redpanda_common

Beta

Consumes data from a Redpanda (Kafka) broker, using credentials from a common redpanda configuration block.

To avoid duplicating Redpanda cluster credentials in your redpanda_common input, output, or any other components in your data pipeline, you can use a single redpanda configuration block. For more details, see the Pipeline example.

Introduced in version 4.39.0.

If you need to move topic data between Redpanda clusters or other Apache Kafka clusters, consider using the redpanda input and output instead.
  • Common

  • Advanced

# Common configuration fields, showing default values
input:
  label: ""
  redpanda_common:
    topics: [] # No default (required)
    regexp_topics: false
    consumer_group: "" # No default (optional)
    auto_replay_nacks: true
# All configuration fields, showing default values
input:
  label: ""
  redpanda_common:
    topics: [] # No default (required)
    regexp_topics: false
    rack_id: ""
    start_from_oldest: true
    fetch_max_bytes: 50MiB
    fetch_min_bytes: 1B
    fetch_max_partition_bytes: 1MiB
    consumer_group: "" # No default (optional)
    commit_period: 5s
    partition_buffer_bytes: 1MB
    auto_replay_nacks: true

Pipeline example

This data pipeline reads data from topic_A and topic_B on a Redpanda cluster, and then writes the data to topic_C on the same cluster. The cluster details are configured within the redpanda configuration block, so you only need to configure them once. This is a useful feature when you have multiple inputs and outputs in the same data pipeline that need to connect to the same cluster.

input:
  redpanda_common:
    topics: [ topic_A, topic_B ]

output:
  redpanda_common:
    topic: topic_C
    key: ${! @id }

redpanda:
  seed_brokers: [ "127.0.0.1:9092" ]
  tls:
    enabled: true
  sasl:
    - mechanism: SCRAM-SHA-512
      password: bar
      username: foo

Consumer groups

When you specify a consumer group in your configuration, this input consumes one or more topics and automatically balances the topic partitions across any other connected clients with the same consumer group. Otherwise, topics are consumed in their entirety or with explicit partitions.

Delivery guarantees

If you choose to use consumer groups, the offsets of records received by Redpanda Connect are committed automatically. In the event of restarts, this input uses the committed offsets to resume data consumption where it left off.

Redpanda Connect guarantees at-least-once delivery. Records are only confirmed as delivered when all downstream outputs that a record is routed to have also confirmed delivery.

Ordering

To preserve the order of topic partitions:

  • Records consumed from each partition are processed and delivered in the order that they are received

  • Only one batch of records of a given partition is processed at a time

This approach means that although records from different partitions may be processed in parallel, records from the same partition are processed in sequential order.

Delivery errors

The order in which records are delivered may be disrupted by delivery errors and any error-handling mechanisms that start up. Redpanda Connect uses at-least-once delivery unless instructed otherwise, and this includes reattempting delivery of data when the ordering of that data is no longer guaranteed.

For example, a batch of records is sent to an output broker and only a subset of records are delivered. In this scenario, Redpanda Connect (by default) attempts to deliver the records that failed, even though these delivery failures may have been sent before records that were delivered successfully.

Use a fallback output

To prevent delivery errors from disrupting the order of records, you must specify a fallback output in your pipeline configuration. When adding a fallback output, it is good practice to set the auto_retry_nacks field to false. This also improves the throughput of your pipeline.

For example, the following configuration includes a fallback output. If Redpanda Connect fails to write delivery errors to the foo topic, it then attempts to write them into a dead letter queue topic (foo_dlq), which is retried indefinitely as a way to apply back pressure.

output:
  fallback:
    - redpanda_common:
        topic: foo
    - retry:
        output:
          redpanda_common:
            topic: foo_dlq

Batching

Records are processed and delivered from each partition in the same batches as they are received from brokers. Batch sizes are dynamically sized in order to optimize throughput, but you can tune them further using the following configuration fields:

  • fetch_max_partition_bytes

  • fetch_max_bytes

You can break batches down further using the split processor.

Metadata

This input adds the following metadata fields to each message:

  • kafka_key

  • kafka_topic

  • kafka_partition

  • kafka_offset

  • kafka_timestamp_ms

  • kafka_timestamp_unix

  • kafka_tombstone_message

  • All record headers

Fields

topics

A list of topics to consume from. Use commas to separate multiple topics in a single element.

When a consumer_group is specified, partitions are automatically distributed across consumers of a topic. Otherwise, all partitions are consumed.

Alternatively, you can specify explicit partitions to consume by using a colon after the topic name. For example, foo:0 would consume the partition 0 of the topic foo. This syntax supports ranges. For example, foo:0-10 would consume partitions 0 through to 10 inclusive.

It is also possible to specify an explicit offset to consume from by adding another colon after the partition. For example, foo:0:10 would consume the partition 0 of the topic foo starting from the offset 10. If the offset is not present (or remains unspecified) then the field start_from_oldest determines which offset to start from.

Type: array

# Examples

topics:
  - foo
  - bar

topics:
  - things.*

topics:
  - foo,bar

topics:
  - foo:0
  - bar:1
  - bar:3

topics:
  - foo:0,bar:1,bar:3

topics:
  - foo:0-5

regexp_topics

Whether listed topics are interpreted as regular expression patterns for matching multiple topics. When topics are specified with explicit partitions, this field must remain set to false.

Type: bool

Default: false

rack_id

A rack specifies where the client is physically located, and changes fetch requests to consume from the closest replica as opposed to the leader replica.

Type: string

Default: ""

start_from_oldest

Whether to consume from the oldest available offset. Otherwise, messages are consumed from the latest offset. This setting is applied when creating a new consumer group or the saved offset no longer exists.

Type: bool

Default: true

fetch_max_bytes

The maximum number of bytes that a broker tries to send during a fetch.

If individual records are larger than the fetch_max_bytes value, brokers will still send them.

Type: string

Default: 50MiB

fetch_min_bytes

The minimum number of bytes that a broker tries to send during a fetch. This field is equivalent to the Java setting fetch.min.bytes.

Type: string

Default: 1B

fetch_max_partition_bytes

The maximum number of bytes that are consumed from a single partition in a fetch request. This field is equivalent to the Java setting fetch.max.partition.bytes.

If a single batch is larger than the fetch_max_partition_bytes value, the batch is still sent so that the client can make progress.

Type: string

Default: 1MiB

consumer_group

An optional consumer group. When this value is specified:

  • The partitions of any topics, specified in the topics field, are automatically distributed across consumers sharing a consumer group

  • Partition offsets are automatically committed and resumed under this name

Consumer groups are not supported when you specify explicit partitions to consume from in the topics field.

Type: string

commit_period

The period of time between each commit of the current partition offsets. Offsets are always committed during shutdown.

Type: string

Default: 5s

partition_buffer_bytes

A buffer size (in bytes) for each consumed partition, which allows the internal queuing of records before they are flushed. Increasing this value may improve throughput but results in higher memory utilization.

Each buffer can grow slightly beyond this value.

Type: string

Default: 1MB

auto_replay_nacks

Whether to automatically replay messages that are rejected (nacked) at the output level. If the cause of rejections is persistent, leaving this option enabled can result in back pressure.

Set auto_replay_nacks to false to delete rejected messages. Disabling auto replays can greatly improve memory efficiency of high throughput streams, as the original shape of the data is discarded immediately upon consumption and mutation.

Type: bool

Default: true