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Streaming Big Data with Spark Streaming and Scala – Hands On

Spark Streaming tutorial covering Spark Structured Streaming, Kafka integration, and streaming big data in real-time.
4.4
4.4/5
(3,273 reviews)
24,732 students
Created by

9.5

Classbaze Grade®

10.0

Freshness

8.6

Popularity

9.3

Material

Hands-on examples of processing massive streams of data - in real time
Platform: Udemy
Video: 6h 26m
Language: English
Next start: On Demand

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Classbaze Rating

Classbaze Grade®

9.5 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness

10.0 / 10
This course was last updated on 6/2022.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Popularity

8.6 / 10
We analyzed factors such as the rating (4.4/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Material

9.3 / 10
Video Score: 8.5 / 10
The course includes 6h 26m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 6 hours 47 minutes of 113 Apache Spark courses on Udemy.
Detail Score: 9.8 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

2 articles.
0 resource.
0 exercise.
0 test.

In this page

About the course

Now updated to the IntelliJ IDE!
“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 analyzing that 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 language
•Learn how Apache Spark operates on a cluster
•Set up discretized streams with Spark Streaming and transform them as data is received
•Use structured streaming to stream into dataframes in real-time
•Analyze streaming data over sliding windows of time
•Maintain stateful information across streams of data
•Connect Spark Streaming with highly scalable sources of data, including Kafka, Flume, and Kinesis
•Dump streams of data in real-time to NoSQL databases such as Cassandra
•Run SQL queries on streamed data in real time
•Train machine learning models in real time with streaming data, and use them to make predictions that keep getting better over time
•Package, deploy, and run self-contained Spark Streaming code to a real Hadoop cluster using Amazon Elastic MapReduce.
This course is very hands-on, filled with achievable activities 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!

What can you learn from this course?

✓ 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

What you need to start the course?

• To follow along with the examples, you’ll need a personal computer. The course is filmed using Windows 10, but the tools we install are available for Linux and MacOS as well.
• We’ll walk through installing the required software in the first lecture: The Scala IDE, Spark, and a JDK.
• My “Taming Big Data with Apache Spark – Hands On!” would be a helpful introduction to Spark in general, but it is not required for this course. A quick introduction to Spark is included.
• The course includes a crash course in the Scala programming language if you’re new to it; if you already know Scala, then great.

Who is this course is made 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.

Are there coupons or discounts for Streaming Big Data with Spark Streaming and Scala - Hands On ? What is the current price?

The course costs $15.99. And currently there is a 20% discount on the original price of the course, which was $19.99. So you save $4 if you enroll the course now.
The average price is $17.1 of 113 Apache Spark courses. So this course is 6% cheaper than the average Apache Spark course on Udemy.

Will I be refunded if I'm not satisfied with the Streaming Big Data with Spark Streaming and Scala - Hands On course?

YES, Streaming Big Data with Spark Streaming and Scala – Hands On has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any financial aid for this course?

Currently we could not find a scholarship for the Streaming Big Data with Spark Streaming and Scala - Hands On course, but there is a $4 discount from the original price ($19.99). So the current price is just $15.99.

Who will teach this course? Can I trust Sundog Education by Frank Kane?

Sundog Education by Frank Kane has created 34 courses that got 127,324 reviews which are generally positive. Sundog Education by Frank Kane has taught 606,010 students and received a 4.6 average review out of 127,324 reviews. Depending on the information available, we think that Sundog Education by Frank Kane is an instructor that you can trust.
Founder, Sundog Education. Machine Learning Pro
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.
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9.5

Classbaze Grade®

10.0

Freshness

8.6

Popularity

9.3

Material

Platform: Udemy
Video: 6h 26m
Language: English
Next start: On Demand

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