Cross-Cluster Search Filtering Using Preliminary Tag Indexing
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Solution Overview
Problem
Large cloud-distributed databases require extensive time and resources for cross-cluster searches, often yielding no results and wasting hardware, network bandwidth, and electrical energy.
Innovation Solution
Implement a preliminary tag search to identify which cross-cluster searches will yield results, allowing only successful searches to be conducted, thereby reducing unnecessary searches.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cross-cluster searches are performed on all clusters to ensure complete search coverage, then search completeness is improved, but hardware resource consumption and time increase significantly
Solution Approach 1:
The patent applies preliminary action by performing a tag search before the actual cross-cluster search. The tag search预先 identifies which clusters contain relevant data based on metadata tags, allowing the system to skip clusters that definitely don't contain matching data. This preliminary filtering action resolves the contradiction by maintaining search completeness (through thorough tagging) while dramatically improving search efficiency (by avoiding futile searches).
Solution Approach 2:
The patent introduces an intermediary element - the tag index - that mediates between the search query and the actual data clusters. Instead of directly searching all clusters, the query first interacts with the tag index to determine which clusters are worth searching. This intermediary layer resolves the contradiction by providing a filtering mechanism that ensures no relevant data is missed while eliminating wasteful searches.
2Reliability
If cross-cluster searches are performed across all clusters, then data retrieval completeness is improved, but network bandwidth consumption increases
Solution Approach 1:
The tag search performs a preliminary action by querying the tag index before initiating actual data retrieval across clusters. This preliminary query uses minimal network bandwidth to determine which clusters contain relevant data, preventing unnecessary data transfer across the network. The principle resolves the contradiction by filtering out clusters that don't contain matching data, thus maintaining retrieval completeness while dramatically reducing network bandwidth consumption.
3Measurement precision
If cross-cluster searches are performed on all clusters, then search accuracy is improved, but electrical energy consumption increases
Solution Approach 1:
The tag search performs a preliminary action that consumes minimal electrical energy to query the tag index and identify relevant clusters. This preliminary filtering prevents the system from wasting significant electrical energy on searching clusters that contain no relevant data. The principle resolves the contradiction by maintaining search accuracy (through comprehensive tagging) while dramatically reducing overall electrical energy consumption.
Solution Approach 2:
The patent applies partial action by performing only the necessary tag search before the actual data search, rather than performing exhaustive searches on all clusters. The tag search provides sufficient information to identify relevant clusters without the excessive energy cost of searching every cluster. This resolves the contradiction by achieving the necessary search accuracy through partial filtering action.
4Reliability
If the number of cross-cluster searches is increased to cover all clusters, then search thoroughness is improved, but time consumption increases
Solution Approach 1:
The tag search performs a preliminary action that quickly identifies relevant clusters by querying the tag index, which is optimized for fast metadata lookup. This preliminary filtering maintains search thoroughness (by ensuring all relevant clusters are identified) while dramatically reducing search time (by eliminating the need to query tags on every cluster).
Solution Approach 2:
The patent segments the search process into two distinct phases: a preliminary tag search phase that identifies relevant clusters, and an actual data search phase that occurs only on identified clusters. This segmentation resolves the contradiction by separating the thoroughness-checking function (tag indexing) from the time-consuming data retrieval function, allowing the system to maintain thoroughness while minimizing time consumption.
Data Source
AI summary
A preliminary tag search improves computer functioning by reducing cross-cluster searches. Today's cloud service providers maintain large, distributed datasets stored by multiple clusters having many nodes. Many cross-cluster searches generate no search results, but unsuccessful cross-cluster searches still consume much hardware resources, network bandwidth, and electrical energy. The preliminary tag search eliminates unfruitful cross-cluster searches. The preliminary tag search may identify only the cross-cluster searches that will generate positive search results. The preliminary tag search may identify wasteful cross-cluster searches that would generate no search results. Prior to conducting cross-cluster searches, a distributed database service may first perform the preliminary tag search that identifies successful/unsuccessful cross-cluster searches. The distributed database service may then decline or skip unsuccessful cross-cluster searches.