Synchronized Dataset Replacement to Avoid Update Traffic Spikes
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Solution Overview
Problem
Large-scale data processing systems face challenges in synchronizing datasets across multiple services or clients, leading to data inconsistency, errors, and increased system load due to simultaneous updates, which degrade performance and user experience.
Innovation Solution
A method and apparatus for synchronized data replacement involving randomized querying within a request period, where processing clients receive an indication to request an updated dataset at random times, store it before an expiration time, and replace the old dataset at the expiration time, reducing system load and maintaining synchronization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If simultaneous updates are performed across multiple services or clients, then data consistency is improved, but system load increases and performance degrades
Solution Approach 1:
The system performs preliminary actions by sending dataset replacement indications and allowing clients to fetch updated datasets before the expiration time. This prepares the system in advance for the replacement event, distributing the load over time rather than concentrating it at the moment of replacement, thus maintaining data consistency while avoiding peak system load.
Solution Approach 2:
The system implements periodic action through the use of expiration times and request periods. Clients are instructed to request datasets at randomized times within a request period, and replacements occur at scheduled expiration times. This periodic structure distributes system operations over time, reducing instantaneous load while maintaining synchronization across clients.
2Reliability
If simultaneous updates are performed across multiple services or clients, then data consistency is improved, but traffic spikes increase
Solution Approach 1:
Clients perform preliminary actions by requesting and storing updated datasets before the expiration time during the request period. This preliminary fetching of data prevents traffic spikes at the replacement moment, as the actual replacement involves only a simple pointer swap rather than large data transfers, while still ensuring all clients have the updated data for consistency.
Solution Approach 2:
The system uses periodic action through request periods and expiration times to distribute traffic. Clients are instructed to request datasets at randomized times within the request period, spreading out the traffic load. The actual replacement occurs periodically at the expiration time, avoiding continuous or simultaneous traffic spikes across all clients.
3Reliability
If datasets are updated across multiple services or clients, then data synchronization is improved, but the complexity of coordination increases
Solution Approach 1:
The system introduces an intermediary element - the dataset replacement indication - that coordinates between the data source and multiple clients. This indication contains all necessary information (expiration time, request period, dataset identifier) that clients need to synchronize their updates independently. The intermediary structure simplifies coordination by providing a single source of truth that clients can follow autonomously, reducing the complexity of direct client-to-client or client-to-server coordination.
Data Source
AI summary
A processing client may receive a dataset replacement indication that indicates an upcoming synchronized data replacement in which processing clients are to synchronously replace a first synchronized dataset with a second synchronized dataset as well as a request period during which the processing clients are to request, at randomized times, the second synchronized dataset. The processing client may transmit a query requesting the second synchronized dataset. The processing client may receive a response including the second synchronized dataset and an indication of an expiration time for the first synchronized dataset that indicates when the processing clients are to replace the first synchronized dataset. The processing client may store, at the processing client prior to the expiration time, the second synchronized dataset and the indication of the expiration time. The processing client may replace, in response to the expiration time occurring, the first synchronized dataset with the second synchronized dataset.