What is the optimal time complexity of solving Time Based Key Value Store?

The optimized solution achieves a time complexity of O(n) by using sorting, mathematical shortcuts, or hash table lookups.

What is the auxiliary space complexity for Time Based Key Value Store?

The space complexity is O(n) since we only use a minimal/constant amount of extra memory for tracking variables (or auxiliary space if dynamic structures are allocated).

What are the typical edge cases we must handle in Time Based Key Value Store?

Key edge cases include empty collections, negative or large bounds causing integer overflow, arrays with only one element, or inputs where target criteria are not met.

How can we optimize the brute force approach for Time Based Key Value Store?

Brute force methods often inspect all possible combinations. We optimize this by sorting the input list to enable binary search, or tracking processed items in a set to avoid redundant nested loop lookups.

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Time Based Key Value Store

Learn how to solve the 'Time Based Key Value Store' problem. This detailed resource details brute force and optimized approaches.

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Problem Statement

Easy

Design a time-based key-value data structure that can store multiple values for the same key at different time stamps and retrieve the key's value at a certain timestamp.

Implement the TimeMap class:

- TimeMap() Initializes the object.

- set(key: str, value: str, timestamp: int) Stores the key key with the value value at the given time timestamp.

- get(key: str, timestamp: int) -> str Returns a value such that set was called previously, with timestamp_prev <= timestamp. If there are multiple such values, it returns the value associated with the largest timestamp_prev. If there are no values, it returns "".

Constraints

•1 <= key.length, value.length <= 100
•key and value consist of lowercase English letters and digits
•1 <= timestamp <= 10^7
•All timestamps of set are strictly increasing for each key
•At most 2 * 10^5 calls will be made to set and get

Examples

Example 1

Input

["TimeMap", "set", "get", "get", "set", "get", "get"]
[[], ["foo", "bar", 1], ["foo", 1], ["foo", 3], ["foo", "bar2", 4], ["foo", 4], ["foo", 5]]

Output

[None, None, "bar", "bar", None, "bar2", "bar2"]

Explanation

set("foo", "bar", 1): stores bar at time 1. get("foo", 1): returns "bar". get("foo", 3): returns "bar" (latest value at or before time 3). set("foo", "bar2", 4): stores bar2 at time 4. get("foo", 4): returns "bar2". get("foo", 5): returns "bar2".

Need a Hint?

Analyze the input constraints. Try sorting first (O(n log n)) or using a hash map/set to track seen elements in O(n) time.

Edge Cases to Watch

Empty list or null input variables
Single item lists/arrays
Extremely large input bounds causing integer or stack overflow

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