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Fast and Effective Root cause Analysis of Streaming Data using In-Memory Processing Techniques
2017
Indian Journal of Science and Technology
Objectives: Increased data generation mandates a highly scalable and powerful processing framework for root cause analysis. The objective is to identify such a framework by analyzing the existing processing architectures. Methods/Analysis: In-order to identify the best processing architecture for root-cause analysis, the existing architectures are divided in terms of sequential processing using python, CPU based parallelization, Hadoop MapReduce and Spark based parallel in-memory processing.
doi:10.17485/ijst/2017/v10i38/114003
fatcat:5nvppkn4q5bgzg2royrjfno2xu