Introduction

In a TikTok system design interview, the candidate was tasked with designing an efficient Key-Value Store system. The challenge focused on designing high-performance operations and optimizing time complexity. With the assistance of csoahelp, the candidate successfully navigated the problem and provided a robust solution.

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Problem Description

Task: Design an in-memory key-value store to handle integers (keys as strings, values as integers) and a global version number. No persistent storage is required.

Requirements:

1. PUT <key> <value>
   • Assigns a value to the given key.
   • Increments a global version number, assigning it to the write operation.
   • Output format: PUT(#<version_number>) <key> = <value>.
2. GET <key>
   • Retrieves the most recent value of a key.
   • Output format: GET <key> = <value> or GET <key> = <NULL> if the key is not set.
3. GET <key> <version_number>
   • Retrieves the value of a key at a specific version.
   • Output format: GET <key>(#<version_number>) = <value> or <NULL> if the version is invalid.

Input Example:

PUT key1 5
PUT key2 6
GET key1
GET key1 1
GET key2 2
PUT key1 7
GET key1 3
GET key4
GET key1 4

Output Example:

PUT(#1) key1 = 5
PUT(#2) key2 = 6
GET key1 = 5
GET key1(#1) = 5
GET key2(#2) = 6
PUT(#3) key1 = 7
GET key1(#3) = 7
GET key4 = <NULL>
GET key1(#4) = 7

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Interview Walkthrough

Clarifications

At the start of the interview, the candidate sought clarification on the problem:

1. Is the key always a string, and the value always an integer?
   • The interviewer confirmed that key is a string and value is an integer.
2. Does the global version expire?
   • The global version number does not expire and is incremented with each write operation.
3. Is the version specific to each key, or global across all keys?
   • The version is global across all keys.

Once these details were clarified, the candidate, with our guidance, finalized their approach to the problem.

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Solution Approach

Data Structure Design

The candidate, guided by us, used a HashMap as the primary storage structure:

• Structure:HashMap<String, List<Tuple>>
  • Key: The string key.
  • Value: A list of tuples, where each tuple is (version, value).

Algorithm Design

1. PUT <key> <value>
   • If the key does not exist, initialize an empty list for it.
   • Append a tuple (global_version, value) to the list.
   • Increment the global_version after every write.
   • Time Complexity: O(1).
2. GET <key>
   • Retrieve the most recent value of the key.
   • Return <NULL> if the key does not exist.
   • Time Complexity: O(1).
3. GET <key> <version_number>
   • Use binary search to find the tuple with the highest version number ≤ the requested version.
   • Time Complexity: O(log(n)), where n is the number of versions for the given key.

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Implementation Steps

Step 1: PUT Operation

• The candidate implemented the following steps:
  1. Check if the key exists in the HashMap. If not, initialize an empty list.
  2. Append the new (version, value) tuple to the list.
  3. Increment the global_version and print the operation result.

Step 2: GET Operation

• Standard GET: Retrieve the last value in the list. If the key does not exist, return <NULL>.
• Versioned GET: Use binary search to find the closest version ≤ the requested version. If no valid version is found, return <NULL>.

Step 3: Optimization and Testing

• We guided the candidate to test edge cases:
  • Requests for non-existent keys or versions.
  • Performance under high numbers of versions.
  • Validating the binary search logic for GET with a version number.

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Test Cases

Example 1: Basic Operations

1. Input:PUT key1 5 PUT key2 6 GET key1 GET key1 1 PUT key1 7 GET key1 3 GET key1 2 GET key4 GET key1 4
2. Output:PUT(#1) key1 = 5 PUT(#2) key2 = 6 GET key1 = 5 GET key1(#1) = 5 GET key2(#2) = 6 PUT(#3) key1 = 7 GET key1(#3) = 7 GET key1(#2) = 5 GET key4 = <NULL> GET key1(#4) = 7

Example 2: Edge Cases

• Requesting a non-existent key:
  • Input: GET key3
  • Output: GET key3 = <NULL>.
• Requesting a version that exceeds the current global version:
  • Input: GET key1 10
  • Output: GET key1(#10) = 7.

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Insights and Feedback

This problem emphasized system design and algorithm optimization. By leveraging HashMaps and binary search, the candidate efficiently addressed the requirements, ensuring optimal performance.

With csoahelp’s guidance, the candidate not only completed the task but also confidently handled edge cases and performance considerations.

If you are preparing for challenging technical interviews like this one, let csoahelp guide you to success!

Contact csoahelp today and make your technical interviews a breeze!

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