BSDP: A Novel Balanced Spark Data Partitioner

2021 IEEE 27th International Conference on Parallel and Distributed Systems (ICPADS)(2021)

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摘要
As a memory-based distributed big data computing framework, Spark has been widely used in big data processing systems. However, during the execution of Spark, due to the imbalance of input data distribution and the shortage of existing data partitioners in Spark, it is easy to cause partition skew problem and reduce the execution efficiency of Spark. Aiming at this problem, this paper proposes a b...
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关键词
Analytical models,Computational modeling,Distributed databases,Transforms,Big Data,Data models,Scheduling
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