Reviewed by Aditya Kumar · Last reviewed 2026-03-25
**Single Command**: `sqoop import-all-tables` with `--exclude-tables` for large/irrelevant tables. ```bash sqoop import-all-tables --connect jdbc:mysql://host/sales_db \ --username user -P --warehouse-dir /user/hive/warehouse \ --exclude-tables audit_log,temp_data...
This easy-level Spark/Big Data question appears frequently in data engineering interviews at companies like Meesho. While less common, it tests deeper understanding that distinguishes strong candidates. Mastering the underlying concepts (airflow, sql) will help you answer variations of this question confidently.
Start by clearly defining the core concept being asked about. Interviewers want to see that you understand the fundamentals before diving into implementation details. Structure your answer with a definition, then explain the practical application with a concise example. The expert answer includes a code example that demonstrates the implementation pattern.
Single Command: sqoop import-all-tables with --exclude-tables for large/irrelevant tables.
sqoop import-all-tables --connect jdbc:mysql://host/sales_db \
--username user -P --warehouse-dir /user/hive/warehouse \
--exclude-tables audit_log,temp_data --num-mappers 4
Why Not Always import-all-tables: (1) No per-table --split-by—Sqoop picks primary key; composite or missing PK causes single-mapper. (2) All-or-nothing—one failure fails all. (3) No per-table incremental.
Scalability Trade-offs: Parallelize with separate jobs (Airflow DAG, one task per table). Each table gets tuned --num-mappers and --split-by.
Cost Implications: import-all-tables simpler but slower for heterogeneous tables. Table-by-table enables spot clusters per table and incremental per table.
Pro-Move: 'We use MetaData catalog to drive sqoop imports; each table has its own split-by.' Red Flag: import-all-tables on 50+ tables without exclude—imports audit logs and temp tables.
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According to DataEngPrep.tech, this is one of the most frequently asked Spark/Big Data interview questions, reported at 1 company. DataEngPrep.tech maintains an editor-reviewed database of 1,863 data engineering interview questions across 7 categories.