C_CPI Integration Suite Development Practice Question
An integration developer is building an integration flow in SAP Cloud Integration that must process a large flat-file payload. The flow uses a Splitter with an XML path expression to divide the message into individual records. After splitting, each record must be processed in parallel to reduce total runtime, and the original message must be reassembled before the flow completes. Which configuration achieves this requirement?
⚠ Common exam trap
The trap here is assuming that a Splitter automatically reassembles messages after parallel processing, when an explicit Gather step is required.
Answer choices
Why each option matters
Answer the question above first, then reveal the full breakdown to understand why each option is right or wrong.
Correct answer & explanation
✓
Configure the Splitter with Parallel Processing enabled and define a Gather step with an appropriate timeout and aggregation expression.
Parallel processing on the Splitter distributes each split record to concurrent branches, reducing total processing time for large payloads. Reassembling the original message after these branches requires an explicit Gather step, which collects the individual messages and applies an aggregation expression and timeout. Together, parallel processing plus Gather satisfy both the performance and reassembly requirements in a single, supported configuration.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✓
Configure the Splitter with Parallel Processing enabled and define a Gather step with an appropriate timeout and aggregation expression.
Why this is correct
Enabling parallel processing on the Splitter causes the subsequent steps to run concurrently for each split message, and the Gather step collects the individual results back into a single message. This directly satisfies both the performance and reassembly requirements, and the timeout prevents indefinite waiting if one branch stalls.
- ✗
Configure the Splitter with Sequential Processing and rely on the built-in automatic aggregation that reassembles messages after sequential processing.
Why it's wrong here
Sequential processing does not provide parallel execution, so the runtime improvement is lost. SAP Cloud Integration's Splitter does not automatically reassemble messages after processing in the way described; aggregation requires an explicit Gather step. Relying on implied automatic aggregation would leave the flow without a defined reassembly point and could break downstream steps.
- ✗
Configure the Splitter with Parallel Processing enabled and add a Content Modifier step to merge the split messages after processing.
Why it's wrong here
A Content Modifier only sets headers, properties, or the body of a single message; it cannot collect multiple split messages back into one. Parallel processing alone produces multiple messages, and without a Gather step there is no aggregation, so the original message is never reassembled and downstream steps would receive multiple messages.
- ✗
Configure the Splitter with Sequential Processing and add a Multicast step after it to run the branches in parallel.
Why it's wrong here
Sequential processing on the Splitter processes one record at a time, which defeats the parallel runtime goal. Adding a Multicast after the Splitter does not reassemble the split messages through the splitter's own aggregation mechanism, and Multicast has its own parallel semantics that do not guarantee reassembly of the original message in this context.
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Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official SAP exam blueprint
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