Benthos processors are functions applied to messages passing through a pipeline. The function signature allows a processor to mutate or drop messages depending on the content of the message. There are many types on offer but the most powerful is the
Processors are set via config, and depending on where in the config they are placed they will be run either immediately after a specific input (set in the input section), on all messages (set in the pipeline section) or before a specific output (set in the output section). Most processors apply to all messages and can be placed in the pipeline section:
pipeline: threads: 1 processors: - label: my_cool_mapping bloblang: | root.message = this root.meta.link_count = this.links.length()
threads field in the pipeline section determines how many parallel processing threads are created. You can read more about parallel processing in the pipeline guide.
Processors have an optional field
label that can uniquely identify them in observability data such as metrics and logs. This can be useful when running configs with multiple nested processors, otherwise their metrics labels will be generated based on their composition. For more information check out the [metrics documentation][metrics.about].
Processors that interact with external services.aws_dynamodb_partiqlaws_lambdacachehttpmongodbredisschema_registry_decodesqlsubprocess
Processors that specialize in translating messages from one format to another.archiveavrobloblangcompressdecompressgrokparse_logprotobufschema_registry_decodeunarchivexml
Higher level processors that compose other processors and modify their behavior.branchcatchfor_eachgroup_bygroup_by_valueinsert_partparallelswitchtrywhileworkflow
Some processors have conditions whereby they might fail. Rather than throw these messages into the abyss Benthos still attempts to send these messages onwards, and has mechanisms for filtering, recovering or dead-letter queuing messages that have failed which can be read about here.
All Benthos processors support multiple part messages, which are synonymous with batches. This enables some cool windowed processing capabilities.
Many processors are able to perform their behaviours on specific parts of a message batch, or on all parts, and have a field
parts for specifying an array of part indexes they should apply to. If the list of target parts is empty these processors will be applied to all message parts.
Part indexes can be negative, and if so the part will be selected from the end counting backwards starting from -1. E.g. if part = -1 then the selected part will be the last part of the message, if part = -2 then the part before the last element will be selected, and so on.
You can read more about batching in this document.