Database Recovery Batch Processing Log Replay
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Solution Overview
Problem
Restoring a database to a consistent state after a failure is a time-consuming and resource-intensive process due to the need to replay each transaction individually from the log, which can be inefficient in terms of time and computing resources.
Innovation Solution
Implementing a database recovery system that enables batch processing of logged transactions, where transactions are grouped and processed together rather than individually, allowing multiple processors to handle different transactions simultaneously and reducing the number of messages and disk accesses required.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If transactions are replayed one-at-a-time from the log after database failure, then data consistency is restored, but the recovery process becomes time-consuming and resource-intensive
Solution Approach 1:
The patent combines multiple individual transaction replay operations into a single batch processing operation. Instead of replaying transactions sequentially one-at-a-time, the system groups multiple log records into batches and processes them simultaneously, maintaining data consistency while dramatically reducing recovery time and resource consumption.
Solution Approach 2:
The patent segments the recovery process into distinct phases: identifying batchable log records, grouping them into batches, and processing each batch as a unit. This segmentation allows the system to apply batch processing specifically to suitable transactions while maintaining proper transaction boundaries and consistency requirements.
2Reliability
If transactions are replayed one-at-a-time from the log after database failure, then each transaction is processed correctly, but computing resources are consumed inefficiently
Solution Approach 1:
The patent merges multiple individual transaction processing operations into a single batch processing operation. By combining the work of processing multiple transactions into one unified operation, the system reduces overhead costs such as message passing, disk accesses, and processor context switches, thereby decreasing overall computing resource consumption while maintaining correctness.
Solution Approach 2:
The patent enables continuous batch processing of log records during recovery, eliminating the idle time and overhead associated with sequential processing. Multiple processors can work continuously on different batches simultaneously, maximizing resource utilization and reducing total recovery time and energy consumption.
3Productivity
If batch processing is implemented for log replay, then recovery speed and efficiency improve, but system complexity increases
Solution Approach 1:
The patent segments the batch processing system into distinct functional modules: log record analysis, batch formation, batch processing execution, and result consolidation. This modular segmentation manages system complexity by organizing functions into separate, manageable components while enabling high-speed batch processing through coordinated operation of these modules.
4Loss of energy
If batch processing is used for database recovery, then the number of messages and disk accesses is reduced, but processing logic becomes more complex
Solution Approach 1:
The patent merges multiple message passing operations and disk access operations into fewer batched operations. Instead of sending individual messages or performing separate disk accesses for each transaction, the system consolidates these operations into batch processing units, reducing overall communication overhead and I/O operations while managing processing logic complexity through structured batch handling.
Data Source
AI summary
Disclosed herein are system, method, and computer program product embodiments for a database recovery and optimization with batch processing system. An embodiment operates by retrieving a database log that includes a plurality of operations for modifying data of a database stored across a plurality of tables. From the database log, a plurality of consecutive insert operations for inserting data into the database are identified. The consecutive insert operations are sorted by table. The sorted insert operations are grouped into a batch message. The batch message is transmit to the database for replay. An acknowledgement is received that the replay has completed.