PhD-Guidance-in-Mapreduce
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Major applications of MapReduce include genome big data analysis, predictive analytics, data mining and visualization, stream processing, and data warehousing. Common tools used for MapReduce include Netbeans, Sqoop, HBase, HIPI, Disco, and Gigaom. Modern research topics in MapReduce involve distributed processing, data storage and analytics, privacy and security, DNA sequence alignment, and statistical machine translation.
PhD-Guidance-in-Mapreduce
- 2. 2 MAJOR APPLICATIONS IN MAPREDUCE We use major applications to develop the Mapreduce based research work, 1 Genome big data analysis 2 Predictive and advanced analytics 3 Data mining/visualization 4 Mapreduce stream processing 5 Data warehouse offloading 6 ETL /data integration
- 3. Netbeans Sqoop HBase HIPI Disco Gigaom UPPERMOST TOOLS IN MAPREDUCE Uppermost following tools are used to implement the Mapreduce thesis work, 1 2 3 4 5 6
- 4. Distributed and parallel processing Data storage and analytics Privacy and security DNA sequence alignment Statistical machine translation MODERN RESEARCH TOPICS IN MAPREDUCE We give more modern research topics in Mapreduce for PHD scholars below, 1 2 3 4 5