Developer Training for Apache Spark™ and Hadoop

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This 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.
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.

Code Titre Durée Prix HT
HADP01 Developer Training for Apache Spark™ and Hadoop 4 jours Nous consulter


  • 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 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 to query data using Spark SQL, DataFrames, and Datasets
  • How to use Spark Streaming to process a live data stream




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.



50% Pratique 50% Théorique



Introduction to Apache Hadoop and the Hadoop Ecosystem
Apache Hadoop Overview
Data Processing
Introduction to the Hands-On Exercises

Apache Hadoop File Storage

Apache Hadoop Cluster Components
HDFS Architecture
Using HDFS

Distributed Processing on an Apache Hadoop Cluster

YARN Architecture
Working With YARN

Apache Spark Basics

What is Apache Spark?
Starting the Spark Shell
Using the Spark Shell
Getting Started with Datasets and DataFrames
DataFrame Operations

Working with DataFrames and Schemas

Creating DataFrames from Data Sources
Saving DataFrames to Data Sources
DataFrame Schemas
Eager and Lazy Execution

Analyzing Data with DataFrame Queries

Querying DataFrames Using Column Expressions
Grouping and Aggregation Queries
Joining DataFrames

RDD Overview

RDD Overview
RDD Data Sources
Creating and Saving RDDs
RDD Operations

Transforming Data with RDDs

Writing and Passing Transformation Functions
Transformation Execution
Converting Between RDDs and DataFrames

Aggregating Data with Pair RDDs

Key-Value Pair RDDs
Other Pair RDD Operations

Querying Tables and Views with SQL

Querying Tables in Spark Using SQL
Querying Files and Views
The Catalog API

Working with Datasets in Scala

Datasets and DataFrames
Creating Datasets
Loading and Saving Datasets
Dataset Operations

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

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

Distributed Data Persistence

DataFrame and Dataset Persistence
Persistence Storage Levels
Viewing Persisted RDDs

Common Patterns in Spark Data Processing

Common Apache Spark Use Cases
Iterative Algorithms in Apache Spark
Machine Learning
Example: k-means

Introduction to Structured Streaming

Apache Spark Streaming Overview
Creating Streaming DataFrames
Transforming DataFrames
Executing Streaming Queries

Structured Streaming with Apache Kafka

Receiving Kafka Messages
Sending Kafka Messages

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



Hadoop Spark