Hadoop and Spark Developer
PRICE: 30,000
Sessions : 24       Hours: 144
Inclusive all of taxes
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.

Upcoming Batches

19/10/19

SAT - SUN (48 DAYS)

Timings - 10:00 AM to 01:00 PM (IST)

23/11/19

SAT - SUN (48 DAYS)

Timings - 02:00 PM to 05:00 PM (IST)

Can’t find a batch you were looking for?

Hadoop and Spark Developer Curriculum

  • 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

  • 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

  • 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

  • Understanding Input Splits
  • MapReduce job submission flow
  • Performance improvement using combiners
  • Partitioners
  • MapReduce as a whole

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

  • 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

  • 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.

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

  • 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
  • Understanding Zookeeper.

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

  • 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

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

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

  • Understand Spark SQL architecture
  • Learn Spark Streaming API

  • 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

  • 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

  • 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

Hadoop and Spark Developer Reviews

The best institute for Data Science training. I had chosen the Hadoop course and the training was excellent.

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Saquib Ahsan

Hi All, Those who are looking for an institute to learn BIG DATA. Let me tell you Palin is the best institute in Gurgaon.After visiting so many institutes I found that it is the best to learn and invest your money and time.If you really want to learn this is the place.

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Deepak Raghav

Thanks for the Training & the Knowledge you delivered to me. This real time training is extremely helpful in my career growth. Best Infrastructure and the Best Team of Professional Trainers. Thanks for your backup Support as well that helped me out to clear my doubts.

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Pawan Kajla

Trainer is highly knowledgable and energetic and keeps participants engaged. Really good for beginners.

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Bharti

Great learning environment. Trainers are industry professionals and have in depth knowledge.

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Rajat Narula

Hadoop and Spark Developer Project

Features

EXPERIENCED TRAINER

Min 8+ years of industry Experience.For end to end implementation in analytics life cycle

HIGHEST PLACEMENT RATE

Training as per industry requirement with mock interviews training

ENDORSED CURRICULUM

Designed by professionals according to industry requirement

FLEXIBLE SCHEDULE

Choose the timimg as per your convenience

REAL TIME CASE STUDIES

For end to end implementation in analytics life cycle

CLASS RECORDINGS

Life time access for recorded sessions

Students Questions and answers

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.

Any Graduate having a programming background and database handling skills can opt Hadoop & Spark developer program to make his career into big data profiles

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

Palin Analytics offers you both the platforms for the training you can opt either online or classroom

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.

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.

Volume of data is increasing doubled in every two years. Most of the MNC 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.

On an average a fresher gets 7-9 LPA with a skill set of Hadoop and Spark & Scala.

We will 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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About Trainer

Tushar

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