C_CPI Integration Suite Development Practice Question
An integration developer is building an integration flow in SAP Cloud Integration that reads a large IDoc XML payload and must split it into individual IDoc messages before mapping each one to a JSON structure for a non-SAP receiver. The developer wants to avoid loading the entire payload into memory at once and needs each split message to retain the original message headers. Which approach is most appropriate?
⚠ Common exam trap
The trap here is assuming that a one-to-many Message Mapping or a Multicast can split a single payload into separate messages, when splitting is actually performed by a Splitter component.
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
✓
Use a General Splitter with XPath /IDOC, set the Streaming option, and enable the Splitter's ability to keep headers; then map each split message individually.
For large repeating XML structures, a General Splitter with an XPath expression creates one message per matched element. Streaming the split avoids holding the entire document, and retaining headers keeps correlation context available for later steps. This combination is the standard way to process each IDoc independently and then map it to JSON for the receiver.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Use a Message Mapping with a one-to-many mapping to generate multiple target messages from the single source IDoc payload.
Why it's wrong here
A Message Mapping produces one target message per mapping execution; one-to-many refers to generating multiple target nodes within a single message, not multiple messages. It does not split the incoming payload into separate messages that can be routed individually. This would not meet the requirement to process each IDoc as its own message with retained headers.
- ✗
Use a Multicast with parallel processing and a Content Modifier that extracts each IDoc using XPath before mapping.
Why it's wrong here
Multicast replicates the same incoming message to multiple branches; it does not iterate over repeating elements in the payload. A Content Modifier with XPath could extract one IDoc, but it would not automatically produce one branch per IDoc. This design would require additional logic and still risks loading the full payload, so it does not address the requirement.
- ✗
Use an XML to JSON converter on the whole payload and then a Content Modifier to loop over the array with a Groovy script.
Why it's wrong here
Converting the entire large XML to JSON first loads the full document into memory and produces a single large JSON message, which contradicts the goal of processing individual IDocs without holding everything in memory. A Groovy loop would still operate on that large object. This approach also does not naturally preserve original message headers across the loop iterations.
- ✓
Use a General Splitter with XPath /IDOC, set the Streaming option, and enable the Splitter's ability to keep headers; then map each split message individually.
Why this is correct
The General Splitter with an XPath expression targeting /IDOC creates one message per IDoc element. Enabling streaming avoids materializing the full document in memory, which matters for large payloads. Preserving headers on the split messages ensures correlation and other context survives, so downstream mapping and receiver calls can rely on them. This directly satisfies the memory and header-retention requirements.
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JA
Written and reviewed by Johnson Ajibi, MSc IT Security
Senior Network & Security Engineer · founder of Courseiva
Last reviewed September 2026 · checked against the official SAP exam blueprint
This C_CPI practice question is part of Courseiva's free SAP certification practice question bank. Courseiva provides original exam-style practice questions with explanations, topic-based practice, mock exams, readiness tracking, and study analytics to help learners prepare for the C_CPI exam.