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Song et al., 2023 - Google Patents

Memory management optimization strategy in Spark framework based on less contention

Song et al., 2023

Document ID
13113373437988323369
Author
Song Y
Yu J
Wang J
He X
Publication year
Publication venue
The Journal of Supercomputing

External Links

Snippet

The parallel computing framework Spark 2. x adopts a unified memory management model. In the case of the memory bottleneck, the memory allocation of active tasks and the RDD (Resilient Distributed Datasets) cache causes memory contention, which may reduce …
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Classifications

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    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
    • G06F9/5011—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resources being hardware resources other than CPUs, Servers and Terminals
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    • G06F11/3442—Recording or statistical evaluation of computer activity, e.g. of down time, of input/output operation; Recording or statistical evaluation of user activity, e.g. usability assessment for planning or managing the needed capacity
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