Arrays and Hash Map Operations Questions

Covers algorithmic patterns that use arrays together with hash based maps or dictionaries to achieve efficient lookup and counting. Topics include frequency counting, duplicate detection, two sum and k sum variants, sliding window with counts, index mapping, grouping by keys, and using hash maps to reduce time complexity from quadratic to linear. Emphasize insertion deletion and lookup costs, collision and memory considerations, trade offs between using hash maps versus sorting or two pointer techniques, and typical interview problem families that rely on combining arrays with associative containers.

MediumTechnical

0 practiced

Implement in Python an efficient grouping function that takes a list of (key, value) tuples and returns a dictionary mapping each key to the list of its values. Discuss how to scale this grouping when the dataset is too large to fit in memory and how to stream results or use external aggregation.

MediumTechnical

0 practiced

You must estimate the number of unique users in a daily log of 500M events with limited memory. Compare exact hash-based counting versus probabilistic structures such as HyperLogLog. Explain how HyperLogLog uses hashing and registers to estimate cardinality, and discuss merging across partitions and error-memory trade-offs for data engineering use cases.

MediumTechnical

0 practiced

Implement in Python a function that returns the length of the longest substring without repeating characters using the sliding-window + hash map pattern. Explain how you update the left boundary using stored character indices and analyze time/space complexity. Provide an example to illustrate the window movement.

MediumTechnical

0 practiced

Given a string s and a pattern p, implement in Python a function that returns starting indices of p's anagrams in s. Use sliding-window and hash maps to maintain character counts and achieve O(n) time. Explain an optimization to avoid full map comparisons on each shift.

HardTechnical

0 practiced

A production service shows performance degradation due to repeated hash collisions in a custom partitioning function. Describe how you would detect pathological collision cases, mitigate them (for example using different hash functions, salted hashing, rebalancing), and design monitoring and alerts to detect recurrence or malicious inputs.

Unlock Full Question Bank

Get access to hundreds of Arrays and Hash Map Operations interview questions and detailed answers.

Join thousands of developers preparing for their dream job.