Persistent Query Virtual Tables for Real-Time Database Reporting
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Solution Overview
Problem
Current database systems face challenges in providing real-time reporting due to the time-consuming Extract, Transform, and Load (ETL) process, especially in large datasets, which makes it difficult to generate reports in a timely manner and often results in inaccurate data, as modern systems struggle to accommodate the massive memory requirements for high data throughput environments.
Innovation Solution
A real-time database system that supports persistent queries by creating query virtual tables, parsing queries into tree structures, establishing listeners for data change notifications, and propagating data changes through intermediate virtual tables, allowing for immediate data updates and aggregations, thus enabling faster reporting without the need for massive infrastructure.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional ETL process is used to consolidate and transform data from multiple sources, then data can be consolidated into a uniform arrangement, but the process takes hours or days and cannot provide real-time reporting
Solution Approach 1:
The system pre-establishes virtual tables and data relationships before actual reporting is needed. When data changes occur in source systems, the pre-configured virtual tables automatically update and propagate changes through established relationships, eliminating the need for time-consuming ETL processes during report generation.
Solution Approach 2:
Virtual tables serve as intermediaries between source data systems and reporting applications. These virtual tables abstract the complexity of data consolidation and transformation, providing a uniform data view without requiring physical data movement or complex ETL operations when reports are generated.
2Productivity
If in-memory database is used to achieve fast data access and throughput, then data throughput is improved, but memory requirements become massive and cost-ineffective
Solution Approach 1:
Instead of copying entire datasets into memory, the system creates virtual representations (virtual tables) that copy only the necessary data structures and relationships. These virtual tables maintain data integrity while consuming minimal memory by storing only metadata and pointers rather than complete data copies.
Solution Approach 2:
The system segments data access by creating separate virtual tables for different data sources and relationships. Each virtual table manages its own data cache and retrieval mechanisms independently, allowing selective loading of data into memory only when needed for specific queries rather than loading entire datasets.
3Ease of operation
If data is consolidated into a single database to simplify reporting, then report generation is simplified, but existing legacy systems and functional silos make migration cost prohibitive
Solution Approach 1:
The virtual table system provides a universal interface that works with multiple different data source formats and legacy systems simultaneously. A single reporting application can query data from diverse sources (databases, files, APIs) through unified virtual tables without requiring migration to a single consolidated database, eliminating the need for costly system consolidation while maintaining reporting simplicity.
Data Source
AI summary
A database system supporting persistent queries, using a persistent query service and various data sources. On receiving a request to create a persistent query from a client software application, the persistent query service: creates a query virtual table; parses the persistent query; creates a plurality of intermediate virtual tables; establishes listeners for the query virtual table; creates a plurality of data source virtual tables; causes the plurality of data source virtual tables to retrieve initial data from data sources; and propagates data via intermediate virtual tables to the persistent query virtual table. On detection of a data change in a data source, the associated data source virtual table causes the data change to propagate via intermediate virtual tables to the persistent query virtual table, and the client software application executes client code of at least one listener.