The batch processor accepts spans, metrics, or logs and places them into batches. Batching helps better compress the data and reduce the number of outgoing connections required to transmit the data. This processor supports both size and time based batching.

It is highly recommended to configure the batch processor on every collector. The batch processor should be defined in the pipeline after the memory_limiter as well as any sampling processors. This is because batching should happen after any data drops such as sampling.

Please refer to config.go for the config spec.

The following configuration options can be modified:

• send_batch_size (default = 8192): Number of spans, metric data points, or log records after which a batch will be sent regardless of the timeout.
• timeout (default = 200ms): Time duration after which a batch will be sent regardless of size.
• send_batch_max_size (default = 0): The upper limit of the batch size. 0 means no upper limit of the batch size. This property ensures that larger batches are split into smaller units. It must be greater than or equal to send_batch_size.

Examples:

processors:
  batch:
  batch/2:
    send_batch_size: 10000
    timeout: 10s

Refer to config.yaml for detailed examples on using the processor.