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Databricks·Software Engineer·Technical Phone Screen·Senior

Senior
May 2026

Summary

Databricks technical phone screen with a networking/IP routing problem that looked like a simple lookup question until you realized they wanted a real trie implementation. Not a lot of context given upfront, had to ask clarifying questions to understand the full scope.

Questions Asked (1)

Q1

Given a list of CIDR rules each tagged as approve or reject, and a query IP address or CIDR block, determine whether the query should be approved or rejected using longest-prefix-match semantics. Default to rejected if no rule matches.

Algorithms & Data StructuresSystem DesignTechnical Trade-offs
Author's notes

My first instinct was to just iterate through all the rules and check containment, which works but they pushed back immediately on efficiency.

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AI HintsAI Generated

Suggested Approach

Clarify the input format and semantics: rules are CIDR blocks with approve/reject tags, and the query is an IP or CIDR block. Use a binary trie (prefix tree) to store rules, where each node represents a bit of the IP address and holds the rule if a prefix ends there. For a query, traverse the trie along the bits of the query IP (or the first IP of the query CIDR) and keep track of the deepest node with a rule; that rule determines the decision, defaulting to reject if none found.

Pro tip: Discuss how to handle overlapping rules and the importance of longest-prefix match: mention that you can store the rule at the node where the prefix ends, and during traversal, update the best match whenever you encounter a rule. Also, consider edge cases like IPv4 vs IPv6, and whether the query CIDR should be checked against rules that cover it entirely or partially.

1. Clarify requirements and edge cases

Ask about input formats (IPv4/IPv6, CIDR notation), whether rules can overlap, and how to handle a query CIDR that spans multiple rules. Confirm default behavior (reject if no match).

2. Choose data structure

Propose a binary trie (prefix tree) where each level corresponds to a bit of the IP address. Each node can store a rule (approve/reject) if a prefix ends there. This allows efficient longest-prefix match.

3. Insert rules into trie

For each rule, convert the CIDR to a bit string (e.g., 32 bits for IPv4). Traverse the trie, creating nodes as needed, and at the final node, store the rule. If multiple rules have the same prefix, the last one wins or handle conflict resolution.

4. Query the trie

For a query IP, traverse the trie bit by bit. Keep track of the deepest node that contains a rule. After traversal, the stored rule at that node is the decision. If no rule found, default to reject.

5. Handle query CIDR and complexity

If the query is a CIDR block, decide whether to check all IPs in the block (inefficient) or interpret the query as a prefix and find the most specific rule that covers it. Discuss time complexity: O(32) for IPv4, O(128) for IPv6 per query, and space O(N*32) for N rules.

Key Points to Mention

  • Longest-prefix match semantics: the most specific rule (longest prefix) wins.
  • Binary trie (prefix tree) for efficient storage and lookup.
  • Handling of IPv4 vs IPv6: bit lengths and representation.
  • Default behavior: reject if no rule matches.
  • Edge cases: overlapping rules, query CIDR vs IP, and rule conflicts.
  • Time and space complexity: O(bits) per query, O(N*bits) space.

AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.