COF-C03 Practice Question: Snowflake AI Data Cloud Features and Architecture
A data engineering team is loading a 500 GB CSV file into a Snowflake table using the COPY command. They notice that the load is taking longer than expected and the warehouse is showing high CPU utilization. Which of the following is the MOST likely cause for the slow performance?
⚠ Common exam trap
The trap here is assuming that increasing warehouse size will always solve slow data loading, when the real bottleneck is often file size and lack of parallelism.
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
✓
The file is too large for a single COPY command and should be split into smaller files.
For optimal load performance, Snowflake recommends splitting large data files into multiple smaller files (100-250 MB compressed) to allow parallel loading across the warehouse nodes. A single large file cannot be parallelized, leading to slower loads and potential resource contention. Increasing warehouse size or tweaking other parameters does not address the fundamental limitation of loading a single large file.
Answer analysis
Option-by-option breakdown
For each option: why learners choose it and why it is or isn't the right answer here.
- ✗
The COPY command is using a single thread by default and should be configured for multi-threading.
Why it's wrong here
Snowflake automatically parallelizes loads when multiple files are present. There is no configuration to enable multi-threading for a single file. The COPY command distributes work across files, not within a single file. Thus, the solution is to split the file, not to configure threading.
- ✗
The CSV file contains too many columns, causing parsing overhead.
Why it's wrong here
While parsing overhead exists, it is not the most likely cause for slow performance with a large single file. Snowflake handles column parsing efficiently, and the number of columns typically does not cause such a significant slowdown. The main issue is the file size and lack of parallelism.
- ✗
The warehouse size is too small and should be increased to handle the file size.
Why it's wrong here
While increasing warehouse size can improve performance, the primary bottleneck for a single large file is the lack of parallelism due to file size. Even a larger warehouse may not help if the file cannot be split across nodes. The issue is not compute capacity but the inability to parallelize the load of one file.
- ✓
The file is too large for a single COPY command and should be split into smaller files.
Why this is correct
Snowflake recommends splitting large files into multiple smaller files (typically 100-250 MB compressed) to enable parallel loading. A single large file cannot be processed in parallel, causing one thread to handle the entire load, leading to high CPU on a single node and longer load times. Splitting the file allows the warehouse to distribute the load across multiple nodes.
About these practice questions
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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 Snowflake exam blueprint
This COF-C03 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 COF-C03 exam.