SOL-C01 · Question #125
SOL-C01 Question #125: Real Exam Question with Answer & Explanation
The correct answer is B: Pre-process the JSON files to split large arrays into multiple smaller JSON documents before. Splitting large arrays into multiple smaller JSON documents before loading is the most effective solution. Option A is incorrect because MAX_FILE_SIZE parameter mainly controls the split into smaller chunks for parallel processing, not row size limits. Option C is incorrect becau
Question
A data engineer is tasked with loading JSON data containing nested arrays into Snowflake. Some JSON files exceed Snowflake's maximum single row size limit. Which of the following strategies is the MOST effective way to handle this situation while maintaining data integrity and query performance?
Options
- AIncrease the MAX FILE SIZE parameter in the Snowflake stage configuration to accommodate
- BPre-process the JSON files to split large arrays into multiple smaller JSON documents before
- CUse the `STRIP OIJTER ARRAY file format option during the COPY INTO command to flatten the
- DLoad the entire JSON file as a single VARIANT column and then use Snowflake's JSON parsing
- EImplement a custom IJDF (User-Defined Function) in JavaScript to recursively parse the JSON
Explanation
Splitting large arrays into multiple smaller JSON documents before loading is the most effective solution. Option A is incorrect because MAX_FILE_SIZE parameter mainly controls the split into smaller chunks for parallel processing, not row size limits. Option C is incorrect because 'STRIP_OUTER ARRAY only works if there is a single outer array and doesn't address the nested structure or size limits within the document. Option D would likely still exceed row size limits. Option E is an overly complex solution compared to pre-processing the files. Pre- processing allows for controlled splitting to avoid exceeding row size limits and maintains efficient
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