Working with Different SQL Dialects Questions
Understand differences between SQL Server, PostgreSQL, BigQuery, Snowflake, and other databases. Know which functions are available in which databases (e.g., GENERATE_DATE_ARRAY in BigQuery vs. recursive CTEs in others) and how to adapt queries accordingly.
HardTechnical
0 practiced
A BI dashboard intermittently shows different top-products each refresh. The underlying SQL uses GROUP BY product, ORDER BY SUM(sales) DESC without a deterministic tiebreaker. Explain why results can be nondeterministic across database engines and propose robust fixes. Consider differences in planner optimizations and parallel execution across Postgres, BigQuery, and Snowflake.
EasyTechnical
0 practiced
Get the first day of the month for a date column 'order_date' in PostgreSQL, BigQuery, Snowflake, and SQL Server. Show the SQL expression for each dialect and explain why DATE_TRUNC exists in some systems while SQL Server requires a date arithmetic workaround.
HardTechnical
0 practiced
Fill missing daily values per user in a time series so dashboards show zeros for absent dates. For events(user_id, event_date, value), provide an approach and SQL for: 1) BigQuery using GENERATE_DATE_ARRAY and LEFT JOIN; 2) Postgres using generate_series; 3) Snowflake using TABLE(GENERATOR) with sequence. Also show how to forward-fill the last known value instead of zero.
EasyTechnical
0 practiced
Temporary tables behave differently across platforms. Describe the semantics and lifecycle of temporary or transient tables in SQL Server (#temp), PostgreSQL (TEMP/TEMPORARY), Snowflake (TEMPORARY), and BigQuery (use of WITH/temporary tables via scripting). For BI workloads, when would you prefer CTEs, temp tables, or persistent derived tables?
MediumSystem Design
0 practiced
Design an automated daily incremental ingestion process for a CSV feed of 100M rows/day into three target warehouses: BigQuery, Snowflake, and PostgreSQL. Requirements: dedupe by business key, maintain history of changes, and keep dashboards low-latency. Describe staging, partitioning, dedupe/upsert strategy (MERGE/ON CONFLICT/streams+tasks), monitoring, and cost considerations per platform.
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