Graph Database Query Pushdown to Reduce Data Transmission
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Solution Overview
Problem
Conventional graph data query technologies in graph databases require traversal of all stored data, leading to excessive data reading and transmission, which reduces query efficiency and user experience.
Innovation Solution
The query engine parses query conditions and pushes them down to the storage engine, enabling the storage engine to execute the query directly, reducing unnecessary data reading and transmission.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the query engine traverses all stored graph data to execute queries, then comprehensive data coverage is achieved, but data reading and transmission amounts increase excessively
Solution Approach 1:
The patent extracts and pushes down query conditions from the query engine to the storage engine, enabling the storage engine to execute queries directly on stored data without requiring the query engine to traverse all data. This extraction of query execution capability resolves the contradiction by maintaining data coverage while minimizing data reading and transmission.
Solution Approach 2:
The patent performs preliminary action by pushing query conditions down to the storage engine before actual query execution. The storage engine prepares and executes queries using pushed-down conditions, which eliminates the need for the query engine to read and process all data, thereby reducing data transmission while ensuring comprehensive data coverage.
2Measurement precision
If the query engine processes all graph data to ensure accurate query results, then query accuracy is maintained, but query execution time increases
Solution Approach 1:
The patent extracts query execution functionality from the query engine and transfers it to the storage engine through query condition pushdown. This allows the storage engine to execute queries directly on stored data with appropriate filtering conditions, maintaining query accuracy while significantly reducing execution time by avoiding full data traversal.
Solution Approach 2:
The patent performs preliminary action by pushing query conditions to the storage engine before query execution. The storage engine uses these conditions to perform selective data access and filtering operations, ensuring accurate results while minimizing the time required for query processing.
3Loss of information
If the query engine reads and transmits large amounts of data to perform queries, then complete data analysis is achieved, but system resource consumption increases
Solution Approach 1:
The patent extracts query execution capability from the query engine and transfers it to the storage engine through query condition pushdown. This enables the storage engine to perform complete data analysis using pushed-down query conditions without requiring the query engine to read and transmit large amounts of data, thereby reducing system resource consumption while maintaining analysis completeness.
Solution Approach 2:
The patent performs preliminary action by pushing query conditions to the storage engine before query execution. The storage engine uses these conditions to perform selective data access and processing, achieving complete data analysis for relevant data while minimizing resource consumption by avoiding unnecessary data reading and transmission.
Data Source
AI summary
Graph database graph data query is described. In response to a query request for a graph database, a query statement comprised in the query request is parsed to obtain at least one query condition comprised in the query statement, where the graph database comprises a query engine and a storage engine. Whether the at least one query condition comprises a query condition that needs to be executed by one or more of an operator for: querying information about a node or an edge in graph data, performing a filtering query on graph data, limiting a quantity of query results, sorting query results, or performing statistical analysis on query results is determined. If the at least one query condition comprises the query condition, the query condition that needs to be executed by the operator is pushed down to the storage engine, so that the storage engine executes the query request.