PIG ONLINE TRAINING

PIG COURSE CONTENT

    The Hadoop Ecosystem

  • Hadoop overview
  • Surveying the Hadoop components
  • Defining the Hadoop architecture
  • Exploring HDFS and MapReduce

    Storing data in HDFS

  • Achieving reliable and secure storage
  • Monitoring storage metrics
  • Controlling HDFS from the Command Line
  • Parallel processing with MapReduce

  • Detailing the MapReduce approach
  • Transferring algorithms not data
  • Dissecting the key stages of a MapReduce job
  • Automating data transfer

  • Facilitating data Ingress and Egress
  • Aggregating data with Flume
  • Configuring data fan in and fan out
  • Moving relational data with Sqoop
  • Executing Data Flows with Pig

    Describing characteristics of Apache Pig

  • Contrasting Pig with MapReduce
  • Identifying Pig use cases
  • Pinpointing key Pig configurations
  • Advanced Pig

  • Pig Latin: Relational Operators
  • File Loaders
  • Group Operator
  • CO GROUP Operator
  • Joins and CO GROUP
  • Union, Diagnostic Operators
  • Pig UDF
  • Structuring unstructured data

  • Representing data in Pig's data model
  • Running Pig Latin commands at the Grunt Shell
  • Expressing transformations in Pig Latin Syntax
  • Invoking Load and Store functions
  • Performing ETL with Pig

    Transforming data with Relational Operators

  • Creating new relations with joins
  • Reducing data size by sampling
  • Extending Pig with user–defined functions
  • Filtering data with Pig

  • Consolidating data sets with unions
  • Partitioning data sets with splits
  • Injecting parameters into Pig scripts

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Testimonials

"The Bigdata Training was pretty good, it was a very good experience, and I am also looking forward to take more trainings from Mentors Inn on other technologies as and when required for me." -Sridevi (Hadoop)