Complex Data Integration and Joins Questions
Handling intricate join scenarios: multi-condition joins, conditional joins with complex logic, joining on date ranges or overlapping time periods, complex left joins with multiple filtering conditions, self-joins for hierarchical or relationship data, handling non-standard relationships between tables. Understanding implications of different join types on row counts, NULL values, and duplicate handling. Designing queries that correctly integrate data from multiple sources while maintaining data integrity and avoiding duplicate counting or missing data.
HardTechnical
0 practiced
You run a join in Spark where one side is heavily skewed (few keys with billions of rows). Explain practical strategies to mitigate skew: salting, broadcasting the small table, sampling, repartitioning, and using map-side combines. Describe how you would test the effectiveness of your chosen strategy.
MediumTechnical
0 practiced
Write a SQL join that uses multiple conditions: equality on customer_id and a non-equi condition on event_ts being within 7 days of some reference_ts in the other table. Example tables: promotions(promo_id, customer_id, promo_start) and purchases(purchase_id, customer_id, purchase_ts). Return purchases that occurred between promo_start and promo_start + 7 days for the same customer. Discuss performance considerations.
HardTechnical
0 practiced
Given two very large tables to be joined on multiple columns, describe how you would interpret and act upon a query plan that shows a Nested Loop Join instead of Hash Join, causing very slow execution. What causes this choice and how would you change statistics, hints, or rewrite the query to encourage a more efficient plan?
HardTechnical
0 practiced
Design a test harness and a set of automated tests to validate the correctness of join logic in a production ETL job that merges orders with customer segments. Tests should cover row counts, duplicate detection, null handling, boundary-time matching, and data lineage. Include SQL assertions and end-to-end test ideas.
HardTechnical
0 practiced
You want to join user clickstream events to ad-impression logs where matches are approximate (time tolerance of 100ms and fuzzy IP/device match). Propose an efficient hybrid approach: pre-filter by coarse keys, apply time-windowed joins, then rank matches and pick the best candidate. Sketch SQL or pseudocode and describe how you avoid explosion of candidate pairs.
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