Cluster Maintenance Scheduling for Database Node Availability
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Solution Overview
Problem
Existing database systems face limitations in processing speed due to hardware constraints, data storage methods, and restricted co-processing options, leading to inefficiencies in data management and query execution.
Innovation Solution
A database system architecture that employs parallelized data input, storage, and query processing across multiple computing devices, utilizing a parallelized data input sub-system, data store and process sub-system, and query and response sub-system to optimize data partitioning, storage, and query planning for efficient data management and response.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If parallelized processing across multiple computing devices is implemented, then processing speed and efficiency are enhanced, but device complexity and system coordination requirements increase
Solution Approach 1:
The patent divides the database system into multiple independent computing devices (nodes) that each handle portions of data and queries. The data is partitioned across these nodes, and each node can process queries independently, enabling parallel execution. This segmentation allows the system to achieve higher processing speeds while managing complexity through modular architecture.
Solution Approach 2:
Each computing device in the parallelized system is designed to perform multiple functions: storing data partitions, processing queries, coordinating with other nodes, and managing maintenance schedules. This multi-functionality reduces the need for specialized components and simplifies the overall system architecture while maintaining high productivity.
2Reliability
If maintenance scheduling is performed on individual computing devices, then system reliability is improved, but processing time is lost during maintenance operations
Solution Approach 1:
The patent implements a scheduling mechanism that coordinates maintenance operations across multiple computing devices to ensure continuous system operation. When one node undergoes maintenance, other nodes continue processing queries and managing data. The scheduler optimizes maintenance timing to minimize impact on overall system productivity, allowing updates, upgrades, or repairs to be performed without complete system shutdown.
Solution Approach 2:
The system performs preliminary scheduling of maintenance operations, identifying optimal time windows and coordinating between nodes before maintenance begins. This advance planning ensures that maintenance activities are timed to minimize disruption to query processing and data operations, maintaining both reliability and productivity.
3Quantity of substance
If data is stored across distributed computing resources, then system capacity and processing parallelism are increased, but data consistency and coordination overhead increase
Solution Approach 1:
The patent implements coordination mechanisms where computing devices exchange information about data state, query results, and maintenance status. This feedback loop ensures that distributed data remains consistent across nodes, with each node aware of relevant changes made by other nodes. The scheduler uses this feedback to coordinate maintenance operations and ensure data integrity throughout the distributed system.
Data Source
AI summary
A database system includes a lead computing device of a computing device cluster of a plurality of computing device clusters operably coupled to determine that the computing device cluster is due for maintenance. The lead computing device further operable to determine a maintenance schedule of the computing device cluster based on a threshold number of computing nodes of the computing device cluster being available during maintenance, identify a computing device of the computing device cluster to take offline for the maintenance. For an upcoming offline maintenance period, reallocate tasks to be executed by computing nodes of the computing device to computing nodes of one or more other computing devices of the computing device cluster, transition the computing device to an offline maintenance mode after completion of current tasks in accordance with the maintenance schedule, and after completion of the offline maintenance period, transition the computing device to an available mode.