Persistent Shuffle Storage for Dynamic Key Range Reallocation
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Solution Overview
Problem
Existing shuffle operations in distributed data processing systems are inefficient when dealing with unbounded or unknown data sets, as optimal key ranges cannot be discernible at the start, and there is a lack of flexibility in reconfiguring during the operation.
Innovation Solution
The system allows for dynamic reconfiguration of shuffle operations by analyzing metadata to adjust key range allocations and stores shuffle results in persistent storage, enabling efficient handling of unbounded data sets and decoupling producers from consumers.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If key range allocations are fixed at the start of the shuffle operation, then the system structure is simple and easy to implement, but the system cannot adapt to unbounded data sets or change in data distribution patterns
Solution Approach 1:
The patent implements dynamic reconfiguration of the shuffle operation by allowing key range allocations to be modified during runtime. The system monitors data distribution patterns and adjusts key range assignments to shufflers dynamically, enabling adaptation to unbounded data sets without requiring a complete redesign of the shuffle architecture.
Solution Approach 2:
The system performs preliminary actions by establishing initial key range allocations before the shuffle operation begins, then prepares for subsequent reconfiguration by maintaining metadata about data distribution. This allows the system to start with a simple configuration and evolve it as needed based on observed data patterns.
2Reliability
If shuffle results are stored in persistent storage, then fault tolerance is improved and operations can resume from failure points, but storage requirements and system complexity increase
Solution Approach 1:
The patent introduces persistent storage as an intermediary layer between the shuffle operation and consumers. This intermediary stores shuffle results in a durable manner, allowing the system to recover from failures by resuming operations from the persisted state rather than requiring complete reprocessing, thereby improving fault tolerance with moderate complexity addition.
3Speed
If the shuffle operation processes all data before consumers can access it, then data consistency is maintained, but the time to deliver data to consumers is increased
Solution Approach 1:
The system performs preliminary shuffle operations on portions of data and stores results in persistent storage before all data processing is complete. Consumers can then access partially processed data from persistent storage while the shuffle operation continues, enabling faster data delivery without compromising overall data consistency for the complete data set.
Data Source
AI summary
A method includes receiving a request to perform a shuffle operation on a data stream; receiving at least a portion of the data stream including a plurality of records, each including a key; storing each of the plurality of records in a persistent storage location assigned to a key range corresponding to keys included in the plurality of records; receiving a request from a consumer for a subset of the plurality of records including a range of keys; and upon receiving the request from the consumer, providing the subset of the plurality of records including the range of keys from the one or more persistent storage locations.