ARA-C01 Data Engineering Practice Question
An architect is building a near-real-time pipeline that reads JSON events from a Kafka topic and must land them into Snowflake with sub-minute latency. The team has a Snowpipe streaming setup using the Snowflake Ingest SDK and writes to a table with a VARIANT column. They observe that the ingestion service occasionally reports channel errors and some events are missing after a client restart. Which configuration change best addresses the missing events?
⚠ Common exam trap
The trap here is assuming that adding channels or shortening the flush interval guarantees delivery, when recovery after a restart actually depends on persisting and replaying the channel's offset token.
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
✓
Enable offset token tracking and pass the last committed offset token when reopening the channel so the SDK resumes from the correct position.
Snowpipe streaming channels expose offset tokens that represent the client's progress in the source stream. Persisting the last committed token and supplying it when a channel is reopened lets the SDK resume from the correct position, closing the gap that would otherwise appear after a client restart. Throughput tuning and alternative ingestion methods do not solve the resume-position problem.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
Reduce the client's flush interval so that events are committed more frequently, eliminating the need to track positions across restarts.
Why it's wrong here
A shorter flush interval reduces the window of uncommitted data but does not remove the need to know where to resume; any event buffered between the last flush and the crash is still lost. Frequent flushing also increases overhead and can hurt throughput. Recovery still requires a durable position marker such as an offset token.
- ✗
Increase the number of channels per table and distribute events round-robin so that a single channel failure cannot drop data.
Why it's wrong here
Adding channels improves throughput and parallelism but does not provide recovery of uncommitted events after a restart, because each channel maintains its own position independently. A failed channel still loses the events that were not yet committed unless the client knows where to resume. More channels can even complicate recovery by multiplying the number of positions that must be tracked.
- ✓
Enable offset token tracking and pass the last committed offset token when reopening the channel so the SDK resumes from the correct position.
Why this is correct
Snowpipe streaming channels support offset tokens that let a client record its position in the source stream. When a channel is reopened after a restart, supplying the last successfully committed offset token causes the SDK to resume from that point rather than starting fresh, which prevents gaps. This is the intended mechanism for exactly-once-style recovery in the Ingest SDK.
- ✗
Switch the pipeline to a standard Snowpipe with AUTO_INGEST so that the cloud provider's event notifications guarantee delivery of every record.
Why it's wrong here
Standard Snowpipe ingests files from a stage using event notifications or REST calls and is not designed for per-record streaming from Kafka. Event notifications are best-effort and can be missed or duplicated, and Snowpipe does not expose per-record offsets. This change would increase latency and still not guarantee that every Kafka record is captured after a restart.
About these practice questions
Courseiva writes every ARA-C01 question from scratch — 209 in total, each with an explanation and a wrong-answer breakdown. None are copied from real exams or dumps. Learn why practice questions differ from exam dumps →
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 Snowflake exam blueprint
This ARA-C01 practice question is part of Courseiva's free Snowflake 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 ARA-C01 exam.