Apache Spark Scala online course

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    Apache Spark and Scala Training

    Apache Spark and Scala Online Course with Certification

    Learn Scala and Apache Spark online. The course covers RDDs, Spark Core, Spark SQL, Spark Streaming, Kafka and Spark on Google Cloud Dataproc. Choose live online, classroom or self paced learning. You receive a certificate of completion.

    ★ 4.3 out of 5 rating 15k+ learners trained Certificate on completion
    • Live Interactive Classes
    • Job Assistance
    • Industry Expert Trainers
    • Recorded Classes on LMS
    • Hands On Practicals
    • Online and Classroom Batches

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      Course experience level:


      Course Duration
      [Confirm duration]
      Learning Mode
      Live Online, Classroom and Self Paced
      Projects
      A Practical in Every Module
      Certification
      Certificate of Completion
      Job Support
      Job Assistance
      Batch Timing
      [Confirm batch timings]
      Experience Level
      [Confirm prerequisites]
      Fees Start At
      ₹5,000

      Who Should Take This Apache Spark and Scala Course?

      This course is for:

      Software Engineers

      Upgrade your big data skills and add Scala and Spark to your toolset.

      Data Engineers and ETL Developers

      Process large datasets with Spark Core, Spark SQL and Spark Streaming.

      Data Scientists and Analytics Professionals

      Move your analysis onto a distributed engine that handles large data.

      Graduates

      Start a career in big data and analytics with a structured course.

      Not sure which course is right for you?
      Take our 2 minute course finder to choose between Apache Spark Scala, PySpark, Big Data and Python.
      Find My Course →

      Learn Apache Spark with Scala: What You Will Learn

      Big Data and Spark Basics RDDs Scala Object Oriented Scala Spark Core Spark SQL Spark Streaming Spark on GCP Dataproc
      By the end of the course, you'll be able to:
      Apache Spark and Scala tools
      Scala
      Apache Spark
      Spark SQL
      Spark Streaming
      Hive
      YARN
      Kafka
      GCP Dataproc

      Hands On Spark and Scala Practicals

      Practical 01

      Scala and Spark Setup

      Tools: Scala, Spark shell
      You'll build:
      • Spark and Scala installed on Windows and Ubuntu
      • An IDE set up for Scala
      • Scala code run in the Scala shell
      • A Spark shell with a Spark context
      View Practical →
      Practical 02

      RDD Practicals

      Tools: Scala, Spark RDDs
      You'll build:
      • RDDs loaded with data
      • HadoopRDD, filtered RDD and joined RDD
      • Transformations and actions
      • Shared variables
      View Practical →
      Practical 03

      Streaming Practicals

      Tools: Spark Streaming, Kafka, Flume
      You'll build:
      • Distributed log files processed in real time
      • Transformations and actions on discretized streams
      • Integration with Flume and Kafka
      • Monitoring of streaming jobs
      View Practical →

      Each practical gives you something specific to explain in an interview.

      Spark and Scala Career Roles After This Course

      Course
      Skill Building
      Hands On Practicals
      Real Time Project
      CV Help
      Interview Preparation
      Job Assistance
      Career roles you can target
      Role Core Skills
      Spark Developer Scala, RDDs, Spark Core, Spark SQL
      Big Data Developer Spark, Hive, YARN
      ETL Developer Spark SQL, DataFrames, Parquet and JSON
      Streaming Data Trainee Spark Streaming, Kafka
      Junior Data Engineer Scala, Spark SQL, GCP Dataproc

      Job assistance is described below with what it includes. These roles are examples of where the skills are used. This course does not guarantee a job offer.

      How Prwatech supports your job search

      What job assistance includes, in detail.

      01

      CV Help

      Get help creating a professionally written CV.

      02

      Interview Preparation

      Get guidance for interview preparation and common interview questions.

      03

      Real Time Project

      Work on an industry grade project to see how data teams use Spark.

      04

      Screening Test

      Learners who pass the screening test receive interview calls.

      05

      Job Assistance

      [Describe exactly what else this includes, such as referrals or a job board.]

      92% learners placed since 2010
      Verify against internal placement records and delete this line before the page goes live.
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      Why Learn Apache Spark with Prwatech

      15+ Years
      Training Experience
      15k+
      Learners Trained
      Industry
      Experts Lead Live Q&A
      Recorded
      Classes on Your LMS
      Job
      Assistance Included
      Online +
      Classroom Batches

      Apache Spark Trainers

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      [Trainer Name]

      [Current role]
      [Years of experience]
      Specialization: [Specialization]
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      [Trainer Name]

      [Current role]
      [Years of experience]
      Specialization: [Specialization]

      Meet Your Trainers →

      Student Reviews

      ★ 4.3 average from 299+ verified Google reviews

      Every review is public on Google.

