consumption before consuming it down.

    In this case, the number of core threads in the thread pool needs to be determined according to whether the business is IO-intensive or CPU-intensive.

  2. Anonymous users2024-02-14

    at most onece modeThe basic idea is to ensure that each message is successfully committed, and then consumed.

    Set the automatic imitation of hidden ants to false, and after receiving the message, it will be committed first, and then consumed.

    at least onece mode.

    The basic idea is to ensure that each message is successfully processed before committing.

    Set auto-commit to false; After the message is processed, manually commit.

    When adopting this model, it is best to ensure the "idempotency" of consumption operations to prevent repeated consumption.

    Exactly onece mode.

    The core idea is to handle the OFFSET as a unique ID at the same time as the message, and to ensure the atomicity of the processing.

    Set the auto-withdrawal deficit to false; Submit the message after it is successfully processed.

    For example, for a buried relational database, you can set the id to the unique index of the message processing result, and if the index already exists when it is processed again, it will not be processed.

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