batched

Available in: Cloud, Self-Managed

Consumes data from a child input and applies a batching policy to the stream.

Introduced in version 4.11.0.

  • Common

  • Advanced

# Common config fields, showing default values
input:
  label: ""
  batched:
    child: null # No default (required)
    policy:
      count: 0
      byte_size: 0
      period: ""
      check: ""
# All config fields, showing default values
input:
  label: ""
  batched:
    child: null # No default (required)
    policy:
      count: 0
      byte_size: 0
      period: ""
      check: ""
      processors: [] # No default (optional)

Batching at the input level is sometimes useful for processing across micro-batches, and can also sometimes be a useful performance trick. However, most inputs are fine without it so unless you have a specific plan for batching this component is not worth using.

Fields

child

The child input.

Type: input

policy

Allows you to configure a batching policy.

Type: object

# Examples

policy:
  byte_size: 5000
  count: 0
  period: 1s

policy:
  count: 10
  period: 1s

policy:
  check: this.contains("END BATCH")
  count: 0
  period: 1m

policy.count

A number of messages at which the batch should be flushed. If 0 disables count based batching.

Type: int

Default: 0

policy.byte_size

An amount of bytes at which the batch should be flushed. If 0 disables size based batching.

Type: int

Default: 0

policy.period

A period in which an incomplete batch should be flushed regardless of its size.

Type: string

Default: ""

# Examples

period: 1s

period: 1m

period: 500ms

policy.check

A Bloblang query that should return a boolean value indicating whether a message should end a batch.

Type: string

Default: ""

# Examples

check: this.type == "end_of_transaction"

policy.processors

A list of processors to apply to a batch as it is flushed. This allows you to aggregate and archive the batch however you see fit. Please note that all resulting messages are flushed as a single batch, therefore splitting the batch into smaller batches using these processors is a no-op.

Type: array

# Examples

processors:
  - archive:
      format: concatenate

processors:
  - archive:
      format: lines

processors:
  - archive:
      format: json_array