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.
MediumTechnical
0 practiced
Explain how using DISTINCT in combination with joins can hide underlying join errors (e.g., duplicate explosion) and why DISTINCT is often a band-aid. Describe a systematic approach to remove duplicates at the source, verify canonical keys, and rewrite the join to produce correct aggregates without relying on DISTINCT.
MediumTechnical
0 practiced
You have customers and multiple addresses per customer with effective_from timestamps. For each order, attach the customer's most recent address as of order_time. Provide a SQL solution that deduplicates addresses per customer using window functions before joining to orders, ensuring one matched address per order even when addresses change frequently.
EasyTechnical
0 practiced
NULLs in join keys and duplicate rows often surprise analysts. Given two tables A(id, val) and B(id, val): explain how SQL equality predicates treat NULL keys during joins, how NULL keys can lead to missing matches, and provide two strategies to include NULL-keyed rows in join logic when appropriate (e.g., grouping NULLs together or using surrogate keys).
HardTechnical
0 practiced
You maintain a pipeline that joins newly ingested events to a slowly changing dimension (Type 2). Occasionally, duplicate events are emitted and land in the pipeline twice. Describe an end-to-end strategy to ensure the final reporting tables are not double-counted: dedupe incoming events, use deterministic keys for idempotent upserts, and implement monotonic offsets/checkpoints. Provide pseudo-SQL or pseudo-code showing idempotent upsert flow.
MediumTechnical
0 practiced
Write a PostgreSQL query using LATERAL (or CROSS APPLY) to join each customer to their single most recent address (addresses(customer_id, address_id, effective_from)). Make sure the query scales when addresses are large by pushing filters early.
Unlock Full Question Bank
Get access to hundreds of Complex Data Integration and Joins interview questions and detailed answers.
Sign in to ContinueJoin thousands of developers preparing for their dream job.