Hadoop and Spark developer 5/5 (4)

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Our Hadoop & Spark developer Program is designed by the industry experts. These skills fulfill the requirements of jobs related to Big data data. Now a days there are huge requirements of Big data professionals in the industry.

  • GOLD
18 Sessions
54 Hours

Skills you will master



Mob : +91-9810600764
Address : M8, Lower ground Floor, Sector 14 OLD DLF Gurgaon 122001
Email : info@palin.co.in


About The Program

Our Hadoop & Spark developer Program is designed by the industry experts. These skills fulfil the requirements of jobs related to Big data data. Now a days there are huge requirements of Big data professionals in the industry. This program gives you high quality content to store and process  the raw data. Training includes Industry specific data as well as assignments, case study, project.

During the training participants will be going through


After the completion of the course you will be able to crack the interviews with most of the renowned organizations like Airtel, IBM, UHG, Amazon, Flipkart and many more.


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Career Advisor
Nitesh Saharan, Consultant
Palin Analytics delivers real world relevance with activities and assignments that helps students build critical thinking and analytic skills that will transfer to other courses and professional life.
Program Description
Hadoop & Spark developer program is designed as per the needs of developers in the industry who are good at programming specially in Java to build methods to process large amount of data over hadoop platform. It includes HDFS architecture and mapreduce basic and advance along with hive queries to perform ETL functions over HDFS along with all major hadoop constituents like scoop, impala, pig, zookeeper and apache spark with RDD, spark streaming, spark SQL and Scala.
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   Session 1 - Introduction to Big Data

Understand what big data is? Limitation of existing systems, Hadoop ecosystem, Understanding Hadoop 2.x component, Performing read and write operations, RAC awareness, Installation of Hadoop in virtual machine

   Session 2 - Hadoop Architecture & HDFS

Hadoop Architecture, Horizontal scaling, Movement of only code and not data over network, High availability, Scalability: Multiple Name node, HDFS Commands, Hadoop configuration files, Password less SSH

   Session 3 - Hadoop Mapreduce framework

How MapReduce is different from traditional way, Hadoop 2.x Mapreduce architecture and component, Understand processing part i.e. YARN, Mapreduce concept, Run the basic Mapreducer program

   Session 4 - Hadoop MapReduce Framework : go further

Understanding Input Splits, Mapreduce job submission flow, Performance improvement using combiners, Partitioners, Mapreduce as a whole

   Session 5 - MapReduce Advanced

Understanding counters, Map Side Join, Reduce side Join, MR units,Custom input formats, Sequence file format

   Session 6 - PIG

Why and how PIG came into picture, Where PIG is a good fit, Where PIG should not be used, Conceptual data flow, Different versions of PIG execution, Data models in PIG, PIG relational operators, UDF in PIG: Customized function in Java, Describe, explain and illustrate, Demo

   Session 7 - HIVE

Why and how HIVE came into picture? How is this different from PIG? Hive architecture and component, Where and where not HIVE to be used? Data type is HIVE. Perform basic HIVE operations.

   Session 8 - Advance Hive

HIVE UDF, Joins in HIVE, Dynamic partitioning, Create UDF for HIVE, Performance Tuning

   Session 9 - HBASE and Zookeeper

Understand NoSQL database, Understand CAP theorem, Comparison of RDBMS and HBASE, HBASE Architecture, How updated is implement on top of HDFS, Data model and physical storage in HBASE, Execute basic HBASE command, Data loading techniques in HBASE, Understaning Zookeeper.

   Session 10 - Flume, Sqoop, OOZIE and PROJECT

Implement Flume and Sqoop, Understand Oozie, Schedule job in Oozie, Oozie workflow, Project.

