Pretty straightforward self-join on the same table.
Start by clarifying the schema and whether the hierarchy is stored as a self-referencing table (employee_id, manager_id) or as a closure table. Then write a simple self-join or recursive CTE to retrieve the manager for the given employee, and discuss edge cases like the CEO having no manager.
Pro tip: Mention that for frequent manager lookups, a self-join on an indexed manager_id column is efficient, but if the hierarchy is deep and you need all ancestors, a recursive CTE or closure table is better. This shows you consider performance and scalability.
Ask whether the hierarchy is stored in a single table with employee_id and manager_id columns, or in a separate relationship table. Confirm the column names and data types.
Determine if the question asks for the immediate manager only or the entire chain of command. For immediate manager, a self-join suffices; for the chain, use a recursive CTE.
For immediate manager: SELECT m.* FROM employees e JOIN employees m ON e.manager_id = m.employee_id WHERE e.employee_id = ?. For chain: use WITH RECURSIVE to traverse upward.
Discuss what happens if the employee is the CEO (manager_id is NULL) or if the employee ID does not exist. Mention using LEFT JOIN to return NULL for the CEO.
Mention indexing on manager_id for performance. If the hierarchy is large and queried often, consider a closure table or nested set model for faster ancestor queries.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Clarify the schema (e.g., employees table with id and manager_id) and whether the hierarchy is a tree or can have cycles. Then present a recursive CTE solution (or iterative approach) that traverses from the given manager down to all descendants, and discuss performance considerations.
Pro tip: Mention that recursive CTEs are ANSI SQL and supported by most databases, but if the interviewer asks about a specific system, adapt (e.g., CONNECT BY for Oracle). Also, proactively discuss how to handle cycles or depth limits to show robustness.
Ask about the table structure (e.g., employees with id, manager_id), whether the hierarchy is a tree, and if cycles are possible. Confirm the desired output (list of employee ids or full rows).
Decide between recursive CTE (standard) or iterative application-level traversal. Explain the trade-offs (e.g., recursive CTE is set-based and efficient for moderate depth).
Use a recursive CTE: anchor member selects direct reports of the given manager; recursive member joins employees to the CTE on manager_id = employee.id. Include a depth column if needed.
Discuss cycle detection (e.g., using a path array or depth limit), indexing on manager_id, and potential performance issues with deep hierarchies.
Walk through a small example to verify correctness, and explain how the query works step by step. Mention alternative approaches if the database doesn't support recursive CTEs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.
Honestly the most interesting part of the whole thing.
Clarify the hierarchy representation (e.g., tree with parent pointers or adjacency list) and define 'lowest common manager' as the deepest node that is an ancestor of both employees. Then choose an algorithm: if parent pointers exist, find intersection of ancestor paths; otherwise, use a recursive post-order traversal to find the lowest node whose subtree contains both employees.
Pro tip: Discuss trade-offs between time and space complexity, and mention that in a real system like Reddit, the hierarchy might be a graph with multiple managers, so you'd need to handle cycles or use a union-find approach.
Ask about the data structure (tree vs. graph, parent pointers, etc.) and confirm the definition of 'lowest common manager' (deepest common ancestor).
Decide between path-based (if parent pointers) or recursive traversal (if tree). Consider iterative vs. recursive and space constraints.
Trace the algorithm on a small hierarchy to verify correctness and edge cases (e.g., one employee is the manager of the other).
State time and space complexity (e.g., O(n) time, O(h) space for recursion) and discuss optimizations.
Mention cases like employees not in hierarchy, multiple managers, or large hierarchies requiring iterative solutions.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.