DEV 362 - Create Data Pipelines Using Apache Spark (Spark v1.6)

DEV 362 - Create Data Pipelines Using Apache Spark (Spark v1.6)

About this Course

DEV 362 describes the benefits of the Apache Spark v1.6 unified platform and how to build data pipeline application using Spark streaming, Spark SQLSpark GraphX and MLlib. The concepts are taught using scenarios in Scala that also form the basis of hands-on labs.

What's Covered

Course Lessons Lab Activities

7: Introduction to Apache Spark Data Pipelines

Identify Spark Unified Stack Components
List Benefits of Apache Spark Unified Stack Over Hadoop Ecosystem
Describe Spark Data Pipeline Use Cases

 

No labs

8: Create an Apache Spark Streaming Application

Describe Spark Streaming Architecture
Create DStreams and a Spark Streaming Application
Apply Operations on DStreams
Define Windowed Operations
Describe How Streaming Applications are Fault-Tolerant

 

Create a Spark Streaming Application

9: Use Apache Spark GraphX to Analyze Flight Data

Describe GraphX
Define Regular, Directed, and Property Graphs
Create a Property Graph
Perform Operations on Graphs

 

Use Apache Spark GraphX

10: Use Apache Spark MLlib

Describe Apache Spark MLlib
Describe the Machine Learning Techniques
Use Collaborative Filtering to Predict User Choice

 

Use Apache Spark MLlib to Make Recommendations

Get Certified

This course is part of the preparation for the MapR Certified Spark Developer (MCSD) certification exam.

Prerequisites

  • Completion of ESS 100 - 102, and ESS 360
  • Basic Hadoop knowledge and intermediate Linux knowledge
  • Experience using a text editor such as vi
  • Terminal program installed; familiarity with command-line options such as mv, cp, ssh, grep, cd, and useradd
  • Knowledge of functional programming with Scala or Python, and experience with SQL

Curriculum

  • Lesson 7 - Introduction to Apache Spark Data Pipelines
  • Quiz 7
  • Lesson 8 - Create Data Pipelines With Apache Spark
  • Quiz 8
  • Lesson 9 - Use Apache Spark GraphX
  • Quiz 9
  • Lesson 10 - Use Apache Spark MLlib
  • Quiz 10
  • Course Materials
  • Slide Guide (Transcript)
  • Lab Guide

About this Course

DEV 362 describes the benefits of the Apache Spark v1.6 unified platform and how to build data pipeline application using Spark streaming, Spark SQLSpark GraphX and MLlib. The concepts are taught using scenarios in Scala that also form the basis of hands-on labs.

What's Covered

Course Lessons Lab Activities

7: Introduction to Apache Spark Data Pipelines

Identify Spark Unified Stack Components
List Benefits of Apache Spark Unified Stack Over Hadoop Ecosystem
Describe Spark Data Pipeline Use Cases

 

No labs

8: Create an Apache Spark Streaming Application

Describe Spark Streaming Architecture
Create DStreams and a Spark Streaming Application
Apply Operations on DStreams
Define Windowed Operations
Describe How Streaming Applications are Fault-Tolerant

 

Create a Spark Streaming Application

9: Use Apache Spark GraphX to Analyze Flight Data

Describe GraphX
Define Regular, Directed, and Property Graphs
Create a Property Graph
Perform Operations on Graphs

 

Use Apache Spark GraphX

10: Use Apache Spark MLlib

Describe Apache Spark MLlib
Describe the Machine Learning Techniques
Use Collaborative Filtering to Predict User Choice

 

Use Apache Spark MLlib to Make Recommendations

Get Certified

This course is part of the preparation for the MapR Certified Spark Developer (MCSD) certification exam.

Prerequisites

  • Completion of ESS 100 - 102, and ESS 360
  • Basic Hadoop knowledge and intermediate Linux knowledge
  • Experience using a text editor such as vi
  • Terminal program installed; familiarity with command-line options such as mv, cp, ssh, grep, cd, and useradd
  • Knowledge of functional programming with Scala or Python, and experience with SQL

Curriculum

  • Lesson 7 - Introduction to Apache Spark Data Pipelines
  • Quiz 7
  • Lesson 8 - Create Data Pipelines With Apache Spark
  • Quiz 8
  • Lesson 9 - Use Apache Spark GraphX
  • Quiz 9
  • Lesson 10 - Use Apache Spark MLlib
  • Quiz 10
  • Course Materials
  • Slide Guide (Transcript)
  • Lab Guide