Apache Spark Essentials is a two-day course that provides students with a quick introduction to the Spark environment, benefits, features and common uses and tools. Working in a hands-on learning environment, students will learn where Spark fits into the Big Data ecosystem, and how to use core Spark features for critical data analysis. The course also explores (at a higher-level) key Spark technologies such as Spark shell for interactive data analysis, Spark internals, RDDs, Dataframes and Spark SQL.
This “skills-centric” course is about 50% hands-on lab and 50% lecture, designed to train attendees in core big data/ Spark development and use skills, coupling the most current, effective techniques with the soundest industry practices. Throughout the course students will be led through a series of progressively advanced topics, where each topic consists of lecture, group discussion, comprehensive hands-on lab exercises, and lab review.
This course provides indoctrination in the practical use of the umbrella of technologies that are on the leading edge of data science development focused on Spark and related tools. Working in a hands-on learning environment, students will explore:
- Spark Basics
- Getting Started with Spark
- RDDs In Depth
- Spark SQL & Dataframes
Need different skills or topics? If your team requires different topics or tools, additional skills or custom approach, this course may be further adjusted to accommodate. We offer additional Spark, big data, data science, Hadoop, AI / machine learning / deep learning, programming, analytics, and other related topics that may be blended with this course for a track that best suits your needs. Our team will collaborate with you to understand your needs and will target the course to focus on your specific learning objectives and goals.
This is an Introductory-level course is geared for experienced Developers and Architects seeking to be proficient in Spark tools & technologies. Attendees should be experienced developers who are comfortable with basic Python programming. Students should also be able to navigate Linux command line and have basic knowledge of Linux editors (such as VI / nano) for editing code.
Take Before: Students should have attended the course(s) below, or should have basic skills in these areas:
- TTPS4802 Python Basic Primer / Quick Start to Python
Please see the Related Courses tab for specific Pre-Requisite courses, Related Courses that offer similar skills or topics, and next-step Learning Path recommendations.
Please note that this list of topics is based on our standard course offering, evolved from typical industry uses and trends. We’ll work with you to tune this course and level of coverage to target the skills you need most.
- Background and history
- Spark and Hadoop
- Spark concepts and architecture
- Spark eco system (core, spark sql, mlib, streaming)
Getting Started with Spark
- Spark in local mode
- Spark web UI
- Spark shell
- Analyzing dataset - part 1
- Inspecting RDDs
RDDs In Depth
- RDD Operations / transformations
- RDD types
- MapReduce on RDD
- Caching and persistence
- Sharing cached RDDs
Spark SQL & Dataframes
- Dataframes DDL
- Spark SQL
- Defining tables and importing datasets
Student Materials: Each participant will receive a Student Guide with course notes, code samples, software tutorials, step-by-step written lab instructions, diagrams and related reference materials and resource links. Students will also receive the project files (or code, if applicable) and solutions required for the hands-on work.
Hands-On Setup Made Simple! Our dedicated tech team will work with you to ensure our ‘easy-access’ cloud-based course environment is accessible, fully-tested and verified as ready to go well in advance of the course start date, ensuring a smooth start to class and effective learning experience for all participants. Please inquire for details and options.