32 Hrs
2119+ Enrollments
CCA Spark and Hadoop Developer
This course covers the core concepts of Spark and Hadoop, including HDFS, MapReduce, Spark RDDs, and Spark SQL. You will learn how to use Spark to build real-time data processing applications and how to use Hadoop to store and process large datasets. This course includes hands-on labs and exercises, allowing you to apply what you learn in a practical setting.
32 Hrs
2119+ Enrollments
CCA Spark and Hadoop Developer
CCA Spark and Hadoop Developer
Overview of Course
The CCA Spark and Hadoop Developer course is designed to teach developers how to build efficient and scalable big data applications using Apache Spark and Hadoop. This course is ideal for individuals who want to learn the fundamentals of Spark and Hadoop, and how to use these technologies to process large datasets.
Course Highlights
Learn the basics of Hadoop and Spark
Understand HDFS and MapReduce concepts
Use Spark RDDs to build efficient data processing applications
Key Differentiators
Personalized Learning with Custom Curriculum
Training curriculum to meet the unique needs of each individual
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Trusted by over 100+ Fortune 500 Companies
We help organizations deliver right outcomes by training talent
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Flexible Schedule & Delivery
Choose between virtual/offline with Weekend options
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World Class Learning Infrastructure
Our learning platform provides leading virtual training labs & instances
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Enterprise Grade Data Protection
Security & privacy are an integral part of our training ethos
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Real-world Projects
We work with experts to curate real business scenarios as training projects
Skills You’ll Learn
#1
Basics of Hadoop and Spark
#2
HDFS and MapReduce concepts
#3
Use Spark RDDs to build efficient data processing applications
#4
Spark SQL to process structured data
#5
Spark Streaming to process real-time data
#6
Hands-on experience with big data tools
Training Options
Corporate Training
On Request
Everything in 1-on-1 Training plus- Custom Curriculum
- Extended access to virtual labs
- Detailed reporting of every candidate
- Projects and assessments
- Consulting Support
- Training aligned to business outcomes
For Corporates
Unlock Organizational Success through Effective Corporate Training: Enhance Employee Skills and Adaptability
- Choose customized training to address specific business challenges and goals, which leads to better outcomes and success.
- Keep employees up-to-date with changing industry trends and advancements.
- Adapt to new technologies & processes and increase efficiency and profitability.
- Improve employee morale, job satisfaction, and retention rates.
- Reduce employee turnovers and associated costs, such as recruitment and onboarding expenses.
- Obtain long-term organizational growth and success.
Course Reviews
Curriculum
- Apache Hadoop and Hadoop Ecosystem
- Overview
- Data Ingestion and Storage
- Data Processing
- Data Analysis and Exploration
- Other Ecosystem Tools
- Introduction to the Hands-On Exercises
- Apache Hadoop Cluster Components
- HDFS Architecture
- Using HDFS
- YARN Architecture
- Working With YARN
- What is Apache Spark?
- Starting the Spark Shell
- Using the Spark Shell
- Getting Started with Datasets and DataFrames
- DataFrame Operations
- Creating DataFrames from Data Sources
- Saving DataFrames to Data Sources
- DataFrame Schemas
- Eager and Lazy Execution
- Querying DataFrames Using Column Expressions
- Grouping and Aggregation Queries
- Joining DataFrames
- RDD Overview
- RDD Data Sources
- Creating and Saving RDDs
- RDD Operations
- Writing and Passing Transformation Functions
- Transformation Execution
- Converting Between RDDs and DataFrames
- Key-Value Pair RDDs
- Map-Reduce
- Other Pair RDD Operations
- Querying Tables in Spark Using SQL
- Querying Files and Views
- The Catalog API
- Comparing Spark SQL, Apache Impala, and Apache Hive-on-Spark
- Datasets and DataFrames
- Creating Datasets
- Loading and Saving Datasets
- Dataset Operations
- Writing a Spark Application
- Building and Running an Application
- Application Deployment Mode
- The Spark Application Web UI
- Configuring Application Properties
- 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
- DataFrame and Dataset Persistence
- Persistence Storage Levels
- Viewing Persisted RDDs
- Common Apache Spark Use Cases
- Iterative Algorithms in Apache Spark
- Machine Learning
- Example: k-means
- Apache Spark Streaming Overview
- Example: Streaming Request Count
- DStreams
- Developing Streaming Applications
- Multi-Batch Operations
- Time Slicing
- State Operations
- Sliding Window Operations
- Preview: Structured Streaming
- Streaming Data Source Overview
- Apache Flume and Apache Kafka Data Sources
- Example: Using a Kafka Direct Data Source
Contact Learning Advisor
Meet the instructor and learn about the course content and teaching style.- Make informed decisions about whether to enroll in the course or not.
- Get a perspective with a glimpse of what the learning process entails.
Description
Target Audience:
- Software Developers
- Big Data Engineers
- Data Analysts
Prerequisite:
- Basic programming skills in Python or Java
- Basic understanding of SQL
Benefits of the course:
- Learn the latest technologies and tools used in big data processing
- Gain hands-on experience with real-world projects and applications
- Enhance your skills and increase your job opportunities in the big data industry
Exam details to pass the course:
- The CCA Spark and Hadoop Developer certification exam is a hands-on, practical exam that tests your knowledge of Spark and Hadoop. The exam consists of a set of tasks that you must complete using Spark and Hadoop.
Certification path
- Cloudera Certified Associate (CCA) Spark and Hadoop Developer Certification
Career options after doing the course:
- Big Data Engineer
- Data Scientist
- Data Analyst
- Hadoop Developer
- Spark Developer
Why should you take this course from Skillzcafe:
Why should you take this course from Skillzcafe:
Hands-on training with real-world projects- Certified trainers with industry experience
- Flexible learning options
- Comprehensive curriculum
- Placement assistance
FAQs
This course covers Python and Java programming languages.
Basic understanding of big data concepts is helpful, but not required.
Yes, the Cloudera Certified Associate (CCA) Spark and Hadoop Developer Certification exam is available for this course.
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