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Big data with spark scala

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40 Hours

Course offered by Satendra Kumar

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                                                                       BIG DATA

Introduction to Big Data

  • Overview of Big Data Technologies and its role in Analytics
  • Big Data challenges & solutions
  • Data Science vs Data Engineering
  • FOUR V's of Big Data given by Google.

Unix & Java

  • Introduction to UNIX shell.
  • Basic Commands of UNIX
  • Create
  • Copy
  • Move
  • Delete etc.
  • Basic of JAVA Programming Language
  • Architecture JVM, JRE, JIT
  • Control Structures
  • OOP's Concept in Java
  • String Classes/Array/Exception Handling
  • Collection Classes

Apache HDFS

  • Understanding the problem statement and challenges persisting to such large data to
  • perceive the need of Distributed File System.
  • Understanding HDFS architecture to solve problems
  • Understanding configuration and creating directory structure to get a solution of the given
  • problem statement
  • Setup appropriate permissions to secure data for appropriate users
  • Setting up Java Development with HDFS libraries to use HDFS Java APIs

Apache Map-Reduce

  • What is Map Reduce.
  • Input and output formats.
  • Data Types in Map Reduce.
  • Flow of Map Reduce Jobs.
  • Wordcount In Map Reduce.
  • How to use Custom Input Formats
  • Use case for Structure Data Sets.
  • Writing Custom Classes.

 

 

APACHE HIVE

  • What is HIVE.
  • Architecture of HIVE.
  • Tables in Hive with Load Functions.
  • Query Optimization.
  • Partitioning and Bucketing.
  • Joins in HIVE.
  • Indexing In HIVE.
  • File Formats in HIVE.
  • How to read JSON files in HIVE.

APACHE SQOOP

 

  • What is Sqoop.
  • Relation between SQL & Hadoop.
  • Performing Sqoop Import.
  • Incremental and Conditional Imports
  • Performing Sqoop Export.

PIG

  • What is PIG & ETL.
  • Introduction to PIG Architecture.
  • Introduction of PIG Latin.
  • How to Perform ETL on any Kind of data
  • (PIG Eats Everything)
  • Use cases of PIG.
  • Joins in PIG.
  • Co-grouping In PIG.

Introduction to NoSQL Database &OOZIE

  • What is HBASE.
  • Architecture of HBASE.
  • CRUD operations in HBASE
  • Retrival of HBASE Data.
  • Introduction of Apache Oozie (Scheduler tool)

Introduction to Programming in Scala

  • Basic data types and literals used
  • List the operators and methods used in Scala
  • Classes of Scala
  • Traits of Scala.
  • Control Structures in Scala.
  • Collection of Scala.
  • Libraries of Scala.

 

Introduction to Spark

  • Limitations of MapReduce in Hadoop Objectives
  • Batch vs. Real-time analytics
  • Application of stream processing
  • Spark vs. Hadoop Eco-system

Using RDD for Creating Applications in Spark

  • Features of RDDs
  • How to create RDDs
  • RDD operations and methods
  • Explain RDD functions and describe how to
  • write different codes in Scala

Running SQL queries Using SparkQL

  • Explain the importance and features of SparkQL
  • Describe methods to convert RDDs to
  • DataFrames
  • Explain concepts of SparkSQL

Describe the concept of hive integration

Spark ML Programming

  • Explain the use cases and techniques of
  • Machine Learning (ML)
  • Describe the key concepts of Spark ML
  • Explain the concept of an ML Dataset, and ML
  • algorithm, model selection via cross validation

About the Trainer

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Satendra Kumar

Mca

12 Years of Experience

Working IT professnal

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