Hash Table Questions at Swiggy: What to Expect

Hash Table questions appear in over one-third of Swiggy's technical interview problem set (14 out of 41). This frequency reflects their core operational needs: real-time order matching, efficient restaurant and menu data retrieval, duplicate detection in user activity logs, and rapid geospatial lookups. Mastering hash tables is non-negotiable for tackling Swiggy's focus on scalable, high-performance systems that handle millions of concurrent data points.

What to Expect — Types of Problems

Swiggy's hash table problems typically extend beyond basic implementation. Expect them to be embedded in scenarios mirroring their platform's challenges.

• Frequency Analysis & Counting: The most common pattern. Problems involve counting item frequencies, such as tracking most-ordered dishes, analyzing delivery partner activity, or identifying duplicate user IDs in logs.
• Lookup & Existence Checks: Questions requiring O(1) checks for element presence. Examples include validating if a restaurant ID exists in a service zone or checking for a specific menu item across partnered kitchens.
• Two-Number & Pair-Sum Variants: Classic problems adapted to Swiggy's domain, like finding two delivery assignments whose combined time matches a target or identifying complementary menu items frequently ordered together.
• Sliding Window + Hash Map: More advanced problems combine a hash map with a sliding window to track characters or elements within a subarray. This pattern is useful for analyzing sequences, such as finding the longest delivery route segment with unique drop-off points.

How to Prepare — Study Tips with One Code Example

Focus on applying the hash table as a tool to achieve O(1) average-time lookups, thereby reducing naive O(n²) solutions to O(n). Internalize the frequency map pattern. Always clarify input constraints and edge cases (empty input, all duplicates, large datasets) aloud during the interview.

A fundamental technique is using a hash map to count element frequencies in a single pass. This is the building block for most counting problems.

def count_frequencies(items):
    """Counts frequency of each item in a list."""
    freq_map = {}
    for item in items:
        freq_map[item] = freq_map.get(item, 0) + 1
    return freq_map

# Example: Counting most ordered dish IDs
dish_ids = [101, 102, 101, 103, 101, 102]
print(count_frequencies(dish_ids))
# Output: {101: 3, 102: 2, 103: 1}

Recommended Practice Order

1. Basics: Two Sum, First Unique Character, Valid Anagram.
2. Frequency & Counting: Top K Frequent Elements, Group Anagrams.
3. Design & Advanced: LRU Cache, Insert Delete GetRandom O(1).
4. Swiggy-Specific Practice: Solve all 14 tagged problems on CodeJeet, focusing on the domain context.

Practice Hash Table at Swiggy