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Machine Learning - Apache Storm - Learn by Example

Video Description

Real-world Solved Examples of Real-time Stream Processing! Storm is to real-time stream processing what Hadoop is to batch processing. From simple data transformations to applying machine learning algorithms on the fly, Storm can do it all.
In this Apache Storm - Learn by Example online course, you will learn how to use Storm to build applications which need you to be highly responsive to the latest data, and react within seconds and minutes, such as finding the latest trending topics on Twitter, or monitoring spikes in payment gateway failures. Learn to build a Storm topology, control parallelism, use Trident to perform transformations, apply Machine Learning algorithms on the fly, and so much more! Supplemental material included.

Table of Contents

  1. INTRODUCTION
    1. You, This Course, and Us! 00:02:06
  2. STREAM PROCESSING WITH STORM
    1. How Does Twitter Compute Trends 00:05:42
    2. Improving Performance Using Distributed Processing 00:05:40
    3. Building Blocks of Storm Topologies 00:05:38
    4. Adding Parallelism in a Storm Topology 00:04:54
    5. Components of a Storm Cluster 00:04:06
  3. IMPLEMENTING A HELLO WORLD TOPOLOGY
    1. A Simple Hello World Topology 00:04:14
    2. Ex 1 - Implementing a Spout 00:11:10
    3. Ex 1 - Implementing a Bolt 00:04:44
    4. Ex 1 - Submitting the Topology 00:05:14
  4. PROCESSING DATA USING FILES
    1. Ex 2 - Reading Data from a File 00:11:39
    2. Representing Data Using Tuples 00:03:25
    3. Ex 3 - Accessing Data from Tuples 00:09:07
    4. Ex 4 - Writing Data to a File 00:09:58
  5. RUNNING A TOPOLOGY IN THE REMOTE MODE
    1. Setting up a Storm Cluster 00:07:23
    2. Ex 5 - Submitting a Topology to the Storm Cluster 00:07:21
  6. ADDING PARALLELISM TO A STORM TOPOLOGY
    1. Ex 6 - Shuffle Grouping 00:06:43
    2. Ex 7 - Fields Grouping 00:04:37
    3. Ex 8 - All Grouping 00:02:22
    4. Ex 9 - Custom Grouping 00:05:16
    5. Ex 10 - Direct Grouping 00:05:39
  7. BUILDING A WORD COUNT TOPOLOGY
    1. Ex 11 - Building a Word Count Topology 00:10:04
  8. REMOTE PROCEDURE CALLS USING STORM
    1. Ex 12 - A Storm Topology for DRPC Calls 00:12:48
  9. MANAGING RELIABILITY OF TOPOLOGIES
    1. Ex 13 - Managing Failures in Spouts 00:10:32
  10. INTEGRATING STORM WITH DIFFERENT SOURCES-SINKS
    1. Ex 14 - Implementing a Twitter Spout 00:08:16
    2. Ex 15 - Using a HDFS Bolt 00:07:17
  11. USING THE STORM MULTILANG PROTOCOL
    1. Ex 16 - Building a Storm Topology Using Python 00:08:25
  12. COMPLEX TRANSFORMATIONS USING TRIDENT
    1. Ex 17 - Building a basic Trident Topology rs Classifier 00:08:05
    2. Ex 18 - Implementing a Map Function 00:07:30
    3. Ex 19 - Implementing a Filter Function 00:03:41
    4. Ex 20 - Aggregating Data Classifiers 00:06:04
    5. Ex 21 - Understanding States 00:09:28
    6. Ex 21 - Understanding States 00:11:34
    7. Ex 23 - Joining Data Streams 00:07:49
    8. Ex 24 - Building a Twitter Hashtag Extractor 00:05:59