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Selecting Efficient Cluster Resources for Data Analytics: When and How to Allocate for In-Memory Processing?

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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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DOI
10.1145/3603719.3603733
OpenAlex
W4379932663
Document type
conference-paper
Language
EN
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