Apache Spark and Scala Training in Bangalore myTectra

Unlock your Learning Potential !
ISO 9001:2008
Certified Company
Course details:
Course Code : MYT953
Course Name :Apache Spark and
Scala
Course duration: Fast track – 4 weeks
Regular weekdays – 6 weeks
Week End – 8 weeks
Training mode:
instructor led class training | Live virtual training
Contact: +91 90191 91856
Email:info@mytectra.com
Web: www.mytectra.com

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
myTectra Learning Solutions private Limited
Bangalore-BTM Layout/
+91 90191 91856/ info@mytectra.com / www.mytectra.com

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 bookkeeper
 Define Dstream
 Define Mapreduce word count
 Explain Paraquet
 Scala ORM
 Define Mlib
 Explain multi graphix and its usefulness
 Define property graph

Spark Persistence In Spark
 Persistence
 Motivation
 Example
 Transformation
 Scala and Python
 Examples – K-means
 Latent Dirichlet Allocation (LDA)
Broadcast And Accumulator
 Motivation
 Broadcast Variables

 Example: Join
 Alternative if one table is small
 Better version with broadcast
 How to create a Broadcast
 Accumulators motivation
 Accumulator Rules
 Custom accumulators
 Another common use
 Creating an accumulator using spark context object
Spark SQLAnd RDD
 Spark SQL main capabilities
 Spark SQL usage diagram
 Spark SQL

 Important topics in Spark SQL- Data frames
 Twitter language analysis
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
 Prop erties
 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

Apache Spark and Scala Training in Bangalore myTectra

Recommended

Recommended

More Related Content

What's hot

What's hot (8)

Similar to Apache Spark and Scala Training in Bangalore myTectra

Similar to Apache Spark and Scala Training in Bangalore myTectra (20)

More from myTectra Learning Solutions Private Ltd

More from myTectra Learning Solutions Private Ltd (20)

Recently uploaded

Recently uploaded (20)

Apache Spark and Scala Training in Bangalore myTectra