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Course Details

  • Course Overview
  • Skills Gained
  • Who can Benefit?
  • Prerequisites
  • Syllabus

Cloudera University’s three-day Spark course enables participants to build complete, unified big data applications combining batch, streaming, and interactive analytics on all their data. With Spark, developers can write sophisticated parallel applications for faster business decisions and better user outcomes, applied to a wide variety of use cases, architectures, and industries. This course is part of the developer learning path.Take Your Knowledge to the Next Level and Solve Real-World Problems with Training for Hadoop and the Enterprise Data Hub Cloudera University’s three-day training course for Apache Spark enables participants to build complete, unified big data applications combining batch, streaming, and interactive analytics on all their data. With Spark, developers can write sophisticated parallel applications to execute faster decisions, better decisions, and real-time actions, applied to a wide variety of use cases, architectures, and industries.

Through instructor-led discussion and interactive, hands-on exercises, participants will navigate the Hadoop ecosystem, learning topics such as:

  • Using the Spark shell for interactive data analysis
  • The features of Spark’s Resilient Distributed Datasets
  • How Spark runs on a cluster
  • How Spark parallelizes task execution
  • Writing Spark applications
  • Processing streaming data with Spark

This course is best suited to developers and engineers with prior knowledge and experience with Hadoop.

Course examples and exercises are presented in Python and Scala, so knowledge of one of these programming languages is required. Basic knowledge of Linux is assumed.

Advance Your Ecosystem Expertise

Apache Spark is the next-generation successor to MapReduce. Spark is a powerful, opensource processing engine for data in the Hadoop cluster, optimized for speed, ease of use, and sophisticated analytics. The Spark framework supports streaming data processing and complex, iterative algorithms, enabling applications to run up to 100x aster than traditional Hadoop MapReduce programs.

Introduction to Spark

  • What is Spark?
  • Review: From Hadoop MapReduce to Spark
  • Review: HDFS
  • Review: YARN
  • Spark Overview

Spark Basics

  • Using the Spark Shell
  • RDDs (Resilient Distributed Datasets)
  • Functional Programming in Spark

Working with RDDs in Spark

  • Creating RDDs
  • Other General RDD Operations

Aggregating Data with Pair RDDs

  • Key-Value Pair RDDs
  • Map-Reduce
  • Other Pair RDD Operations

Writing and Deploying Spark Applications

  • Spark Applications vs. Spark Shell
  • Creating the SparkContext
  • Building a Spark Application (Scala and Java)
  • Running a Spark Application
  • The Spark Application Web UI
  • Hands-On Exercise: Write and Run
  • Spark Application
  • Configuring Spark Properties
  • Logging

Parallel Processing

  • Review: Spark on a Cluster
  • RDD Partitions
  • Partitioning of File-based RDDs
  • HDFS and Data Locality
  • Executing Parallel Operations
  • Stages and Tasks

Spark RDD Persistence

  • RDD Lineage
  • RDD Persistence Overview
  • Distributed Persistence

Basic Spark Streaming 

  • Spark Streaming Overview
  • Example: Streaming Request Count

DStreams

  • Developing Spark Streaming Applications
  • Advanced Spark Streaming
  • Multi-Batch Operations
  • State Operations
  • Sliding Window Operations
  • Advanced Data Sources

Common Patterns in Spark Data Processing

  • Common Spark Use Cases
  • Iterative Algorithms in Spark
  • Graph Processing and Analysis
  • Machine Learning
  • Example: k-mean

Improving Spark Performance

  • Shared Variables: Broadcast Variables
  • Shared Variables: Accumulators
  • Common Performance Issues
  • Diagnosing Performance Problems
  • Spark SQL and DataFrames
  • Spark SQL and the SQL Context

Creating DataFrames

  • Transforming and Querying DataFrames
  • Saving DataFrames
  • DataFrames and RDDs
  • Comparing Spark SQL, Impala and Hive-on-Spark
  • Conclusion

 

Audience

  • Developer
  • Engineer

Public Program Schedule

Course Name Duration Brochure Location Schedule Enroll
There is no upcoming Public Batch Schedule, you can ask for Private Batch or for On-Demand Learning

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FAQ

  • Why should I choose RPS?
  • I am working, is it possible to arrange the classes on weekends?
  • Please confirm if your office is open on weekends?
  • Can I get the courseware in advance before start of training?
  • What are the timings (class hours)?
  • How can I make the payment?
  • What is the mode of payment?
  • Candidate authorized RPS to charge $200. But the bank has charged $208. Why is this?
  • If we need training on one of the modules only how does that work?
  • How long before do we need to book the exams?
  • Where are your training centers available?
  • Can I pay the fee in installments?
  • What are the refund policies? Can i get my money back in case i am unable to attend the training?
  • Do you provide a bank loan facility?
  • 10+ years of Training Expertise
  • Certified instructors with industry standard experience
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  • 100000 + professional trained
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Yes, we do offer weekend classes for professionals in group or 1-to-1 Training depending upon the technology.

The administrative and sales staff works on weekdays (Monday - Friday). System Admins and Operation team are available on all days.

Yes, after you have paid the booking amount (which will be non–refundable in this case). Booking amount depends on the technology selected.

Training timings are from 9 am to 5 pm.

You can send the deposit by any of the following methods:-

  • PayPal
  • Credit Card
  • Bank Transfer
  • Demand Draft
  • Cash
  • Purchase Order (in case of Corporates / Government).
  • If you are an International student, the registration amount of USD 200 can be paid by Bank Transfer or PayPal/PayUMoney . The balance amount has to be paid by traveler's cheque or cash after arrival in India. You can also pay the balance by PayPal. There is a surcharge of 4% in this case.
  • For Indian Resident students, the course fees including registration can be paid by Cash, Cheque, Demand Draft or Bank transfer.To Know more Please call +919883305050 or Email us at info@rpsconsulting.in for any of your queries.

Overseas credit card payments through PayPal involve a mark-up of up to 4% as surcharge.

We can provide customized 1-to-1 training for a technology as per your requirement.

Most exams can be booked once you are on the course (e.g. Microsoft, ITIL, VEEAM, EC-Council). Red Hat and some other exams have to be booked in advance.

Our training centers are available in Bangalore, Chennai, Hyderabad, Pune and Delhi.

We do not have facility to pay in installments

If the course fee has been paid for and RPS cancels the Course, a refund will be provided, else the courses are non-refundable.

We do not provide loan facility.

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