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Cheng et al., 2017 - Google Patents

Cross-platform resource scheduling for spark and mapreduce on yarn

Cheng et al., 2017

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Document ID
2672851979618690775
Author
Cheng D
Zhou X
Lama P
Wu J
Jiang C
Publication year
Publication venue
IEEE Transactions on Computers

External Links

Snippet

While MapReduce is inherently designed for batch and high throughput processing workloads, there is an increasing demand for non-batch processes on big data, eg, interactive jobs, real-time queries, and stream computations. Emerging Apache Spark fills in …
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Classifications

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