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Learn By Example: Apache Storm
This online training program has twenty-five examples solved in developing Storm Apps.
Self-Paced
Learning Style
Course
Learning Style
Intermediate
Difficulty
4 Hours
Course Duration
Course Info
Certificate
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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
Audience:
· 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
Prerequisite:
· You can install a Java IDE, such as IntelliJ Idea
· Java programming expertise and familiarity with the use of Java frameworks
Career & Salary Insight
Outline
More Information
Subjects | Big Data |
---|---|
Lab Access | No |
Learning Style | Self-Paced Learning |
Learning Type | Course |
Difficulty | Intermediate |
Course Duration | 4 Hours |
Language | English |
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Tom Robertson
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Tom is an innovator first, and then a Data Scientist & Software Architect. He has integrated expertise in business, product, technology and management. Tom has been involved in creating category defining new products in AI and big data for different industries, which generated more than hundred million revenue cumulatively, and served more than 10 million users.
As a Data Scientist and Software Architect Tom has extensive experience in data science, engineering, architecture and software development. To date Tom has accumulated over a decade of experience in R, Python & Linux Shell programming.
Tom has expertise on Python, SQL, and Spark. He has worked on several libraries including but not limited to Scikit-learn, Pandas, NumPy, Matplotlib, Seaborn, SciPy, NLTK, Keras, and Tensorflow.
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Really interesting trainninginteresting
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