Distributed Database Recovery to Specific Time Point
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Solution Overview
Problem
Current HBase systems cannot recover the system status to a specific time point in a distributed database, lacking consistency in recovery, as they only recover data in units of time and not precise points, and fail to restore the distribution of region servers to a specific time point.
Innovation Solution
A method and system where region servers detect changes, generate event logs with time vectors, create snapshots, and allow the primary server to recover system status by obtaining and analyzing event logs and snapshots to restore the system to a designated time point, using local and global codes to determine event sequences and intervals.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If the primary server recovers data using only period of time as a unit, then the recovery process is simple, but it cannot recover the system status to a specific time point precisely
Solution Approach 1:
The system pre-generates snapshots at different time points and stores them along with event logs before recovery is needed. This preliminary action allows the recovery process to simply select and apply the appropriate snapshot and events, achieving precise time-point recovery without complex real-time processing
Solution Approach 2:
Event logs serve as an intermediary between snapshots and the final recovered state. The logs contain detailed event sequences with time vectors that bridge the gap between discrete snapshots, enabling precise reconstruction of system state at any specific time point within the snapshot range
2Reliability
If the system recovers only data without restoring region server distribution, then the recovery process is faster, but the system status consistency is compromised
Solution Approach 1:
The recovery process is segmented into distinct components: data recovery from snapshots and restoration of region server distribution from event logs. This segmentation allows both data and distribution state to be recovered systematically, ensuring complete system status consistency while maintaining organized recovery procedures
Solution Approach 2:
The event logs serve multiple functions: they record data changes for recovery and simultaneously capture region server distribution changes. This multi-functionality enables a single recovery mechanism to restore both data and distribution state, achieving complete system consistency without requiring separate recovery processes
3Measurement precision
If event logs with time vectors are generated for every system status change, then the recovery precision to specific time point is improved, but the storage requirements and processing complexity increase
Solution Approach 1:
The system adds a time vector dimension to event logs, transforming simple event records into time-stamped events with sequence information. This dimensional enhancement enables precise temporal reconstruction without requiring excessive data, as the time vector provides efficient ordering and identification of events across multiple region servers
Data Source
AI summary
A method for recovering system status consistently to a designed recovering time point in a distributed database, wherein the distributed database comprises a primary server and multiple region servers, comprising: when the region servers detect a change of system status, analyzing an event for the change to generate an event log and storing the event log to the database; after a preset condition, the region servers generate a snapshot respectively; when the primary server receives the instruction to recover the system status to a designed time point, indicates the region servers to implement: reading the event log and snapshots stored in region servers; finding the snapshot closest to the designed time point; finding the event log and snapshot corresponding to an time interval between the time recorded in the snapshot and the designed time point to recover the system status to the designed time point.