Time Based Key-Value Store
Design a key-value store that supports:
- set(key, value, timestamp) - Store the key-value pair at the given timestamp.
- get(key, timestamp) - Return the value with the largest timestamp <= given timestamp. Return "" if no such value.
You will receive a sequence of operations. Output the result of each get operation on a separate line.
Example:
set,foo,bar,1;set,foo,bar2,4;get,foo,1;get,foo,3;get,foo,4;get,foo,5
bar bar bar2 bar2
- The input sequence is split into operations:
set(foo, bar, 1),set(foo, bar2, 4),get(foo, 1),get(foo, 3),get(foo, 4),get(foo, 5). - The
setoperations store key-value pairs at the given timestamps:(foo, bar, 1)and(foo, bar2, 4). - The
getoperations retrieve the value with the largest timestamp <= the given timestamp:get(foo, 1)returnsbarbecause 1≤1.get(foo, 3)returnsbarbecause 1≤3 and there's no value at timestamp 2.get(foo, 4)returnsbar2because 4≤4.get(foo, 5)returnsbar2because 4≤5 and there's no value at timestamp 5.
- The results of the
getoperations are output on separate lines, producing the given output.
Constraints:
- 1 <= key.length, value.length <= 100
- 1 <= timestamp <= 10^7
- Timestamps for set are strictly increasing
- At most 2 * 10^5 operations
Background Knowledge
The problem requires designing a key-value store, which is a fundamental data structure in computer science. A key-value store is a simple database that stores data as a collection of key-value pairs. In this case, we need to support two primary operations: set and get. The set operation stores a key-value pair at a given timestamp, while the get operation retrieves the value associated with a key at the largest timestamp less than or equal to a given timestamp. This problem involves understanding data structures and algorithms for efficient storage and retrieval of data.
To approach this problem, we need to consider the concept of time-based data and how to efficiently store and retrieve data based on timestamps. We can utilize data structures such as hash maps or dictionaries to store key-value pairs, and sorted data structures like lists or trees to manage timestamps. Understanding the trade-offs between different data structures and algorithms is crucial to designing an efficient solution.
The problem also involves querying data based on timestamps, which requires understanding search algorithms and data retrieval techniques. We need to consider how to efficiently find the value with the largest timestamp less than or equal to a given timestamp. This involves understanding concepts like binary search and iterative search algorithms.
Continue the full explanation
You're reading the free preview. Unlock the complete walkthrough, the code editor, test runner and reference solution with Premium.
Editor locked
The code editor is locked for Pro problems. It is only available for free problems. Please upgrade to gain access to the code editor for all problems.