New Batch On BigData and Hadoop

Vepsun Technologies

#100, S R Arcade, 6th Cross , Tulsi Theatre Road, Marathahalli


September 2
New Batch On BigData and Hadoop

Big Data : The problem space and example applications Why dont traditional approaches scale? Requirements Hadoop Background : Hadoop History The ecosystem and stack: HDFS, Map Reduce, Hive, Pig… Cluster architecture overview Development Environment : Hadoop distribution and basic commands Eclipse development HDFS Introduction : The HDFS command line and web interfaces The HDFS Java API (lab) Map Reduce Introduction : Key philosophy: move computation, not data Core concepts: Mappers, reducers, drivers The Map Reduce Java API (lab) Real-World Map Reduce : Optimizing with Combiners and Practitioners (lab) More common algorithms: sorting, indexing and searching (lab) Relational manipulation: map-side and reduce-side joins (lab) Chaining Jobs Testing with MRUnit Higher-level Tools : Patterns to abstract thinking in Map Reduce The Cascading library (lab) The Hive database (lab)


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