About Big Data Hadoop and Spark Developer

Splunk Education’s learning path for power users takes you from investigative keyword searches to creating rich reports and visualizations to becoming a Splunk search ninja! Splunk Education’s learning path for power users takes you from investigative keyword searches to creating rich reports and visualizations to becoming a Splunk search ninja!

Course Content

  • Introduction to linux and big data virtual machine ( vm)
  • Understanding big data
  • Hdfs (the hadoop distributed file system)
  • How hdfs addresses fault tolerance?
  • Hdfs interfaces
  • Advanced hdfs features
  • Map reduce – 1 (theoretical concepts)
  • Mapreduce architecture
  • Mr algorithm and data flow
  • Alternatives to mr – bsp (bulk synchronous parallel)
  • Map reduce – 2 (practice) developing, debugging and deploying mr programs
  • Writablecom parables
  • Optimization techniques
  • Mr algorithms (non- graph)
  • Mr algorithms (graph)
  • Higher level abstractions for mr (pig)
  • Higher level abstractions for mr (hive)
  • Comparison of pig and hive
  • Different types of nosql databases
  • Columnar databases concepts nosql databases – 2 (practice)
  • Interfaces to hbase (for ddl and dml operations)
  • Advance hbase features
  • Spark
  • Introduction to yarn
  • Introduction to oozie
  • Introduction to flume
  • Introduction to sqoop
  • Setting up a hadoop cluster using apache hadoop
  • Ssh configuration
  • Hadoop ecosystem and use cases
  • Proof of concepts and use cases

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