Mule Concepts

- At the simplest level, Mule applications accept and process events as messages through several message processors plugged together in a flow.- Large or streaming messages can be processed as records in a batch job- Essentially every Mule flow contains a series of message processors that accept, then process messages

=> Understanding the basic flow architecture and batch job structure is key to understanding Mule

Flow• A flow is the construct within which you link together several

individual elements to handle the receipt, processing, and eventual routing of a message.• You can connect many flows together to build a complete application

which you can then deploy on premise, on Mule or another application server, or in the cloud.• The units with which flows are constructed are known generically

as building blocks (in Studio’s graphical representation of a flow) or elements (in XML configuration).

Flow

Building blocks Elements

Flow

Flow

Batch Jobs• A batch job is a top-level element in Mule which exists outside all

Mule flows. • Batch jobs split large messages into records which Mule processes

asynchronously.• You can initiate a batch job which is a block of code that splits

messages into individual records, performs actions upon each record, then reports on the results and potentially pushes the processed output to other systems or queues.

Batch Jobs

Batch Jobs• Batch processing is particularly useful when working with the

following scenarios: • Integrating data sets, small or large, streaming or not, to parallel process

records• Synchronizing data sets between business applications. • Extracting, transforming and loading (ETL) information into a target system,

such as uploading data from a flat file (CSV) to Hadoop• Handling large quantities of incoming data from an API into a legacy system

Message Sources• Mule processes messages (i.e. events) initiated in external resources• The first building block of most flows or batch jobs is a receiver which

receives new messages and places them in the queue for processing.• This message source – an inbound HTTP endpoint – receives

messages from one or more external sources, thus triggering the execution of a flow or batch job• Message sources in Mule are usually Anypoint Connectors, elements

which provide connectivity to a specific external source, either via a standard protocol or a third-party API.

Message Processors• In Mule, message processors are grouped together by category.• Mule transformers are the key to exchanging data between nodes, as they

allow Mule to convert message payload data to a format that another application can understand • Mule uses components to conduct backend processes for specific business

logic such as checking customer and inventory databases. Components route messages to the correct application.• Mule includes a variety of filters, scopes, and routers to customize how a flow

or batch job processes messages

Mule Message Structure

• The Mule message is the data that passes through an application via one or more flows. It consists of two main parts:• The message header, which contains metadata about the• The message payload, which contains your business-specific data.

Mule Message Structure

• Batch processing is particularly useful when working with the following scenarios: • Integrating data sets, small or large, streaming or not, to parallel process

records• Synchronizing data sets between business applications. • Extracting, transforming and loading (ETL) information into a target system,

such as uploading data from a flat file (CSV) to Hadoop• Handling large quantities of incoming data from an API into a legacy system

Mule Message StructureHeader:• The metadata contained in the message header consists

of properties which provide useful information about the message. • Contained within the message object, variables represent data about

a message.

Mule Message StructureHeader:• Properties have two main scopes: inbound and outbound. • Inbound properties are immutable, are automatically

generated by the message source and cannot be set or manipulated by the user.• A message retains its inbound properties only for the duration

of the flow; when a message passes out of a flow, its inbound properties do not follow it

Mule Message Structure Header:• Outbound properties are mutable, they contain metadata similar

to that of an inbound property, but an outbound property is applied after the message enters the flow.• Outbound properties can be set automatically by Mule or a user

can set them by manually inserting one or more transformer elements in the flow• If the message is passed to a new flow via a flow-ref rather than a

connector, the outbound properties remain outbound properties rather than being converted to inbound properties

Mule Message Structure Header:• Variables are user-defined metadata about a message. Variables

have three scopes: • Flow variables apply only to the flow in which they exist. • Session variables apply across all flows within the same application.• Record variables apply only to records processed as part of a batch.

Mule Message Structure Message Payload:• The message payload is the most important part of the Mule

message because it contains the data your Mule application processes • The payload doesn’t necessarily stay flow the same as it travels through a

flow. Various message processors in a Mule can affect the payload along the way by setting it, enriching, or transforming it into a new format. You can also extract information from a payload within a flow using a MEL expression