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- Reduce initial time to productivity.
- Increase employee tenure.
- Plug-and-play into HR onboarding and career pathing programs.
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Upskill
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- Upgrade and round out developer skills.
- Tailor to tech stack and specific project.
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Course Summary
The Introduction to Apache Spark training course is designed to demonstrate the necessary skills to work with Apache Spark, an open-source engine for data in the Hadoop ecosystem optimized for speed and advanced analytics.
The course begins by examining how to use Spark as an alternative to traditional MapReduce processing. Next, it explores how Spark supports streamed data processing and iterative algorithms. The course concludes with a lesson on how Spark enables jobs to run faster than traditional Hadoop MapReduce.
- Apache Spark - Hadoop - Apache
- Productivity Objectives:
- Describe how Apache Spark and Hadoop fit together
- List three motivations for using Spark
- Understand Resilient Distributed Datasets (RDDs)
- Implement an application using the key Spark concepts
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about our training
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Real-World Content
Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
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Expert Practitioners
Industry experts with 15+ years of industry experience that bring their battle scars into the classroom.
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Experiential Learning
More coding than lecture, coupled with architectural and design discussions.
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Fully Customized
One-size-fits-all doesn't apply to training teams. That's where we come in!
What You'll Learn
In the Introduction to Apache Spark training course, you'll learn:
- Spark Basics
- What is Apache Spark?
- Using the Spark Shell
- Resilient Distributed Datasets (RDDs)
- Functional Programming with Spark
- The Hadoop Distributed File (HDFS) System
- Why HDFS?
- HDFS Architecture
- Using HDFS
- Spark and Hadoop
- Spark and the Hadoop Ecosystem
- Spark and MapReduce
- RDDs
- RDD Operations
- KeyValue Pair RDDs
- MapReduce and Pair RDD Operations
- Running Spark on a Cluster
- Standalone Cluster
- The Spark Standalone Web UI
- Parallel Programming with Spark
- RDD Partitions and HDFS Data Locality
- Working With Partitions
- Executing Parallel Operations
- Caching and Persistence
- Distributed Persistence
- Caches
- Writing Spark Applications
- SparkContext
- Spark Properties
- Building and Running a Spark Application
- Logging
- Spark Streaming
- Streaming Overview
- Sliding Window Operations
- Spark Streaming Applications
Real-world content
Project-focused demos and labs using your tool stack and environment, not some canned "training room" lab.
Expert Practitioners
Industry experts that bring their battle scars into the classroom.
Experiential Learning
More coding than lecture, coupled with architectural and design discussions.
Fully Customized
One-size-fits-all doesn't apply to training teams. That's where we come in!

Elite Instructor Program
We recently launched our internal Elite Instructor Program. The community driven instructor program is designed to support instructors in transforming students’ lives by consistently showing a world-class level of engagement, ability, and teaching prowess. Reach out today to learn more about our instructors.
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