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Apache Spark and Scala

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Apache Spark and Scala Training in Bangalore - Live Online & Classroom

myTectra the Market Leader in Apache Spark and Scala Training in Bangalore

myTectra offers Apache Spark and Scala training in Bangalore using Class Room. myTectra offers Live Online Apache Spark and Scala Training Globally.


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
Spark Persistence In Spark
Scala and Python
Examples – K-means
Latent Dirichlet Allocation (LDA)
Broadcast And Accumulator
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 SQL And 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
Pattern Matching
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 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
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
Use Case Bobsrockets Package
Different import types
Selective imports
Scala test case- scala test fun. Suite
Junit test in scala
Interface for Junit via Junit 3 suite in scala test
Directory structure for packaging scala application

To Learn Live Online Apache Spark and Scala Training Globally and Apache Spark and Scala Training in Bangalore using Class Room, ENROLL TODAY at myTectra.

Customer Reviews

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Good Training Review by Murthy
I acknowledge that the course is completed. Thanks for the content coverage, and it was the way I expected it to be.
I thank Sudheer for providing timely clarification for all of my queries and of-the class support.
Best place to learn Review by Suhas
Spark course conducted by Mr Alok Mathur has been completed. It was very through and extensive course covering all aspects of usage of the framework.

Good teaching Review by Gaurav
Would like to mention here that Alok Mathur is the best trainer we ever had and an equally wonderful person too. The kind of experience he brings in while covering the course is immense. His teaching methodology is par excellence and he doesn't hesitate to cover the topics even 7-8 times if we have doubts and never in a hurry to just cover the topics. He makes sure that whatever topics he cover we should be confident enough to tackle it in the real world.

Finally I would like to give a big THANKS to ALOK MATHUR :-)

I have completed Apache Spark & Scala course from myTectra Review by Numaan
"It was a very good and learning experience under the guidance of Trainer, who has in depth knowledge and a very interactive method of teaching. The topics were covered adequately and a good amount of practical work was done to understand the topics thoroughly. I am glad to have taken the course."AWESOME..
best institute Review by Jagadeesh
Hi, I completed my Apache spark and scala institute in mytectra. They give good placement facilities and lab facilities for practicing.

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myTectra Stands for Quality Training and provides training using Experienced professionals on the Respective Technologies and who has a good teaching expertise.


myTectra flexible batch schedules enables you to start your class at your convenient date and time.

1. All the enrolled candidates must start the class by any date within 30 days from the date of enrollment.
2. Maximum of 3 Days will be taken by myTectra to schedule the batches from the date of schedule request from the candidate.
3. Individual Focus - Maximum 5 candidates allowed per batches
4. The candidate can request any one of the batch time slot from the below list
Batch Type Time Slab Hours/Day Time Zone Days
Regular Morning 6.30 AM - 9.30 AM Anytime Maximum 2 Hrs IST Monday-to-Friday
Regular Evening 6.30 PM - 9.30 PM Anytime Maximum 2 Hrs IST Monday-to-Friday
Week End 6.30 AM - 9.30 PM Anytime Maximum 3 Hrs IST Saturday,Sunday
Fast Track-Morning 6.30 AM - 9.30 AM Anytime Maximum 2 Hrs IST Monday-to-Saturday
Fast Track-Evening 6.30 PM - 9.30 PM Anytime Maximum 2 Hrs IST Monday-to-Saturday
Customized Batch Customized Timing Customized Hrs IST Customized Days

Note : We can schedule your batch anytime on Saturday and Sunday between 6.30 AM 9.30 PM at your convenient time

Do you have any questions ? please call us on +919019191856 or email to [email protected]