Learn By Example: Apache Storm

This online training program has twenty-five examples solved in developing Storm Apps.


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4 Hours

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This online training program has twenty-five examples solved in developing Storm Apps.

Course Information

About the course:

Storm is to process what Hadoop is to perform batch processing in real-time. Utilizing Storm, you can build apps that allow you to be highly sensitive to the new data and respond in secs and mins, like detecting the latest trend trends on twitter or tracking spikes in payment gateway failure. Storm can do it all, from basic data transformations to the deployment of machine learning algorithms on the fly.

This online training program has twenty-five examples solved in developing Storm Apps.

Course Objective:

· Running a topology for Storms in remote mode and local mode

· Manage reliability and tolerance of faults inside Bolts and Spouts

· Comprehension Bolts and Spouts that are the building blocks of any topology of Storm.

· Parallelization of data processing within a topology utilizing various grouping techniques: grouping of shuffles, a grouping of lines, custom grouping, a grouping of all, direct grouping

· Using libraries like Storm-R and Trident-ML, to apply ML algorithms on the fly

· Executing complex transformations on the fly utilizing the topology of Trident: window, filter, map, and partition operations


· People who are familiar with Batch processing techniques such as Hadoop want to know more about Stream processing

· Engineers who are currently looking to configure end-to-end data processing pipelines that adapt to real-time changes


· You can install a Java IDE, such as IntelliJ Idea

· Java programming expertise and familiarity with the use of Java frameworks


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SubjectsBig Data
Lab AccessNo
Learning StyleSelf-Paced Learning
Learning TypeCourse
Course Duration4 Hours
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