![]() The mechanism does not have any requirements about the number of topic partitions as the repository consumes from all partitions at the same time. The topic used must be unique per idempotent repository instance. This repository stores broadcasts all changes to idempotent state (add/remove) in a Kafka topic, and populates a local in-memory cache for each repository’s process instance through event sourcing. The camel-kafka library provides a Kafka topic-based idempotent repository. Allowing retries while setting enable.idempotence to false and max.in. to 1 will potentially change the ordering of records because if two batches are sent to a single partition, and the first fails and is retried but the second succeeds, then the records in the second batch may appear first. If conflicting configurations are set and idempotence is not explicitly enabled, idempotence is disabled. Enabling idempotence requires this config value to be greater than 0. Users should generally prefer to leave this config unset and instead use to control retry behavior. Produce requests will be failed before the number of retries has been exhausted if the timeout configured by expires first before successful acknowledgement. ![]() Note that this retry is no different than if the client resent the record upon receiving the error. ![]() Setting a value greater than zero will cause the client to resend any record whose send fails with a potentially transient error. Note that enabling idempotence requires this config value to be 'all'. This is equivalent to the acks=-1 setting. This is the strongest available guarantee. This guarantees that the record will not be lost as long as at least one in-sync replica remains alive. acks=all This means the leader will wait for the full set of in-sync replicas to acknowledge the record. In this case should the leader fail immediately after acknowledging the record but before the followers have replicated it then the record will be lost. acks=1 This will mean the leader will write the record to its local log but will respond without awaiting full acknowledgement from all followers. The offset given back for each record will always be set to -1. No guarantee can be made that the server has received the record in this case, and the retries configuration will not take effect (as the client won’t generally know of any failures). The record will be immediately added to the socket buffer and considered sent. The following settings are allowed: acks=0 If set to zero then the producer will not wait for any acknowledgment from the server at all. ![]() This controls the durability of records that are sent. The number of acknowledgments the producer requires the leader to have received before considering a request complete. Setting linger.ms=5, for example, would have the effect of reducing the number of requests sent but would add up to 5ms of latency to records sent in the absense of load. This setting gives the upper bound on the delay for batching: once we get batch.size worth of records for a partition it will be sent immediately regardless of this setting, however if we have fewer than this many bytes accumulated for this partition we will 'linger' for the specified time waiting for more records to show up. This can be thought of as analogous to Nagle’s algorithm in TCP. This setting accomplishes this by adding a small amount of artificial delay that is, rather than immediately sending out a record the producer will wait for up to the given delay to allow other records to be sent so that they can be batched together. However in some circumstances the client may want to reduce the number of requests even under moderate load. Normally this occurs only under load when records arrive faster than they can be sent out. The producer groups together any records that arrive in between request transmissions into a single batched request.
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |