Time-Ordered Backup Objects for Scalable Database Replication
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Solution Overview
Problem
Existing database services face challenges in scaling processing capacity to match workload demands, leading to disruptions and high costs due to interrupted connections and inefficient capacity adjustments.
Innovation Solution
Implementing time and value ordered data objects for backups, which include change logs, active and sealed in-memory tables, and persistent data objects, to efficiently manage database updates and minimize write operations, allowing for faster performance and parallel access.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If processing capacity is increased to match workload demands, then service reliability is improved, but device complexity and cost increase
Solution Approach 1:
The patent segments the database system into multiple independent copies (replicas) that can operate in parallel. Each copy maintains the same data and can handle workloads independently, allowing the system to scale capacity by adding more segments rather than increasing the complexity of a single system.
Solution Approach 2:
The patent creates multiple copies of the database system that can serve workloads simultaneously. By maintaining replicated data across multiple copies and using change logs to track modifications, the system can distribute requests across copies to increase capacity without proportionally increasing complexity.
2Productivity
If multiple copies of data are maintained for scaling, then processing capacity is improved, but write operation complexity increases
Solution Approach 1:
The patent performs preliminary actions by maintaining change logs that record all modifications before they need to be propagated to multiple copies. This preliminary tracking of changes allows the system to efficiently replicate data across copies without complex real-time synchronization, as the change logs already contain the sequence of operations needed.
Solution Approach 2:
The patent uses change logs as an intermediary mechanism between write operations and multiple data copies. Instead of directly managing complex synchronization between copies, the system writes changes to the log first, which then serves as the mediator for propagating updates to all copies in a controlled sequence.
3Reliability
If capacity is increased to avoid disruptions, then service continuity is improved, but cost increases
Solution Approach 1:
The patent makes each database copy universal by ensuring they all contain the same data and can independently handle any workload. This multi-functionality allows the system to distribute requests across multiple copies, increasing capacity and avoiding disruptions without proportionally increasing cost, as each copy serves multiple potential workloads.
Solution Approach 2:
The patent changes the parameter of data redundancy by maintaining multiple copies with identical data. This parameter change allows the system to scale capacity linearly by adding copies, providing service continuity during capacity adjustments without the exponential cost increase that would result from complex synchronization mechanisms.
Data Source
AI summary
Time and value ordering may be applied for items stored in data backups. A change log that persists changes to a data set may be updated with changes and used to update an in-memory table for the data set, which describes changes to items up to a current time. An event may be detected to seal the in-memory table from subsequent updates and a persistent data object that orders the items in the in-memory according to both keys of the respective items and the respective time values of the items, as stored in the change log, may be generated and stored as part of a backup for the data set.