Automated Data Migration in HDFS Federation
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Solution Overview
Problem
Manual data migration in Hadoop Distributed File System (HDFS) federations is cumbersome and inefficient, leading to performance bottlenecks and increased workload for maintenance engineers due to the primary/secondary architecture and metadata management overhead.
Innovation Solution
An automated method for generating a data migration plan using a configuration file that identifies source and target subclusters based on migration trigger factors, employing linear programming to optimize data distribution across subclusters, thereby reducing the workload and maximizing the HDFS federation architecture's efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual data migration is performed in HDFS federation, then data can be moved between subclusters, but the workload for maintenance engineers increases and the process becomes cumbersome
Solution Approach 1:
The system enables self-service automated data migration by implementing self-detection of migration needs through scanning subcluster statuses, self-decision making through linear programming optimization to determine optimal migration plans, and self-execution through automated migration operations. This eliminates the need for manual intervention while balancing data distribution across the federation.
2Quantity of substance
If data is distributed across multiple subclusters in HDFS federation, then storage capacity and fault tolerance are improved, but metadata management overhead and performance bottlenecks increase
Solution Approach 1:
The system implements feedback mechanisms by continuously scanning subcluster statuses to detect data distribution imbalances, using the detected information to trigger automated migration operations when thresholds are exceeded, and adjusting migration plans based on real-time federation state to optimize metadata management and reduce complexity.
3Productivity
If automated migration planning is implemented, then data distribution is optimized and workload is reduced, but system complexity increases due to linear programming requirements
Solution Approach 1:
The system introduces an intermediary automated migration planning component that acts as a mediator between the distributed subclusters. This intermediary uses linear programming to optimize migration decisions, managing the complexity internally while presenting a simplified interface for data distribution optimization and workload reduction across the federation.
Data Source
AI summary
In an approach, a processor obtains a configuration file of a distributed file system federation, the configuration file comprising a list of a plurality of subclusters within the distributed file system federation and migration trigger factors for the plurality of subclusters. A processor determines a list of one or more source subclusters and a list of to-be-migrated directories in the one or more source subclusters based on a scanning result of the plurality of subclusters and the migration trigger factors in the configuration file. A processor generates a migration plan to migrate the to-be-migrated directories from the one or more source subclusters to one or more target subclusters in the distributed file system federation.