Big Data Analytics: Hadoop, Spark

Categories: Analytics, Data, Hadoop, Spark
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About Course

Big data Training

Big Data is a rapidly changing technology space. Techniques such as MapReduce, which were widely used few years back is now not prevalent. We focus on current technologies that are used in big data projects today. We don’t spend time teaching outdated technologies like Java MapReduce and Pig. We focus on Spark, the primary tool used by industry today to solve BigData problems.

Our course gives an outlook towards the various techniques facilitating data analytics on huge datasets. Learners will assess the application of these technologies that provide scalable systems for storing and processing huge amounts of data. This Big Data Hadoop and Spark course help the student understand what Big Data is and how Hadoop solves Big Data problems. Due importance is given to the Hadoop Ecosystem, Hadoop Architecture, HDFS, and the working of MapReduce. This Big Data Hadoop and Spark course will make the aspirant familiar with the installation of Hadoop and Hadoop Ecosystem employed to store and process Big Data. The merits of a distributed batch processing using HDFS are also explained as a part of the course. Students will be comfortable using Apache Pig, Hive, and MapReduce.

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Course Content

Understanding Big Data and Hadoop

  • About Big Data
  • Limitations and Solutions of existing
  • Data Analytics Architecture
  • Hadoop
  • Hadoop Features
  • Hadoop Ecosystem
  • Hadoop 2.x core components
  • Hadoop Storage: HDFS
  • Hadoop Processing: MapReduce
  • Framework
  • Hadoop Different Distributions

Hadoop Architecture and HDFS

Hadoop MapReduce Framework

Advanced MapReduce

Pig

Hive

Advanced Hive and HBase

Advanced HBase

Processing Distributed Data with Apache Spark

Oozie and Hadoop Project