C_CPI Integration Suite Development Practice Question
An integration developer must split a large XML payload into individual messages and process them in parallel, but the order of the resulting records in the target system does not matter. The developer wants the split messages to be handled concurrently rather than sequentially. Which configuration on the Splitter step should the developer use?
⚠ Common exam trap
Many candidates confuse the Parallel Multicast step, which fans out copies of one message, with the Splitter's parallel processing mode, which fans out the split elements themselves.
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
✓
Set the Splitter's processing mode to Parallel Processing on the split elements
When split records are independent and ordering is irrelevant, the Splitter's parallel processing mode is the correct lever. It emits one message per repeating element and hands those messages to multiple threads, raising throughput. Sequential mode, multicast, extra worker nodes, or a Gather step do not introduce the required element-level concurrency.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Set the Splitter to sequential processing and rely on the Parallel Multicast step instead
Why it's wrong here
The Parallel Multicast step routes copies of the same message to multiple branches; it does not divide a single repeating structure into one message per element. Using an XML Splitter sequentially and then a multicast would still process elements one after another on the split path, so the concurrency goal is not met for the split records.
- ✗
Set the Splitter to sequential processing and add a Gather step after it
Why it's wrong here
A Gather step collects messages back together after parallel branches; it is used with parallel processing, not as a way to create concurrency. Applying it after a sequential Splitter does nothing to parallelize the records and only recombines them, leaving the original performance problem unsolved.
- ✗
Set the Splitter to sequential processing and increase the tenant's worker node count
Why it's wrong here
Adding worker nodes increases the tenant's overall capacity but does not change the fact that a sequential Splitter processes messages one at a time on a single path. The split records remain serialized, so the concurrency requirement is not satisfied regardless of node count.
- ✓
Set the Splitter's processing mode to Parallel Processing on the split elements
Why this is correct
The Splitter step supports a parallel processing mode that distributes the split messages to multiple worker threads. Because the target does not require ordering, parallel processing is appropriate and yields higher throughput, while the Splitter still emits one message per repeating element as required.
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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
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