Selective Data Structure Operations for Graph Path Queries
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Solution Overview
Problem
Path queries in distributed graph databases are computationally expensive due to the need for creating multiple interrelated tables and enforcing path consistency rules, which increases processing time and resource usage.
Innovation Solution
The solution involves selectively omitting or deferring certain operations on the in-memory data structure, such as path consistency checking and table creation, based on conditions like single row variables and non-selective operations, to streamline query execution and reduce overhead.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If path consistency checking and table creation operations are performed for all path queries, then query result correctness is ensured, but processing time and computational resources increase significantly
Solution Approach 1:
The patent changes the operational parameters of the query execution system by introducing selective operation modes. Based on query characteristics (such as whether the query is a path query or non-path query), the system dynamically adjusts which operations are performed (full path consistency checking vs. simplified execution). This parameter-based adaptation allows the system to maintain correctness for queries that need it while skipping unnecessary operations for queries that don't require full consistency checking, thereby resolving the contradiction between reliability and productivity.
Solution Approach 2:
The patent applies partial action by performing only the necessary subset of operations for each query type. For path queries, full path consistency checking is performed; for non-path queries, the checking is omitted or deferred. This selective application of operations ensures that the system performs exactly the right amount of work needed for each query type, avoiding the excessive action of always performing full consistency checking on all queries, thus improving processing speed while maintaining correctness where required.
2Reliability
If multiple interrelated tables are created in memory for path query evaluation, then comprehensive query results are obtained, but memory usage and computational overhead increase
Solution Approach 1:
The system dynamically changes the memory allocation parameter based on query type. For path queries, the system allocates memory for multiple interrelated tables to ensure complete query results. For non-path queries, the system reduces memory allocation by omitting table creation. This parameter-based memory management allows the system to maintain result completeness for queries that need it while reducing memory consumption for queries that don't require extensive memory resources.
Solution Approach 2:
The patent applies partial action by creating only the necessary tables in memory for each query type. For path queries, full table creation is performed to ensure comprehensive results. For non-path queries, table creation is omitted or deferred, using only the minimal memory structures needed. This selective table creation ensures result completeness where required while minimizing memory resource consumption where full table creation is unnecessary.
3Reliability
If path consistency rules are enforced during query execution, then data integrity is maintained, but query execution time increases
Solution Approach 1:
The patent changes the execution parameter of path consistency enforcement based on query characteristics. For path queries, the system enables path consistency checking to maintain data integrity. For non-path queries, the system disables or defers path consistency checking, allowing faster execution. This conditional parameter adjustment resolves the contradiction by ensuring data integrity only when necessary, thereby reducing unnecessary execution time overhead.
Solution Approach 2:
The patent applies partial action by performing path consistency checking only for queries that require it (path queries) and omitting it for queries that don't need full consistency verification (non-path queries). This selective enforcement of path consistency rules maintains data integrity for critical queries while avoiding the time penalty of enforcing consistency rules on all queries, thus resolving the contradiction between data integrity and execution time.
Data Source
AI summary
The disclosed technologies are capable of selectively using data structure operations for path query evaluation. One technique involves reading a query that traverses at least two nodes and at least one edge of a graph in a graph database; compiling the query into a set of variables and a set of constraints, where the set of variables and the set of constraints correspond to the two nodes and the one edge of the graph; creating an in-memory data structure that comprises a table; using the set of variables and the set of constraints to determine an operation that is performable using the in-memory data structure; checking for an existence of a condition relating to the in-memory data structure or the operation; skipping the operation if the condition exists or executing the operation if the condition does not exist; and storing a set of intermediate query results in the table.