Distributed Data Retrieval via Node Segmentation and Sorting
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Solution Overview
Problem
In distributed computing environments, retrieving data in an ordered fashion from multiple computing nodes is inefficient due to the need for searching and merging data across various nodes, which increases time and resource requirements.
Innovation Solution
Implementing sorting and merging techniques across multiple computing nodes to efficiently sort and assemble requested data ranges, using existing hardware and network connections to reduce retrieval times and enhance system efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Volume of stationary object
If data is stored across multiple computing nodes in a distributed computing system, then storage capacity is increased, but data retrieval time increases due to the need to search and merge data from multiple nodes
Solution Approach 1:
The patent applies preliminary action by pre-sorting data at each computing node before retrieval requests arrive. Each node maintains its data in sorted order, so when a range query is received, the system can efficiently locate and retrieve the requested range without performing full searches or merges across all nodes during the actual retrieval operation.
Solution Approach 2:
The patent segments the distributed data storage system into multiple computing nodes, each independently maintaining sorted subsets of the overall data. This segmentation allows parallel processing of retrieval requests across different nodes, reducing the time required to assemble complete data ranges compared to a centralized approach.
2Adaptability or versatility
If data is stored in an unordered fashion across computing nodes, then storage flexibility is improved, but ordered data retrieval requires additional searching and merging operations that increase processing time
Solution Approach 1:
The patent applies local quality by allowing each computing node to independently organize its local data subset in sorted order while maintaining overall system flexibility. Each node has the autonomy to manage its own data locally in an optimized manner, and the system as a whole benefits from the coordinated effort of all nodes providing their sorted local data for efficient range queries.
Data Source
AI summary
Enhanced techniques for data retrieval in a distributed computing environment are described. A computing node of a distributed computing environment may receive a data request. The computing node may include one or more subsets of data. The computing node may be configured to search among the one or more subset of data for a beginning of a data range that is responsive to the data request. The computing node may be further configured to forward a data range responsive to the search to another computing node of the distributed computing system to be merged with one or more additional data ranges. Other embodiments are described and claimed.