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Course Description
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
Certification Curriculum
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
- Map-Reduce
- 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
- Overview
- 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
Prerequisites
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.
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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Training FAQ's
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.
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 enquiry@agilitics.sg. Visit our page for more details about Cancellation & Refund Policy.
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