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Idris et al., 2014 - Google Patents

In-map/in-reduce: Concurrent job execution in MapReduce

Idris et al., 2014

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Document ID
17442700469061001296
Author
Idris M
Hussain S
Lee S
Publication year
Publication venue
2014 IEEE 13th International Conference on Trust, Security and Privacy in Computing and Communications

External Links

Snippet

Hadoop based Map Reduce (MR) has emerged as big data processing mechanism in terms of its data intensive applications. In data intensive systems, analysis and visualizations as a result of various algorithms can lead to differentiable and comparable results. Current …
Continue reading at uclab.khu.ac.kr (PDF) (other versions)

Classifications

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    • G06F9/46—Multiprogramming arrangements
    • G06F9/50—Allocation of resources, e.g. of the central processing unit [CPU]
    • G06F9/5061—Partitioning or combining of resources
    • G—PHYSICS
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    • G06F9/06—Arrangements for programme control, e.g. control unit using stored programme, i.e. using internal store of processing equipment to receive and retain programme
    • G06F9/46—Multiprogramming arrangements
    • G06F9/48—Programme initiating; Programme switching, e.g. by interrupt
    • G06F9/4806—Task transfer initiation or dispatching
    • G06F9/4843—Task transfer initiation or dispatching by program, e.g. task dispatcher, supervisor, operating system
    • G06F9/4881—Scheduling strategies for dispatcher, e.g. round robin, multi-level priority queues
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    • G06F9/5005—Allocation of resources, e.g. of the central processing unit [CPU] to service a request
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    • G06F9/505—Allocation of resources, e.g. of the central processing unit [CPU] to service a request the resource being a machine, e.g. CPUs, Servers, Terminals considering the load
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING; COUNTING
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    • G06F9/00—Arrangements for programme control, e.g. control unit
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    • G06Q10/00—Administration; Management
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    • G—PHYSICS
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