Cloudera Data Engineering: Developing Applications with Apache Spark

Cloudera Data Engineering: Developing Applications with Apache Spark is an advanced training course designed for data engineers and developers looking to master application development using Apache Spark within the Cloudera Data Platform (CDP). The course provides in-depth training on how to design, build, and optimize big data applications using Spark’s powerful data processing capabilities. Through hands-on labs and real-world examples, participants will learn how to develop efficient data pipelines, process large-scale datasets, and leverage Spark's advanced features like Spark SQL, Spark Streaming, and MLlib. This course is ideal for professionals aiming to build scalable, high-performance data processing applications in a modern big data environment.

Schedule & Fee
Learning Objectives
Prerequisites
Target Audience
Course Modules
FAQs

Schedule	Learners	Course Fee (Incl. of all Taxes)	Register Your Interest
December 22^nd - 25^th 09:00 AM - 05:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours) Guaranteed-to-Run		10% Off $1,600 $1,440 Fast Filling! Hurry Up.
December 27^th - 04^th 09:00 AM - 05:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours)		10% Off $1,600 $1,440
January 05^th - 08^th 09:00 AM - 05:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours)		20% Off $1,600 $1,280
January 10^th - 18^th 09:00 AM - 05:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours)		20% Off $1,600 $1,280
January 12^th - 15^th 09:00 AM - 05:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours)		20% Off $1,600 $1,280
January 19^th - 28^th 06:00 AM - 10:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours)		20% Off $1,600 $1,280
January 26^th - 29^th 09:00 AM - 05:00 PM (CST) Live Virtual Classroom (Duration : 32 Hours) Guaranteed-to-Run		20% Off $1,600 $1,280

Course Prerequisites

Basic knowledge of Apache Spark and Hadoop
Familiarity with distributed computing and big data concepts
Experience in programming languages such as Java, Scala, or Python
Understanding of data processing principles and data pipelines
Familiarity with Cloudera Data Platform (CDP) is recommended but not required

Learning Objectives

By the end of this course, participants will be able to:

Design and develop scalable data pipelines with Apache Spark
Work with Spark SQL to process and query structured data efficiently
Implement real-time data processing applications with Spark Streaming
Utilize MLlib for machine learning and data analytics within Spark applications
Optimize Spark jobs for performance and resource management
Integrate Apache Kafka and other big data technologies with Spark applications
Deploy and manage Spark jobs on Cloudera Data Platform (CDP)
Implement data governance, security, and compliance best practices in Spark applications

Target Audience

This course is ideal for professionals involved in the development and management of big data applications. The target audience includes:

Data Engineers
Big Data Developers
Data Scientists and Analysts working with large-scale data
IT professionals managing Spark applications on Cloudera
Developers looking to deepen their knowledge of Spark and big data technologies
Technical leads overseeing big data projects

Course Modules

Introduction to Apache Spark on Cloudera
- Overview of Apache Spark and its ecosystem
- Setting up and configuring Apache Spark in Cloudera Data Platform (CDP)
- Key components of Spark: RDDs, DataFrames, Datasets, and Spark SQL
Developing Data Pipelines with Apache Spark
- Building scalable data pipelines with Spark
- Best practices for transforming, cleaning, and processing large datasets
- Using Spark SQL for querying structured data and creating data transformations
Advanced Data Processing with Spark
- Working with Spark Streaming for real-time data processing
- Using Spark MLlib for machine learning and data analytics
- Implementing batch and stream processing pipelines for various big data use cases
Optimizing Spark Applications for Performance
- Techniques for optimizing Spark performance in big data environments
- Best practices for Spark job configurations and memory management
- Understanding Spark execution plans and improving data processing efficiency
Integrating Spark with Other Big Data Technologies
- Integrating Apache Kafka for real-time data streaming in Spark
- Using Apache HBase, Hive, and Parquet for efficient data storage and querying
- Leveraging Apache NiFi for data ingestion and flow management
Handling Complex Data Types and Transformations in Spark
- Working with complex data structures like nested JSON and XML
- Transforming data efficiently using Spark DataFrames and Spark SQL
- Managing large-scale datasets and optimizing joins and aggregations
Managing Spark Jobs in Cloudera
- Deploying and managing Spark applications with Cloudera Manager
- Using YARN and Kubernetes for resource management in Spark clusters
- Monitoring Spark jobs and troubleshooting common issues in Spark applications
Real-Time Data Processing with Spark Streaming
- Implementing real-time data processing pipelines with Spark Streaming
- Using Kafka and Spark Streaming for event-driven data workflows
- Managing stateful and stateless operations in Spark Streaming
Data Governance and Security in Spark Applications
- Implementing data governance policies with Apache Atlas and Cloudera Navigator
- Ensuring security and compliance in Spark applications
- Managing access control, authentication, and encryption in Spark jobs

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What Our Learners Are Saying

The training, courseware, and lab experience were insightful and valuable. Keep up the great work and learning experience!

Nitish A. Anand – Accenture

Course: SC-200: Microsoft Security Operations Analyst
Date: 15th Jan 2025

The instructor was professional and very content.

Justine Daudi Mlimbilah – Bank of Africa, Tanzania

Course: MD-102: Microsoft 365 Endpoint Administrator
Date: 20th Dec 2024

The instructor was so knowledgeable & humble. Rare to find someone so confident but so down to earth these days. So appreciative to him.”

Mohd. Hassan – Ministry of Finance, UAE

Course: AZ-700: Designing and Implementing Microsoft Azure Networking Solutions
Date: 31st July 2024

Instructor is experienced and knowledgeable in guiding.

Dharshini Mahalaxmi – Dr. MGR Education and Research Institute, Chennai, India

Course: SC-300: Microsoft Identity and Access Administrator
Date: 4th May 2024