conference-paper
Open access
Selecting Efficient Cluster Resources for Data Analytics: When and How to Allocate for In-Memory Processing?
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- 2
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Paper overview
Abstract
Distributed dataflow systems such as Apache Spark or Apache Flink enable parallel, in-memory data processing on large clusters of commodity hardware. Consequently, the appropriate amount of memory to allocate to the cluster is a crucial consideration.
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Publication details
- DOI
- 10.1145/3603719.3603733
- OpenAlex
- W4379932663
- Document type
- conference-paper
- Language
- EN
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