The Data Integration Service starts one or more Data Integration Service processes to manage requests to run mapping jobs in the Hadoop environment.
When you run mappings in the Hadoop environment, the following components run within the Data Integration Service process:
Mapping Service Module. The Mapping Service Module receives requests to run mappings from clients.
Logical Data Transformation Manager (LDTM). The LDTM compiles and optimizes mapping jobs, and it generates the execution workflow that is used to run a mapping on a Hadoop cluster.
Workflow Executor Service. The Workflow Executor Service is a part of the Data Transformation Manager (DTM). The Data Integration Service uses the Workflow Executor Service to push jobs to a Hadoop cluster.
The following diagram shows how the components interact with the client, the Hadoop cluster, and the Model Repository Service:
A client submits a mapping execution request to the Data Integration Service. The Mapping Service Module receives the request and stores the job in the queue.
The Mapping Service Module connects to the Model Repository Service to fetch mapping metadata from the Model repository.
The Mapping Service Module passes the mapping to the Logical Data Transformation Manager (LDTM).
The LDTM compiles the mapping and generates the Spark execution workflow. It stores the execution workflow in the Model repository.
The LTDM pushes the execution workflow through the Workflow Executor Service to the cluster for processing.
For more information about the architecture of a Data Integration Service, see the "Data Integration Service Architecture" chapter in the