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Databricks·Software Engineer·Technical Phone Screen·Intermediate

IntermediatePrefer not to say
Apr 2026Remote

Summary

Databricks software engineering interview with a networking/IP routing problem that looked approachable on the surface but had a lot of hidden depth once you got into the weeds of prefix matching and data structures.

Questions Asked (1)

Q1

Given a list of CIDR rules (each pairing a network range with an 'allow' or 'deny' action), write a function that takes an IPv4 address and returns whether it is allowed or denied, using longest-prefix-match semantics and a defined default when no rule matches.

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

I knew what CIDR was but hadn't implemented it from scratch, so parsing the dotted-quad into a 32-bit integer took me longer than it should have.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements: rule format, default action, and whether rules can overlap. Then propose a trie-based solution for efficient longest-prefix match, and discuss trade-offs with simpler approaches like linear scan or sorted intervals.

Pro tip: Mention that you would validate the input IP and CIDR rules, and handle edge cases like /0 and /32. Also, discuss how to handle rule updates if the system requires dynamic changes.

1. Clarify Requirements

Ask about the rule format, default action, and whether rules can overlap. Confirm that longest-prefix-match means the most specific rule wins.

2. Choose Data Structure

Propose a binary trie (prefix tree) where each node represents a bit of the IP address. Store the action at nodes that correspond to rule prefixes.

3. Insert Rules

For each CIDR rule, convert the IP and prefix length to binary, then insert into the trie, marking the node with the action.

4. Lookup IP

Traverse the trie using the bits of the IP address, keeping track of the last seen action. After traversal, return the last action or the default if none.

5. Discuss Trade-offs

Compare trie with linear scan (O(n) per lookup) and sorted intervals (O(log n) with binary search). Mention memory usage and update complexity.

Key Points to Mention

  • Longest-prefix-match semantics: the most specific rule (longest prefix) takes precedence.
  • Default action when no rule matches (e.g., deny or allow) must be defined.
  • Trie implementation: each node has two children (0 and 1) and an optional action.
  • Time complexity: O(32) for lookup and insertion, which is effectively O(1).
  • Space complexity: O(n * 32) worst case, but can be optimized with path compression.
  • Handling overlapping rules: trie naturally resolves by deepest match.
  • Edge cases: /0 rule (matches all), /32 rule (exact match), invalid IPs.
  • Alternative approaches: linear scan (simple but slow), sorted intervals (binary search on prefix lengths).

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