Job Count Accumulators for Low-Latency Data Delivery
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Solution Overview
Problem
Existing systems face inefficiencies in generating and managing job counts for data delivery, leading to system latency and unnecessary resource consumption due to inadequate data tracking and management.
Innovation Solution
A data management system that generates and manages job counts by using a count accumulator, maintaining offset records, and writing updates in a single transaction to ensure exactly-once processing, thereby reducing latency and minimizing data loss during system failures.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional data tracking and management methods are used, then system complexity is reduced, but system latency increases and resource consumption increases
Solution Approach 1:
The patent introduces an intermediary component (job count manager with count accumulator) that sits between the data processing system and the tracking mechanism. This intermediary aggregates individual job completion events into batched count updates, reducing the direct interaction frequency and complexity while maintaining accurate tracking. The intermediary translates granular job events into consolidated count records, solving the contradiction between detailed tracking and system simplicity.
Solution Approach 2:
The patent creates a simplified copy or representation of the actual job processing state through count accumulators. Instead of tracking every individual job event in detail, the system maintains a copy in the form of aggregated count values that represent the overall processing state. This copying approach reduces the complexity of real-time tracking while preserving the essential information needed for monitoring and management.
2Measurement precision
If frequent job count updates are performed, then data accuracy is improved, but system latency increases
Solution Approach 1:
The patent implements periodic action by batching multiple job completion events into consolidated count updates. Instead of updating job counts immediately with each individual job completion, the system accumulates events and performs periodic batch updates. This periodic approach maintains measurement precision over time intervals while significantly reducing the frequency of update operations, thereby lowering system latency and resource consumption.
Solution Approach 2:
The system performs preliminary accumulation of job events before executing the actual count update. By pre-aggregating multiple events into a single batched update operation, the system prepares the data in advance, reducing the need for frequent individual update operations. This preliminary action maintains accuracy while minimizing the time overhead associated with continuous updating.
3Reliability
If multiple transaction writes are used for job count tracking, then data reliability is improved, but resource consumption increases
Solution Approach 1:
The patent merges multiple individual transaction writes into a single batched transaction operation. By combining multiple job count updates into one consolidated write operation, the system maintains the reliability benefits of transactional processing (atomicity, consistency) while dramatically reducing the total number of database transactions required. This merging approach preserves data reliability guarantees without the proportional resource consumption of multiple separate transactions.
Solution Approach 2:
The batched transaction mechanism serves multiple functions simultaneously: it maintains data reliability through transactional guarantees, reduces resource consumption by minimizing transaction overhead, and improves efficiency by processing multiple updates in a single operation. This multi-functional approach resolves the contradiction between reliability and resource usage.
4Loss of information
If detailed job tracking is implemented, then data loss prevention is improved, but system complexity increases
Solution Approach 1:
The job count manager acts as an intermediary that simplifies the tracking mechanism while preventing data loss. It maintains a count accumulator that aggregates job events and persists these counts in a manageable format. This intermediary layer protects against data loss during system failures by ensuring counts are properly recorded and can be recovered, without requiring complex individual job tracking infrastructure.
Solution Approach 2:
The system maintains a simplified copy of the job processing state through count accumulators rather than tracking complete detailed records of every job. This copying approach preserves the essential information needed to prevent data loss (the count of processed jobs) while avoiding the complexity of maintaining full detailed tracking records. The count copy serves as a reliable checkpoint for recovery without the overhead of detailed tracking.
Data Source
AI summary
Various embodiments include systems, methods, and non-transitory computer-readable media for managing data. Consistent with these embodiments, a method includes receiving a message that includes a delivery status of an event; generating a value of a count accumulator based on the receiving of the message; transmitting the message to a storage unit; identifying an offset that corresponds to the message; and writing, in a single transaction, the offset and the value of the count accumulator in a report database.