Graph Database Ingestion With Lock-Free Deterministic Indexing
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Solution Overview
Problem
Existing data ingestion processes into graph databases face inefficiencies due to node duplication, leading to inconsistencies and prolonged processing times, especially when integrating custom data, and traditional solutions like cross-processing communication and graph database locking are inadequate.
Innovation Solution
Employing a deterministic function, such as a hash function, to directly assign indexes based on data attributes, eliminating the need for index assignment services and locking mechanisms, allowing parallel and simultaneous data ingestion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional index assignment services and locking mechanisms are used to prevent node duplication, then data integrity is maintained, but ingestion time increases significantly and parallelism is impeded
Solution Approach 1:
The patent applies preliminary action by pre-computing deterministic indexes for all nodes before ingestion begins. The index computation is performed in advance using a deterministic function on node attributes, so that during the actual ingestion process, no index computation or locking is needed. This separates the index computation phase from the ingestion phase, allowing parallel ingestion without conflicts.
Solution Approach 2:
The patent replaces the mechanical locking mechanism with a mathematical deterministic function. Instead of using locks to prevent simultaneous access to index assignments, the system uses a deterministic function that guarantees the same attributes always produce the same index. This substitution eliminates the need for locking while maintaining data integrity, enabling parallel ingestion operations.
2Reliability
If index search and graph database locking processes are implemented to avoid duplicate nodes, then node duplication is prevented, but processing speed decreases and parallelism is reduced
Solution Approach 1:
The patent applies self-service by making each node carry its own deterministic index computed from its attributes. Instead of a centralized service that searches for and assigns indexes, each node independently determines its own index through the deterministic function. This eliminates the need for index search operations and centralized coordination, dramatically improving processing speed and enabling parallelism.
3Manufacturing precision
If conventional pipeline with index assignment service is used, then nodes are properly indexed, but the service becomes a bottleneck that prevents simultaneous data ingestion
Solution Approach 1:
The patent extracts the index computation from the centralized index assignment service and embeds it directly in each node's data structure. By taking out the index computation function from the service layer and placing it at the data level, the system eliminates the service as a bottleneck while maintaining indexing accuracy. This simplifies the pipeline architecture by removing the coordination layer.
4Reliability
If graph database locking is applied during node creation, then index uniqueness is ensured, but ingestion parallelism is impeded and processing time increases
Solution Approach 1:
The patent introduces a deterministic function as an intermediary between node attributes and index assignment. This intermediary guarantees uniqueness mathematically without requiring locking mechanisms. The deterministic function acts as a mediator that transforms attributes into unique indexes in a lock-free manner, enabling parallel node creation while ensuring index uniqueness.
Data Source
AI summary
A pipeline for data ingestion to a database comprises an index-generating component based on a deterministic function, and a comparison component adapted to determine if an index generated by said index-generating component already exists in said database.