**Architectural Logic**: Character duplication is a string transform; SQL capabilities vary. **PostgreSQL**: `SELECT regexp_replace('123a!', '(.)', '\1\1', 'g')`. **Spark**: `regexp_replace(col("str"), "(.)", "$1$1")`. **Python**: `''.join(c*2 for c in s)`. **Why Choose**: SQL...
This medium-level SQL question appears frequently in data engineering interviews at companies like HashedIn. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (join, python, spark) will help you answer variations of this question confidently.
Break this problem into components. Identify the core trade-offs involved, then walk the interviewer through your reasoning step by step. Demonstrate awareness of edge cases and production considerations - this is what separates good answers from great ones.
Architectural Logic: Character duplication is a string transform; SQL capabilities vary. PostgreSQL: SELECT regexp_replace('123a!', '(.)', '\1\1', 'g'). Spark: regexp_replace(col("str"), "(.)", "$1$1"). Python: ''.join(c*2 for c in s). Why Choose: SQL regex works in many dialects; application layer clearer for complex manipulation. Scalability: For bulk, prefer batch processing in Spark/Python; SQL for inline transforms. Cost: UDF invocations in serverless add cost; native functions when possible.
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Analyze My Answer β FreeAccording to DataEngPrep.tech, this is one of the most frequently asked SQL interview questions, reported at 1 company. DataEngPrep.tech maintains a curated database of 1,863+ real data engineering interview questions across 7 categories, verified by industry professionals.