   Session 11 - Introduction to Apache Spark

What is spark, Implement Spark operations on Spark Shell, Understand Spark and its Ecosystem, Spark Common operations, Advantages of Spark, How Spark fits in with the big data application stack, How Spark fits in with Hadoop, Define Apache Spark components

   Session 12 - Build A Simple Spark Application

Define the lifecycle of a Spark programme, Define the function of SparkContext: Lab: create the application, Define different ways to run a Spark application, Run your Spark application: Lab: launch the application

   Session 13 - Playing with RDD

Learn how to work in RDD in Spark, Understand the role of Spark RDD

   Session 14 - Sprak Streaming and Spark SQL

Understand Spark SQL architecture, Learn Spark Streaming API

   Session 15 - Create an Apache Spark Streaming Application

Spark streaming architecture, Create DStreams, Create a simple Spark Streaming application: Lab: Create a Spark Streaming application, DStream operations: Lab: Apply an operations on DStreams, Apply DStream operations, Use Spark SQL to query DStreams, Define window operations: Lab: Add windowing operations, Use Spark SQL to query DStreams, Define window operations: Lab: Add windowing operations, Describe how DStreams are fault-tolerant

   Session 16 - Introduction to Scala

Introduction : What is Scala? Scala in other Frameworks, Scale REPL, Basic Scala Operations, Functions and Procedures, Collections, Control Structures, OOPS and Functional Programming in Scala

   Session 17 - Scala Continued

Classes in Scala, Getters and Setters, Constructors and Singletons, Companion Objects, Inheritance in Scala, Traits and Layered Traits, Functional Programming in Scala


Industry Specific Project

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Program Highlights
Instructor led training is the live and interactive training by industry professionals
Live Case Study
A project undertaken by you in supervision of the trainers will be conducted once
Assignments which helps in conceptual understanding, Prepared for interview training & techniques.
Lifetime Access
Access to all the recording for the lifetime and avoid notes maintaining chios.
24 X 7 Support
Consultants are available online for proper guidance about the course.
After successful completion of the training and case study Palin will certify you as Palin certified Hadoop & Spark Developer.
Career Counselor
Avail career guidance and Professional guidance for resume building, unlimited opportunities and interviews.

Highly motivated with leadership skills from premier institute having Master’s Degree in computer application . Holds good working experience in different domains like Telecom, Banking, FMCG. With the skill set of Big Data Developer as well as analytics.
   Who are the trainers?
All of our highly-qualified Big data professionals are certified, with more than 10 years of experience in training and working professionally in the same field. Each of them has gone through a rigorous selection process that includes profile screening, technical evaluation and live training demonstration before they are certified to train for us. We also ensure that only those trainers who maintain a high alumni rating continue to train for us.
   Who can go for Hadoop & Spark Developer?
Any Graduate having a programming background and database handling skills can opt Hadoop & Spark developer program to make his career into big data profiles
   What is Hadoop & Spark Developer?
Hadoop is a platform used to store and process very large amount of data which cannot be possible in conventional databases using distributed storage and computing which turns out to be the solution for all big data problems using scala on apache spark
   Is this a classroom training or online?
Palin Analytics offers you both the platforms for the training you can opt either online or classroom.
   Which one is better classroom or online?
Both the training modes are good to get trained. But online training is more better than the classroom training because online trainings are live interactive where you can raise your concerns at any point during the session. Additionally recording of the same session will be provided which you can access anytime anywhere.
   What all topics will be covered in Hadoop & Spark Developer training?
Big Data Introduction, HDFS, Mapreduce, PIG, Hive, HBase, Sqoop, Flume, Oozie, spark constituents, unified stack spark, common spark algorithms, scala, RDD, spark streaming, Broadcast and accumulator, Spark SQL, Scheduling, Log Analysis, Pattern Matching, Classes in scala, Traits, Scala collections, Use cases, oops concepts.
   After the course for which companies I can apply for?
Volume of data is increasing doubled in every two years. Most of the MNC's with larger database are working on Spark & Scala companies like Amazon, United Health Group., Mindlance, Dunnhumby, Essex Services, American Express, Adobe and many more are looking for Hadoop & Spark Scala professionals.
   What are pay packages for fresher in Hadoop & Spark Scala?
On an average a fresher gets 7-9 LPA with a skill set of Hadoop and Spark & Scala.
   What is the process for Hadoop and Spark & Scala Training?
We'll be starting with the introduction to Big Data Hadoop, HDFS, Mapreduce, PIG, HIVE, Hbase, Apache Spark and then will be playing with RDD and Spark Streaming & Spark SQL and end to end completion of Scala with Spark.


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