Preparing with Cloudera Data Engineering

This four-day hands-on training course delivers the key concepts and expertise developers need to use Apache Spark to develop high-performance parallel applications.

Participants will learn how to use Spark SQL to query structured data and Spark Streaming to perform real-time processing on streaming data from a variety of sources. Developers will also practice writing applications that use core Spark to perform ETL processing and iterative algorithms.

    Note: Scala and Python developers will learn key concepts and gain the expertise needed to ingest and process data, and develop high-performance applications using Apache Spark 2.

    1:1 Coaching

    24*7 Support

    Cloud Labs

    High Success Rate

    Globally Renowned Trainer

    Real-time code analysis and feedback

    Course Description

    The course covers how to work with “big data” stored in a distributed file system, and execute Spark applications on a Hadoop cluster. After taking this course, participants will be prepared to face real-world challenges and build applications to execute faster decisions, better decisions, and interactive analysis, applied to a wide variety of use cases, architectures, and industries.

    Learning Objectives

    • How to write, configure, and deploy Apache Spark applications on a Hadoop cluster
    • How to use the Spark shell and Spark applications to explore, process, and analyze distributed data
    • How the Apache Hadoop ecosystem fits in with the data processing lifecycle
    • How data is distributed, stored, and processed in a Hadoop cluster
    • How to query data using Spark SQL, DataFrames, and Datasets
    • How to use Spark Streaming to process a live data stream

    Enroll your course from
    13th – 16th Feb, 2024
    09:30AM – 05:30PM
    Ajit Kumar Amit
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    6th – 9th May, 2024
    09:30AM – 05:30PM
    Ajit Kumar Amit
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    Enroll your course from
    26th – 29th Aug, 2024
    09:30AM – 05:30PM
    Ajit Kumar Amit
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    Enroll your course from
    11th – 14th Nov, 2024
    09:30AM – 05:30PM
    Ajit Kumar Amit
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    Certification Curriculum

    Introduction to Apache Hadoop and the Hadoop Ecosystem
    • Apache Hadoop Overview
    • Data Processing
    • Introduction to the Hands-On Exercises
    Module 1
    Apache Hadoop File Storage
    • Apache Hadoop Cluster Components
    • HDFS Architecture
    • Using HDFS
    Module 2
    Distributed Processing on an Apache Hadoop Cluster
    • YARN Architecture
    • Working With YARN
    Module 3
    Apache Spark Basics
    • What is Apache Spark?
    • Starting the Spark Shell
    • Using the Spark Shell
    • Getting Started with Datasets and DataFrames
    • DataFrame Operations
    Module 4
    Working with DataFrames and Schemas
    • Creating DataFrames from Data Sources
    • Saving DataFrames to Data Sources
    • DataFrame Schemas
    • Eager and Lazy Execution
    Module 5
    Analyzing Data with DataFrame Queries
    • Querying DataFrames Using Column Expressions
    • Grouping and Aggregation Queries
    • Joining DataFrames
    Module 6
    RDD Overview
    • RDD Overview
    • RDD Data Sources
    • Creating and Saving RDDs
    • RDD Operations
    Module 7
    Transforming Data with RDDs
    • Writing and Passing Transformation Functions
    • Transformation Execution
    • Converting Between RDDs and DataFrames
    Module 8
    Aggregating Data with Pair RDDs
    • Key-Value Pair RDDs
    • Map-Reduce
    • Other Pair RDD Operations
    Module 9
    Querying Tables and Views with SQL
    • Querying Tables in Spark Using SQL
    • Querying Files and Views
    • The Catalog API
    Module 10
    Working with Datasets in Scala
    • Datasets and DataFrames
    • Creating Datasets
    • Loading and Saving Datasets
    • Dataset Operations
    Module 11
    Writing, Configuring, and Running Spark Applications
    • Writing a Spark Application
    • Building and Running an Application
    • Application Deployment Mode
    • The Spark Application Web UI
    • Configuring Application Properties
    Module 12
    Spark Distributed Processing
    • Review: Apache Spark on a Cluster
    • RDD Partitions
    • Example: Partitioning in Queries
    • Stages and Tasks
    • Job Execution Planning
    • Example: Catalyst Execution Plan
    • Example: RDD Execution Plan
    Module 13
    Distributed Data Persistence
    • DataFrame and Dataset Persistence
    • Persistence Storage Levels
    • Viewing Persisted RDDs
    Module 14
    Common Patterns in Spark Data Processing
    • Common Apache Spark Use Cases
    • Iterative Algorithms in Apache Spark
    • Machine Learning
    • Example: k-means
    Module 15
    Introduction to Structured Streaming
    • Apache Spark Streaming Overview
    • Creating Streaming DataFrames
    • Transforming DataFrames
    • Executing Streaming Queries
    Module 16
    Structured Streaming with Apache Kafka
    • Overview
    • Receiving Kafka Messages
    • Sending Kafka Messages
    Module 17
    Aggregating and Joining Streaming DataFrames
    • Streaming Aggregation
    • Joining Streaming DataFrames
    Message Processing with Apache Kafka
    • What Is Apache Kafka?
    • Apache Kafka Overview
    • Scaling Apache Kafka
    • Apache Kafka Cluster Architecture
    • Apache Kafka Command Line Tools


    This course is designed for developers and engineers who have programming experience, but prior knowledge of Spark and Hadoop is not required. Apache Spark examples and hands-on exercises are presented in Scala and Python. The ability to program in one of those languages is required. Basic familiarity with the Linux command line is assumed. Basic knowledge of SQL is helpful.

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    Join Cloudera Developer Training for Apache Spark and Hadoop and gain the knowledge and skills needed to start a career as Cloudera Developer Training for Apache Spark and Hadoop. A Path to In-Demand Jobs.

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    Certification Assessment

    When you complete all of the courses in the program, you’ll earn a Certificate to share with your professional network as well as unlock access to career support resources to help you kickstart your new career. Many Professional Certificates have hiring partners that recognize the Professional Certificate credential and others can help prepare you for a certification exam. You can find more information on individual Professional Certificate pages where it applies.

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    • Join Our Dynamic Community
    • Training from Recognized Trainer
    • Post-workshop support by the Coaches


    Our clients praise us for our great results, personable service, expert knowledge, and on-time delivery. Here are what just a few of them had to say:

    Training FAQ's

    Is this training conducted as an online/ virtual course?

    As a response to the COVID-19, we have moved our classes online. Our Live Virtual format delivers the same benefits as our face-to-face training: expert instruction, hands-on labs and exercises, peer-to-peer collaboration, and high-quality instructional material.

    If I cancel the enrollment, will I get a refund?

    Cancellation requests received within 24 hours of registration would be offered a full refund (minus payment gateway charges), please reach out to our support team through drop a refund request to Visit our page for more details about Cancellation & Refund Policy.

    What Payment Options Are Available?

    The process of enrolling for this classroom training is simple. The payment can be made through different options by using a debit/credit card which includes MasterCard, Visa Card, American Express or through PayPal. Acknowledgment will be issued automatically via email to the candidates once payment is done.

    What are the modes of payment available for payment of accreditation fees?

    Payment can be made via credit card, debit card, UPI, and internet banking.

    Have more doubts?

    Please send in an email to, and we will answer any queries you may have!

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