Scalable programming with Scala and Spark [Video]

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Scalable programming with Scala and Spark [Video]

Loonycorn

Use Scala and Spark for data analysis, machine learning and analytics

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Video Details

ISBN 139781788997881
Course Length8 hours 59 minutes

Video Description

Get your data to fly using Spark and Scala for analytics, machine learning, and data science. Let’s parse that. What's Spark? If you are an analyst or a data scientist, you're used to having multiple systems for working with data. SQL, Python, R, Java, etc. With Spark, you have a single engine where you can explore and play with large amounts of data, run machine learning algorithms and then use the same system to productionize your code. Scala: Scala is a general-purpose programming language - like Java or C++. Its functional programming nature and the availability of a REPL environment make it particularly suited for a distributed computing framework like Spark.

Analytics: Using Spark and Scala you can analyze and explore your data in an interactive environment with fast feedback. The course will show how to leverage the power of RDDs and Dataframes to manipulate data with ease.

Machine Learning and Data Science: Spark's core functionality and built-in libraries make it easy to implement complex algorithms like Recommendations with very few lines of code. We'll cover a variety of datasets and algorithms including PageRank, MapReduce and Graph datasets.

Style and Approach

The course will cover the installation of Scala - no worries on that front!

Table of Contents

You, This Course and Us
You, This Course and Us
Installing Scala and Hello World
Introduction to Spark
What does Donald Rumsfeld have to do with data analysis?
Why is Spark so cool?
An introduction to RDDs - Resilient Distributed Datasets
Built-in libraries for Spark
Installing Spark
The Spark Shell
See it in Action: Munging Airlines Data with Spark
Transformations and Actions
Resilient Distributed Datasets
RDD Characteristics: Partitions and Immutability
RDD Characteristics: Lineage, RDDs know where they came from
What can you do with RDDs?
Create your first RDD from a file
Average distance travelled by a flight using map () and reduce () operations
Get delayed flights using filter (), cache data using persist ()
Average flight delay in one-step using aggregate ()
Frequency histogram of delays using countByValue ()
Advanced RDDs: Pair Resilient Distributed Datasets
Special Transformations and Actions
Average delay per airport, use reduceByKey(), mapValues() and join()
Average delay per airport in one step using combineByKey()
Get the top airports by delay using sortBy()
Lookup airport descriptions using lookup(), collectAsMap(), broadcast()
Advanced Spark: Accumulators, Spark Submit, MapReduce, Behind the Scenes
Get information from individual processing nodes using accumulators
Long running programs using spark-submit
Spark-Submit with Scala - A demo
Behind the scenes: What happens when a Spark script runs?
Running MapReduce operations
PageRank: Ranking Search Results
What is PageRank?
The PageRank algorithm
Implement PageRank in Spark
Join optimization in PageRank using Custom partitioning
Spark SQL
Data frames: RDDs + Tables
MLlib in Spark: Build a recommendations engine
Collaborative filtering algorithms
Latent Factor Analysis with the Alternating Least Squares method
Music recommendations using the Audioscrobbler dataset
Implement code in Spark using MLlib
Spark Streaming
Introduction to streaming
Implement stream processing in Spark using Dstreams
Stateful transformations using sliding windows
Graph Libraries
The Marvel social network using Graphs
Scala Language Primer
Scala - A "better Java"?
How do Classes work in Scala?
Classes in Scala - continued
Functions are different from Methods
Collections in Scala
Map, Flat map - The Functional way of looping
First Class Functions revisited
Partially Applied Functions
Closures
Currying
Supplementary Installs
Installing Intellij
Installing Anaconda
[For Linux/Mac OS Shell Newbies] Path and other Environment Variables

What You Will Learn

  • Use Spark for a variety of analytics and Machine Learning tasks
  • Understand functional programming constructs in Scala
  • Implement complex algorithms like PageRank or Music Recommendations
  • Work with a variety of datasets from Airline delays to Twitter, Web graphs, Social networks and Product Ratings
  • Use all the different features and libraries of Spark : RDDs, Dataframes, Spark SQL, MLlib, Spark Streaming and GraphX
  • Write code in Scala REPL environments and build Scala applications with an IDE

Authors

Table of Contents

You, This Course and Us
You, This Course and Us
Installing Scala and Hello World
Introduction to Spark
What does Donald Rumsfeld have to do with data analysis?
Why is Spark so cool?
An introduction to RDDs - Resilient Distributed Datasets
Built-in libraries for Spark
Installing Spark
The Spark Shell
See it in Action: Munging Airlines Data with Spark
Transformations and Actions
Resilient Distributed Datasets
RDD Characteristics: Partitions and Immutability
RDD Characteristics: Lineage, RDDs know where they came from
What can you do with RDDs?
Create your first RDD from a file
Average distance travelled by a flight using map () and reduce () operations
Get delayed flights using filter (), cache data using persist ()
Average flight delay in one-step using aggregate ()
Frequency histogram of delays using countByValue ()
Advanced RDDs: Pair Resilient Distributed Datasets
Special Transformations and Actions
Average delay per airport, use reduceByKey(), mapValues() and join()
Average delay per airport in one step using combineByKey()
Get the top airports by delay using sortBy()
Lookup airport descriptions using lookup(), collectAsMap(), broadcast()
Advanced Spark: Accumulators, Spark Submit, MapReduce, Behind the Scenes
Get information from individual processing nodes using accumulators
Long running programs using spark-submit
Spark-Submit with Scala - A demo
Behind the scenes: What happens when a Spark script runs?
Running MapReduce operations
PageRank: Ranking Search Results
What is PageRank?
The PageRank algorithm
Implement PageRank in Spark
Join optimization in PageRank using Custom partitioning
Spark SQL
Data frames: RDDs + Tables
MLlib in Spark: Build a recommendations engine
Collaborative filtering algorithms
Latent Factor Analysis with the Alternating Least Squares method
Music recommendations using the Audioscrobbler dataset
Implement code in Spark using MLlib
Spark Streaming
Introduction to streaming
Implement stream processing in Spark using Dstreams
Stateful transformations using sliding windows
Graph Libraries
The Marvel social network using Graphs
Scala Language Primer
Scala - A "better Java"?
How do Classes work in Scala?
Classes in Scala - continued
Functions are different from Methods
Collections in Scala
Map, Flat map - The Functional way of looping
First Class Functions revisited
Partially Applied Functions
Closures
Currying
Supplementary Installs
Installing Intellij
Installing Anaconda
[For Linux/Mac OS Shell Newbies] Path and other Environment Variables

Video Details

ISBN 139781788997881
Course Length8 hours 59 minutes
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