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Amazon·Software Engineer·Technical Phone Screen·Intermediate

Intermediate
Jul 2026

Summary

Amazon SWE coding round focused on a sentence/word indexing problem. Pretty design-heavy for what I expected to be a straightforward coding question.

Questions Asked (1)

Q1

Design a data structure that indexes words to the sentences they appear in. You should be able to look up all sentences containing a given word, and also delete a sentence while keeping the index consistent.

Algorithms & Data StructuresSystem DesignData Modeling
Author's notes

Spent the first few minutes thinking it was just an inverted index problem and almost rushed straight to a hashmap of word to sentence list.

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AI HintsAI Generated

Suggested Approach

Start by clarifying requirements and scale, then propose an inverted index using a hash map from words to sets of sentence IDs, plus a map from sentence IDs to sentences. Explain how to support efficient lookup and deletion, and discuss trade-offs and potential optimizations.

Pro tip: Mention that using a set for sentence IDs ensures O(1) deletion from the word's posting list, and consider discussing how to handle updates to sentences (e.g., if a sentence is edited) to show foresight.

1. Clarify Requirements and Scale

Ask about expected data size, read/write ratio, and whether sentences can be updated. This shows you think about practical constraints before designing.

2. Design Core Data Structures

Propose a hash map from words to sets of sentence IDs (inverted index) and a hash map from sentence IDs to sentence text (forward index). Explain how these support lookup and deletion.

3. Detail Operations

Walk through insertion, lookup, and deletion. For deletion, remove the sentence ID from each word's set and delete the sentence from the forward index.

4. Analyze Complexity and Trade-offs

Discuss time and space complexity for each operation. Mention alternatives like using a trie for prefix searches or a database for persistence.

5. Consider Extensions and Optimizations

Talk about handling updates, concurrency, memory optimization (e.g., using integer IDs), and scaling to distributed systems if needed.

Key Points to Mention

  • Inverted index: mapping words to sentence IDs
  • Forward index: mapping sentence IDs to sentences
  • Using sets for O(1) deletion from posting lists
  • Time complexity: O(1) average for lookup and deletion, O(k) for insertion where k is number of words in sentence
  • Handling updates: either delete and re-insert or maintain additional structures
  • Scalability: sharding by word or using a distributed cache/database

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