Hashmap Key Indexing for Faster Computing Operation Retrieval
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing computing systems face inefficiencies in processing large data sets due to the lack of effective hashmap data structures for managing computing operations, leading to suboptimal performance and delays in generating responses.
Innovation Solution
A computer-program product and computing device are provided with instructions to generate a hashmap data structure that indexes data storage with hash keys, enabling efficient execution of computing operations and retrieval of data, thereby optimizing the processing of large data sets.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If traditional data storage methods are used without hashmap indexing, then data can be stored, but data retrieval becomes inefficient and computing operations experience delays
Solution Approach 1:
The system pre-generates hash keys for data elements before actual computing operations are needed. By creating the hashmap data structure in advance and pre-computing hash keys, the system eliminates the need for time-consuming key generation during runtime, thereby improving retrieval speed and reducing computing operation delays
Solution Approach 2:
The hashmap data structure serves as an intermediary between raw data storage and computing operations. The hash key acts as a mediator that enables efficient lookup and retrieval of data elements, transforming the direct access problem into an indirect but much faster hash-based access mechanism
2Productivity
If hashmap data structures are implemented to improve data retrieval efficiency, then computing operations become faster, but system complexity increases
Solution Approach 1:
The system segments the computing operation into distinct phases: hash key generation, hashmap construction, and data retrieval. By dividing the complex process into manageable segments with clear responsibilities, the system achieves high productivity while making the complexity modular and easier to manage
Solution Approach 2:
The hashmap data structure is designed to be universal and multi-functional, serving as a reusable component for various computing operations. Once constructed, the same hashmap can support multiple different queries and operations, amortizing the initial complexity setup cost across numerous productive operations
Data Source
AI summary
A computing device receives a request to generate computing operations to effectuate a response for a function to an input set. The device generates a hashmap data structure. The hashmap data structure indexes respective data storage associated with a respective key of one or more keys. The device generates a first set of computing instructions to solve a first component for the function, executes the first set of computing instructions, and generates a first hash key. The first hash key represents multiple executions of the first set of computing instructions. The device stores the first hash key in the hashmap data structure to index a storage location in the hashmap data structure, generates a second set of computing instructions to solve a second component for the function, and executes the second set of computing instructions by using the first hash key to retrieve data indexed by the first hash key.