Publication | Closed Access
POLM2
15
Citations
47
References
2017
Year
Unknown Venue
Cluster ComputingBig Data AcquisitionEngineeringData ScienceData MiningCloud ComputingBig Data ApplicationsData IntegrationBig Data ArchitectureGarbage CollectionComputer ScienceHigh Pause TimesMassive Data ProcessingData ManagementBig Data InfrastructureBig Data
Big Data applications suffer from unpredictable and unacceptably high pause times due to bad memory management (Garbage Collection, GC) decisions. This is a problem for all applications but it is even more important for applications with low pause time requirements such as credit-card fraud detection or targeted website advertisement systems, which can easily fail to comply with Service Level Agreements due to long GC cycles (during which the application is stopped). This problem has been previously identified and is related to Big Data applications keeping in memory (for a long period of time, from the GC's perspective) massive amounts of data objects.
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