Catalog Query Framework on Distributed Key-Value Store
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Solution Overview
Problem
Current database systems face inefficiencies in processing show commands due to lack of structured frameworks, leading to slow performance and potential system crashes when handling large amounts of data.
Innovation Solution
A framework is introduced that includes a navigation phase and a dependency fetching phase, with each navigation step having a bounded memory limit to prevent memory overload, and a result dependency manager to efficiently process show commands, along with metric tracking to identify performance issues.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If show commands are processed without a structured framework, then the system can handle simple queries, but performance deteriorates and system crashes occur when handling large amounts of data
Solution Approach 1:
The patent segments the show command processing into distinct phases: navigation phase and dependency fetching phase. Each phase is further divided into steps with bounded memory limits, preventing memory overload and system crashes while maintaining processing capability for large datasets
Solution Approach 2:
The patent introduces dynamic memory management where each navigation step has a configurable bounded memory limit. The system dynamically adjusts memory usage by flushing memory between steps, allowing the system to handle variable-sized datasets without crashing while maintaining efficient processing speed
2Quantity of substance
If memory usage is increased to handle large datasets, then more data can be processed, but memory overload occurs leading to system crashes
Solution Approach 1:
The patent divides data processing into multiple navigation steps, each handling a bounded portion of the dataset. This segmentation allows the system to process large quantities of data by treating them as manageable chunks, preventing memory overload while maintaining high data processing capacity
Solution Approach 2:
The patent implements memory flushing between navigation steps, where processed data is discarded from memory and memory resources are recovered for the next step. This enables the system to handle large datasets by continuously recycling memory resources rather than accumulating them, preventing memory overload
3Productivity
If unbounded memory is allocated for show command processing, then all data can be loaded at once, but system resources are wasted and performance decreases
Solution Approach 1:
The patent applies partial action by loading only the necessary bounded portion of data required for each navigation step rather than loading all data at once. This improves memory efficiency and reduces system resource waste while still achieving complete data processing through multiple steps
Solution Approach 2:
The patent changes the memory allocation parameter from unbounded to bounded for each navigation step. This parameter change optimizes memory efficiency and reduces system resource consumption while maintaining the capability to process complete datasets through iterative navigation
Data Source
AI summary
Techniques for executing show commands are described herein. A plurality of navigation steps is utilized, each navigation step corresponding to a different layer in a database structure and each navigation step including an operator to fetch items from a metadata database up to respective bounded limits. Dependency information is also fetched for objects of the specified object type in the show command. After a set of objects from the last layer are processed, memory for the navigation steps is flushed and the next set of objects are processed.