Hierarchical Join Optimization via Non-Buffering Read Operations
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Solution Overview
Problem
Datacenters face resource exhaustion when handling numerous SQL queries with JOIN operations due to inefficient data retrieval and processing of hierarchical data structures, leading to increased memory, network bandwidth, and processing cycle usage.
Innovation Solution
A relational interface system that evaluates SQL queries for suitability in performing non-buffering read operations on hierarchical data storage, transforming queries to optimize data retrieval by identifying top-down hierarchical table relationships and performing 'LEFT OUTER JOIN' operations efficiently, thereby reducing resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional buffering read operations are used to handle SQL JOIN queries on hierarchical data, then data retrieval can be performed, but memory consumption and processing time increase significantly
Solution Approach 1:
The patent extracts only the necessary data from hierarchical storage by transforming SQL queries into navigation operations that retrieve records in a top-down hierarchical sequence. This eliminates the need to load entire result sets into memory buffers, as data is processed in a streamlined fashion directly from storage.
Solution Approach 2:
The system performs preliminary evaluation of SQL queries to determine if they can be converted into non-buffering navigation operations. By pre-processing the query to identify hierarchical table relationships and appropriate navigation paths, the system prepares the data retrieval strategy before execution, avoiding subsequent buffering requirements.
2Loss of information
If multiple read operations are performed to retrieve data from hierarchical storage, then complete query results can be obtained, but elapsed time and network bandwidth usage increase
Solution Approach 1:
The patent merges multiple sequential read operations into a single non-buffering navigation operation by exploiting hierarchical table relationships. The system combines parent-child table joins into one continuous data retrieval process that maintains result completeness while eliminating intermediate buffering steps and reducing total elapsed time.
Solution Approach 2:
The system establishes continuous data flow from hierarchical storage to query results by implementing non-buffering navigation operations. Data flows continuously through the system without being interrupted by buffer filling and emptying cycles, maintaining uninterrupted retrieval of complete query results.
3Adaptability or versatility
If conventional JOIN operations are used on hierarchical data tables, then query flexibility is maintained, but resource utilization including processor cycles and memory increases
Solution Approach 1:
The patent changes the operational parameters of JOIN operations by transforming them into navigation operations that leverage hierarchical relationships. This parameter change allows the system to maintain query flexibility while reducing processor cycle usage, as navigation operations can exploit the inherent hierarchical structure to optimize data retrieval paths.
4Reliability
If buffering operations are used to manage hierarchical data streams, then data processing can be performed, but network bandwidth and memory resources are consumed
Solution Approach 1:
The system extracts data directly from hierarchical storage in a continuous stream without introducing buffering intermediaries. This extraction approach maintains data processing reliability by ensuring complete data retrieval while eliminating the additional network bandwidth consumption associated with buffer management operations.
Data Source
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AI summary
An apparatus (102) for conducting a hierarchical join on a hierarchically lustered data stream is disclosed. The apparatus (102) may include a memory (202) storing query conditions that each determine whether a Structured Query Language query is suitable for performing a non-buffering read operation on a hierarchical data storage (106-112). A processor (204) in communication with the memory (202) may be configured to receive a Structured Query Language ("SQL") query from a client device (114-118) and evaluate the SQL query for one or more of the query conditions stored in the memory (202). When the processor (204) determines that the SQLquery satisfies one or more of the query conditions, the processor (204) may then perform a non-buffering read operation on the hierarchical data storage (106-112) to obtain a hierarchically clustered data stream. The hierarchically clustered data stream may be evaluated to obtain a plurality of record results, which may be transmitted to the client device (114-118).