← Databricks Interview Insights
I got the basic prefix-matching logic down fine: mask off the host bits, compare to the network address, done.
Start by clarifying requirements and constraints, then propose a solution using a binary trie (prefix tree) to store CIDR blocks for efficient longest-prefix matching. Explain how to convert IP addresses and CIDR blocks to binary, insert them into the trie, and query for the first matching CIDR, discussing trade-offs and potential optimizations.
Pro tip: Mention that the 'first' CIDR in the list implies preserving insertion order, so you might need to store metadata (like index) in the trie nodes and return the one with the smallest index among matches. This shows attention to detail and practical implementation awareness.
Ask about the size of the CIDR list, frequency of queries, whether the list is static or dynamic, and if 'first' means first in the original list or first in some other order. This helps determine the appropriate data structure and algorithm.
Propose a binary trie (prefix tree) where each node represents a bit of the IP address. CIDR blocks are inserted as paths from root to the prefix length, with the block's index stored at the terminal node.
For each CIDR block, convert the IP and prefix length to binary, then traverse the trie, creating nodes as needed, and store the block's index at the node corresponding to the prefix length.
Convert the IP to binary and traverse the trie bit by bit, keeping track of the most recent (or smallest index) CIDR block encountered. At the end, return the block with the smallest index if multiple matches exist.
Compare trie approach with alternatives like interval trees or sorting by prefix length. Mention memory usage, time complexity (O(32) for IPv4, O(128) for IPv6), and potential for compression or caching.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.