Structured Query Language Join Operations Questions

Comprehensive coverage of Structured Query Language join types and multi table query patterns used to combine relational data and answer business questions. Topics include inner join, left join, right join, full outer join, cross join, self join, and anti join patterns implemented with NOT EXISTS and NOT IN. Candidates should understand equi joins versus non equi joins, joining on expressions and composite keys, and how join choice affects row counts and null semantics. Practical skills include translating business requirements into correct join logic, chaining joins across two or more tables, constructing multi table aggregations, handling one to many relationships and duplicate rows, deduplication strategies, and managing orphan records and referential integrity issues. Additional areas covered are join conditions versus WHERE clause filtering, aliasing for readability, using functions such as coalesce to manage null values, avoiding unintended Cartesian products, and basic performance considerations including join order, appropriate indexing, and interpreting query execution plans to diagnose slow joins. Interviewers may probe result correctness, edge cases such as null and composite key behavior, and the candidate ability to validate outputs against expected business logic.

EasyTechnical

0 practiced

A report shows the number of rows changed when switching JOIN types. Explain how join choice affects row counts in the presence of one-to-many relationships and duplicate keys. Provide an example where converting a LEFT JOIN to an INNER JOIN or changing join order changes the number of result rows and why.

HardTechnical

0 practiced

Given an EXPLAIN output snippet (simplified) showing a nested loop join with large actual row counts mismatch to estimates, explain likely root causes and propose targeted fixes.

Example snippet:

Nested Loop  (cost=0.00..9999.00 rows=1 width=100)
  -> Seq Scan on orders  (actual rows=1000000)
  -> Index Scan on customers  (actual rows=1000)

What does the planner estimate mismatch indicate and what steps do you take?

HardTechnical

0 practiced

You need to compute conversion rate per marketing campaign, but campaigns and purchases have a many-to-many relationship through exposures. Explain how joining campaigns -> exposures -> purchases could double-count users and propose an aggregation approach to compute unique-user conversion (unique purchasers / unique exposed users). Provide example SQL that deduplicates at the appropriate stage.

EasyTechnical

0 practiced

You have a table employees(emp_id, manager_id, name) where manager_id references emp_id. Write a SQL query to produce pairs (employee_name, manager_name) using a self-join. Show how you would also include employees that have no manager (top-level) using appropriate join type and null handling.

EasyTechnical

0 practiced

You joined transactions to users and saw duplicate user rows because there are multiple transaction rows per user. Describe three SQL strategies to deduplicate users after the join so each user appears once with aggregated metrics. Provide a concise SQL example for each strategy (GROUP BY, DISTINCT ON, ROW_NUMBER() partition).

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