      Read All Reviews on Google →
      Before → After
      Before After
      No Scala knowledge Scala programs with classes, collections and functions
      No Spark experience RDD programming and Spark Core jobs
      SQL on small data only Spark SQL and DataFrames on large data
      No streaming experience Spark Streaming jobs with Kafka

      Apache Spark and Scala Course Syllabus

      1. Introduction to Big Data and Spark
      • Overview of big data and Spark
      • MapReduce limitations
      • Spark history and Spark architecture
      • Spark and Hadoop advantages, and the benefits of using them together
      • Introduction to the Spark ecosystem
      2. Apache Spark Installation and Working with RDDs
      • Installing Apache Spark on a local machine
      • Understanding RDDs and loading data into an RDD
      • Scala RDD, general RDD, paired RDD and double RDD functions
      • Implementing HadoopRDD, filtered RDD and joined RDD
      • Transformations, actions and shared variables
      • Spark operations on YARN and sequence file processing
      • The partitioner and its role in performance improvement
      3. Introduction to Scala
      • Scala foundation and features
      • Setting up Spark and Scala on Windows and Ubuntu
      • Installing IDEs for Scala and running code in the Scala shell
      • Data types and lazy values
      • Control structures, looping structures, functions and procedures
      • Collections, arrays and array buffers
      • Maps, tuples and lists
      4. Object Oriented Programming in Scala
      • Implementing classes, getters and setters
      • Objects and object private fields, and nested classes
      • Auxiliary and primary constructors
      • Companion objects and the apply method
      • Packages, overriding methods, type checking and casting
      • Abstract classes
      5. Spark Core
      • Batch versus real time data processing
      • Introduction to Spark, and Spark compared with Hadoop
      • Coding Spark jobs in Scala
      • The Spark shell and creating a Spark context
      • RDD programming: operations, transformations and actions
      • Loading and saving data
      • Key value pair RDDs and broadcast variables
      6. Spark SQL
      • Introduction to Apache Spark SQL and the SQL context
      • Importing and saving data
      • Processing text, JSON and Parquet files
      • DataFrames and user defined functions
      • Using Hive and a local Hive metastore server
      7. Spark Streaming
      • Introduction to Spark Streaming and its architecture
      • Processing distributed log files in real time
      • Discretized streams
      • Transformations and actions on streaming data
      • Integration with Flume and Kafka
      • Monitoring streaming jobs
      8. Google Cloud and Dataproc
      • Module 8: creating a Compute Engine project, enabling billing, adding team members, Compute Engine resources and how to manage them
      • Module 9: the Hadoop ecosystem, running Hadoop on Cloud Dataproc, Cloud Storage instead of HDFS, optimizing Dataproc

      Apache Spark Training Fees and Learning Formats

      All formats include the same curriculum and projects.

      Swipe sideways to compare all three formats →

      Self Paced Most Popular
      Live Online
      Classroom
      Recorded Content ✓ ✓ ✓
      Live Classes Not included ✓ ✓
      Trainer Support Limited ✓ ✓
      Projects ✓ ✓ ✓
      Career Support [Specify] ✓ ✓
      Access Lifetime [Duration] [Duration]
      Price
      ₹5,000
      or ₹[X,XXX] per month EMI
      ₹[XX,XXX]
      or ₹[X,XXX] per month EMI
      ₹[XX,XXX]
      or ₹[X,XXX] per month EMI

      Talk to an Advisor

      What happens after you enquire?

      1
      Submit enquiry
      2
      Advisor calls you
      3
      Discuss background & goals
      4
      Choose suitable batch
      5
      Complete enrollment
      6
      Start learning

      Frequently Asked Questions

      Who can join this Apache Spark and Scala course?
      Software engineers, data engineers, ETL developers, data scientists, analytics professionals and graduates who want a career in big data can join. The course teaches Scala from the basics, so you do not need earlier Scala experience. If you are unsure about your background, speak with the learning team before you enrol.
      What is the Apache Spark training duration?
      The course runs for [Confirm duration].
      What is the Apache Spark and Scala course fee?
      The self paced course costs ₹5,000. The live online fee is [Confirm online fee] and the classroom fee is the online fee plus ₹500. Contact the learning team for EMI details.
      Do I need to know Hadoop for Hadoop Spark Scala work?
      No. The first module explains Hadoop and the limits of MapReduce before it introduces Spark. You learn how Spark and Hadoop work together, including Spark on YARN.
      Why learn Spark with Scala and not Python?
      Both use the same Spark engine. Spark is written in Scala, so Scala gives direct access to the Spark API. If you prefer Python, see our PySpark course.
      Does the course cover Spark SQL, Spark Streaming and Kafka?
      Yes. Module 6 covers the SQL context, DataFrames, text, JSON and Parquet files, user defined functions and Hive with a local metastore. Module 7 covers discretized streams, processing log files in real time, and integration with Flume and Kafka.
      Does the course cover machine learning with MLlib?
      No. This course covers Spark Core, Spark SQL and Spark Streaming. For machine learning, see our Data Science course.
      Is this an Apache Spark and Scala certification course?
      You receive a Prwatech certificate of completion, and it is included in the course. It is a course certificate and not a vendor or exam certification. Preparation for a Spark certification exam, and exam fees, are not part of this course.
      Do you provide job assistance?
      Learners who pass the screening test receive interview calls. We also help with your CV and with interview preparation. We do not guarantee a job offer.
      What if I miss a live class?
      Every class is recorded and uploaded to your LMS. Earlier class recordings and presentations are also available to you.

      Start Learning Apache Spark

      Get the complete curriculum and speak with a learning advisor about the right learning format for you.

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