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:  +91 8099 133 133 (India)

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:  +91 8099 133 133 (India)

Course Description

The Apache Spark, Scala and Storm course will enable the participants to understand how Spark enables in-memory distributed datasets that optimize iterative workloads in addition to interactive queries. This course is a part of Developer's learning path.

Prerequisites
  • Some prior experience in Core Java and good analytical skills
  • Basic knowledge of Unix , sql scripting
  • Prior knowledge of Apache Hadoop is not required.
FAQs

What is unique about this Training?

  • Course coverage - designed based on latest industry requirements.
  • Course Material Provided
    • Short notes (compiled for easy reading)
    • Practice exercises
    • eBooks for reference
    • Workbooks for reference
  • Certification and Exam Guidance
    • Question Bank (1000+) provided
    • Internal tests conducted
    • Certification Tips & Techniques provided
  • Project Implementation (Free)
    • At the end of course, a project case study is provided for implementation to gain complete end-to-end experience
    • Gain hands on experience working in a project group
      SDLC - Agile project management methodology
  • CV & Job Interviews
    • Guidance provided to prepare attractive CV
    • Mock Interviews and Job guidance
  • Placement support provided
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Course Contents

Apache Spark

Why Spark? Explain Spark and Hadoop Distributed File System

  • What is Spark
  • Comparison with Hadoop
  • Components of Spark

Spark Components, Common Spark Algorithms-Iterative Algorithms, Graph Analysis, Machine Learning

  • Apache Spark- Introduction, Consistency, Availability, Partition
  • Unified Stack Spark
  • Spark Components
  • Comparison with Hadoop – Scalding example, mahout, storm, graph

Running Spark on a Cluster, Writing Spark Applications using Python, Java, Scala

  • Explain python example
  • Show installing a spark
  • Explain driver program
  • Explaining spark context with example
  • Define weakly typed variable
  • Combine scala and java seamlessly.
  • Explain concurrency and distribution.
  • Explain what is trait.
  • Explain higher order function with example.
  • Define OFI scheduler.
  • Advantages of Spark
  • Example of Lamda using spark
  • Explain Mapreduce with example

RDD and its operation

  • Difference between RISC and CISC
  • Define Apache Mesos
  • Cartesian product between two RDD
  • Define count
  • Define Filter
  • Define Fold
  • Define API Operations
  • Define Factors

Spark, Hadoop, and the Enterprise Data Centre, Common Spark Algorithms

  • How hadoop cluster is different from spark
  • Define writing data
  • Explain sequence file and its usefulness
  • Define protocol buffers
  • Define text file, CSV, Object Files and File System
  • Define sparse metrics
  • Explain RDD and Compression
  • Explain data stores and its usefulness

Spark Streaming

  • Define Elastic Search
  • Explain Streaming and its usefulness
  • Apache bookeeper
  • Define Dstream
  • Define mapreduce word count
  • Explain Paraquet
  • Scala ORM
  • Define Mlib
  • Explain multi graphix and its usefulness
  • Define property graph

 

Scala

Introduction of Scala

  • Scala Overview

Pattern Matching

  • Advantages of Scala
  • REPL (Read Evaluate print loop)
  • Language Features
  • Type Interface
  • Higher order function
  • Option
  • Pattern Matching
  • Collection
  • Currying
  • Traits
  • Application Space

Executing the Scala code

  • Uses of scala interpreter
  • Example of static object timer in scala
  • Testing of String equality in scala
  • Implicit classes in scala with examples.
  • Recursion in scala
  • Currying in scala with examples.
  • Classes in scala

Classes concept in Scala

  • Constructor
  • Constructor overloading
  • Properties
  • Abstract classes
  • Type hierarchy in Scala
  • Object equality
  • Val and var methods

Case classes and pattern matching

  • Sealed traits
  • Case classes
  • Constant pattern in case classes
  • Wild card pattern
  • Variable pattern
  • Constructor pattern
  • Tuple pattern

Concepts of traits with example

  • Java equivalents
  • Advantages of traits
  • Avoiding boilerplate code
  • Linearization of traits
  • Modelling a real world example

Scala java Interoperability

  • How traits are implemented in scala and java
  • How extending multiple traits is handled

Scala collections

  • Classification of scala collections
  • Iterable
  • Iterator and iterable
  • List sequence example in scala

Mutable collections vs. Immutable collections

  • Array in scala
  • List in scala
  • Difference between list and list buffer
  • Array buffer
  • Queue in scala
  • Dequeue in scala
  • Mutable queue in scala
  • Stacks in scala
  • Sets and maps in scala
  • Tuples

Use Case bobsrockets package         

  • Different import types
  • Selective imports
  • Testing-Assertions
  • Scala test case- scala test fun. Suite
  • Junit test in scala
  • Interface for Junit via Junit 3 suite in scala test
  • SBT
  • Directory structure for packaging scala application

Storm

Storm Architecture

  • Baysean Law
  • Hadoop Distributed Computing
  • Features of Big Data
  • Legacy Architecture of Real Time System
  • Difference b/w Storm and Hadoop
  • Logical Dynamic and Components in Storm
  • Topology in Storm
  • Storm Execution Components
  • Stream Grouping
  • Tuple
  • Spout
  • Bolt-normalization bolt

Apache storm installation

  • Apache storm installation

Grouping

  • Grouping and its different type
  • Reliable and unreliable messaging
  • How to get Data – Direct connection and Enqueued message
  • Life cycle of bolt

What is Trident

  • Trident Spouts
  • Types of trident spouts
  • Trident spout components
  • Trident spout Interface
  • Trident filter, function & Aggregator

Boot Stripping

  • What is Twitter Boot Stripping
  • Deep Dive in Boot Stripping
  • Fundamental concept of storm
  • Storm Development Environment

Trainers

Imtiaz

Mr. Imtiaz is having 7+yrs of experience in Corporate and One - One Training. He works for a Leading MNC in Hyderabad and is very passionate about Teaching. He is an expert in Java, BigData, Hadoop Technologies.

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