Streaming Big Data with Spark Streaming and Scala - Hands On (Udemy.com)

Spark Streaming tutorial covering Spark Structured Streaming, Kafka integration, and streaming big data in real-time.

Created by: Sundog Education by Frank Kane

Produced in 2021

icon
What you will learn

  • Process massive streams of real-time data using Spark Streaming
  • Integrate Spark Streaming with data sources, including Kafka, Flume, and Kinesis
  • Use Spark 2's Structured Streaming API
  • Create Spark applications using the Scala programming language
  • Output transformed real-time data to Cassandra or file systems
  • Integrate Spark Streaming with Spark SQL to query streaming data in real time
  • Train machine learning models with streaming data, and use those models for real-time predictions
  • Ingest Apache access log data and transform streams of it
  • Receive real-time streams of Twitter feeds
  • Maintain stateful data across a continuous stream of input data
  • Query streaming data across sliding windows of time

icon
Quality Score

Content Quality
/
Video Quality
/
Qualified Instructor
/
Course Pace
/
Course Depth & Coverage
/

Overall Score : 90 / 100

icon
Course Description

New!
Updated for Spark 3.
0.
0!"Big Data" analysis is a hot and highly valuable skill. Thing is, "big data"never stops flowing! Spark Streaming is a new and quickly developing technology for processing massive data sets as they are created - why wait for some nightly analysis to run when you can constantly update your analysis in real time, all the time? Whether it's clickstream data from a big website, sensor data from a massive "Internet of Things" deployment, financial data, or something else - Spark Streaming is a powerful technology for transforming and analyzingthat data right when it is created, all the time.
You'll be learning from an ex-engineer and senior manager from Amazon and IMDb.
This course gets your hands on to some real live Twitter data, simulated streams of Apache access logs, and even data used to train machine learning models! You'll write and run real Spark Streaming jobs right at home on your own PC, and toward the end of the course, we'll show you how to take those jobs to a real Hadoop cluster and run them in a production environment too.
Across over 30 lectures and almost 6 hours of video content, you'll:
Get a crash course in the Scala programming languageLearn how ApacheSpark operates on a clusterSet up discretized streams withSpark Streaming and transform them as data is receivedUse structured streaming to stream into dataframes in real-timeAnalyze streaming data over sliding windows of timeMaintain stateful information across streams of dataConnectSparkStreaming with highly scalable sources of data, including Kafka, Flume, and KinesisDump streams of data in real-time to NoSQL databases such as CassandraRun SQL queries on streamed data in real timeTrain machine learning models in real time with streaming data, and use them to make predictions that keep getting better over timePackage,deploy, and run self-contained Spark Streaming code to a real Hadoop cluser using Amazon ElasticMapReduce.
This course is very hands-on, filled with achievableactivities and exercises to reinforce your learning. By the end of this course, you'll be confidently creating Spark Streaming scripts in Scala, and be prepared to tackle massive streams of data in a whole new way. You'll be surprised at how easy Spark Streaming makes it!
Who this course is for:
Students with some prior programming or scripting ability SHOULD take this course.
If you're working for a company with "big data" that is being generated continuously, or hope to work for one, this course is for you.
Students with no prior software engineering or programming experience should seek an introductory programming course first.

icon
Instructor Details

Sundog Education by Frank Kane

Sundog Education's mission is to make highly valuable career skills in big data, data science, and machine learning accessible to everyone in the world. Our consortium of expert instructors shares our knowledge in these emerging fields with you, at prices anyone can afford.
Sundog Education is led by Frank Kane and owned by Frank's company, Sundog Software LLC.Frank spent 9 years at Amazon and IMDb, developing and managing the technology that automatically delivers product and movie recommendations to hundreds of millions of customers, all the time. Frank holds 17 issued patents in the fields of distributed computing, data mining, and machine learning. In 2012, Frank left to start his own successful company, Sundog Software, which focuses on virtual reality environment technology, and teaching others about big data analysis.
Due to our volume of students we are unable to respond to private messages; please post your questions within the Q&A of your course. Thanks for understanding.

icon
Reviews

4.5

310 total reviews

5 star 4 star 3 star 2 star 1 star
% Complete
% Complete
% Complete
% Complete
% Complete

By Shiv Ranjan Kumar on 10/18/2020

It was excellent

By Jose Luis Saez Martinez on 10/4/2020

El curso ha sido muy provechoso. Los ejemplos que se usan hace que sea muy fcil de seguir y comprender. He echado de menos los subttulos en espaol ya que solo estn en ingls e italiano. Sera una mejora a realizar. Pero por lo dems, me ha parecido interesante.

By Raquel Ventas Olmedo on 9/27/2020

Frank es un gran formador. Con este curso consigues la base para entender cmo funciona spark streaming. Totalmente recomendable.

By Maumribeiro M. Ribeiro on 9/25/2020

Very good lectures, with a professional approach and a motivated instructor. I would recommend it

By Andres Tolosa on 9/15/2020

Muy claro el curso. Y muy prctico.
Recomendable 100%

By Mihail Gorokhovsky on 9/1/2020

Useful, but over simplified sometimes.

By G S on 8/27/2020

Was well explained ! and nice tutorials

By Asheesh Mathur on 8/15/2020

As usual Excellent. Frank is great..seasoned.

By Felipe Oliveira Gutierrez on 8/15/2020

It is a good course on average. He explains how to implement code in Spark very well. Sometimes he explains the details of what is happening under the hood, but I missed a deeper dive into some lectures. He also say that in some lecture it is better "sit and watch" what he is doing. This is the point where I had to evaluate as an "average/good" course. My wounder was, if he has a lecture about some subject why not show it in full manner?

By Myeongwon Kim on 8/7/2020

Great stuff!

By Usman a Khan on 8/5/2020

It's a good course even for beginners for real time analytics and spark streaming

By Alfonso R. on 7/17/2020

Great course, excellent teacher!!!