Metadata Label Switching for Real-Time Analytics Data Staging
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Solution Overview
Problem
Conventional systems face performance overhead and service interruptions due to data copying and moving during batch processing and archiving, especially when handling large or infinite data sets for real-time analytics on mobile devices, which struggle with bandwidth limitations and growing data structures.
Innovation Solution
Implementing table-ring based data staging using metadata manipulation to switch labels of data structures without moving or copying data, maintaining results in small-sized tables and using a 'cut-and-rewind' query execution mechanism to support continuous analytics, allowing for efficient data staging without shutting down queries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If data is maintained in a continuously growing data structure to support real-time analytics, then real-time analytics capability is improved, but data structure size grows indefinitely causing performance degradation and service interruptions
Solution Approach 1:
The patent segments the continuously growing data structure into multiple fixed-size tables arranged in a ring buffer structure. Each table stores a portion of the analytics results, and the system cycles through these tables using round-robin assignment. This segmentation prevents any single table from growing indefinitely while maintaining continuous analytics capability across the segmented structure.
Solution Approach 2:
The patent implements periodic action by cycling through fixed-size tables in a round-robin manner. Instead of continuously growing one data structure, the system periodically rotates through multiple tables, overwriting older data in a cyclic pattern. This periodic rotation maintains bounded data structure sizes while supporting continuous real-time analytics.
2Ease of manufacture
If data is archived by moving and copying from one table to another, then old data management is improved, but performance overhead and service interruptions increase
Solution Approach 1:
The patent uses copying to create a metadata label that references the current active table without physically moving the actual data. The label acts as a pointer that can be changed to reference different tables in the ring buffer, enabling efficient data management and archiving through metadata manipulation rather than costly data movement operations.
Solution Approach 2:
The patent introduces a metadata label as an intermediary between the query interface and the actual data tables. This label acts as a mediator that can be changed to point to different tables in the ring buffer, allowing the system to switch between current and archived data without direct data movement or service interruption.
3Use of energy by moving object
If batch processing is used to download data, then bandwidth limitations are addressed, but data copying overhead and performance loss occur
Solution Approach 1:
The patent segments the data into fixed-size tables that can be independently managed and retrieved. This segmentation allows mobile devices to download only the specific table currently referenced by the metadata label, rather than downloading entire datasets. The segmented structure enables efficient batch processing by aligning data retrieval with the fixed table boundaries.
Solution Approach 2:
The patent performs preliminary action by pre-organizing analytics results into fixed-size tables before they need to be retrieved. This advance organization into discrete, manageable units allows for efficient batch downloading when bandwidth is limited, as the data is already structured for optimal transfer and storage.
4Ease of manufacture
If conventional archiving moves data between tables, then data warehouse management is improved, but real-time analytics performance deteriorates due to data movement overhead
Solution Approach 1:
The patent uses copying to create lightweight metadata labels that reference data tables, rather than physically moving the actual data. This copying approach allows the system to manage archived data efficiently while maintaining fast access to current analytics results, as the metadata operations are much faster than data movement operations.
Solution Approach 2:
The patent introduces metadata labels as intermediaries that decouple the archiving management from actual data movement. The labels can be changed to reference different tables without moving the underlying data, enabling efficient data warehouse management while preserving real-time analytics performance through the intermediary layer.
Data Source
AI summary
Data staging for results of analytics according to an example method includes maintaining current results from the analytics in a first data structure, the first data structure having a label identifying first data structure as a target for queries. The method also includes maintaining prior results from the analytics in at least one other data structure. The method also includes changing the label of the first data structure after a predetermined time. The method also includes assigning the label to one of the other data structures, wherein the label identifies the one of the other data structures as the target for queries.