Lineage Metadata In-Memory Structures for Faster Query Retrieval
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Solution Overview
Problem
Existing data processing systems face inefficiencies in processing and retrieving lineage metadata, leading to prolonged query processing times and resource utilization due to the need to access and process metadata from large databases, which introduces latency and additional processing overhead.
Innovation Solution
Implementing a specialized lineage server that stores lineage metadata in a special-purpose data structure optimized for speed and efficiency, utilizing random access memory to minimize storage space and enhance query response times.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If lineage metadata is stored in conventional databases, then data completeness and durability are ensured, but query processing time and resource utilization increase significantly
Solution Approach 1:
The patent segments lineage metadata into two storage locations: frequently accessed metadata is stored in a specialized in-memory data structure for fast retrieval, while the complete metadata repository remains in conventional databases for durability. This segmentation allows the system to balance between quick access and data completeness.
Solution Approach 2:
The patent introduces a specialized in-memory data structure as an intermediary layer between the conventional database and the query processing system. This intermediary caches frequently accessed lineage metadata, reducing the need to query the full database and thereby decreasing processing time while maintaining access to complete data when needed.
2Reliability
If lineage metadata is stored in conventional databases, then data durability is maintained, but processing overhead and resource consumption increase
Solution Approach 1:
The patent divides the metadata storage system into two segments: a specialized in-memory structure for active processing and a conventional database for persistent storage. This allows the system to maintain durable storage while improving processing efficiency for frequently accessed metadata.
Solution Approach 2:
The patent creates copies of frequently accessed lineage metadata and stores them in the specialized in-memory data structure. This copying mechanism allows fast processing of common queries without repeatedly accessing the full database, thereby reducing processing overhead while maintaining data durability in the original database.
3Loss of time
If lineage metadata is stored in memory, then query response time decreases, but storage space requirements increase
Solution Approach 1:
The patent applies local quality by storing only the frequently accessed portion of lineage metadata in the specialized in-memory data structure, rather than storing the entire metadata repository in memory. This allows the system to optimize query response time for common operations while minimizing memory consumption.
Solution Approach 2:
The patent implements partial action by caching only the subset of metadata that is most frequently accessed, rather than loading all metadata into memory. This selective approach achieves significant query response time improvements while keeping storage space requirements manageable.
4Speed
If a specialized data structure is implemented, then metadata access speed increases, but system complexity increases
Solution Approach 1:
The patent designs the specialized in-memory data structure to serve multiple functions: it acts as a cache for fast access, provides a structured format for efficient querying, and maintains compatibility with existing database interfaces. This multi-functionality justifies the added complexity by delivering multiple benefits from a single component.
Solution Approach 2:
The specialized data structure serves as an intermediary layer that translates between the conventional database format and the query processing requirements. While this adds complexity, it enables fast access speeds by pre-organizing data in an optimized format that reduces query processing time.
Data Source
AI summary
Among other things, we describe a method of receiving a portion of metadata from a data source, the portion of metadata describing nodes and edges; generating instances of a data structure representing the portion of metadata, at least one instance of the data structure including an identification value that identifies a corresponding node, one or more property values representing respective properties of the corresponding node, and one or more pointers to respective identification values, each pointer representing an edge associated with a node identified by the corresponding respective identification value; storing the instances of the data structure in random access memory; receiving a query that includes an identification of at least one particular element of data; and using at least one instance of the data structure to cause a display of a computer system to display a representation of lineage of the particular element of data.