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Apache Spark and Scala

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 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 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 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

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

I have completed Apache Spark & Scala course from myTectra Review by Numaan

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"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

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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.
WHY DO YOU AWAIT FOR FIXED SCHEDULES ? CHOOSE MYTECTRA LEARN AT YOUR CONVENIENT TIME
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]

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