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Projects in Hadoop and Big Data - Learn by Building Apps
Introduction
Introduction (3:33)
Add Value to Existing Data with Mapreduce
Introduction to the Project (15:02)
Build and Run the Basic Code (14:10)
Understanding the Code (13:56)
Dependencies and packages (14:45)
Hadoop Analytics and NoSQL
Introduction to Hadoop Analytics (15:48)
Introduction to NoSQL Database (15:30)
Solution Architecture (14:52)
Installing the Solution (9:13)
Kafka Streaming with Yarn and Zookeeper
Introduction to Kafka Yarn and Zookeeper (14:31)
Code Structure (15:24)
Creating Kafka Streams (15:19)
Yarn Job with Samza (15:37)
Real Time Stream processing with Apache Kafka and Apache Storm
Real Time Streaming (15:11)
Hortonbox Virtual Machine (14:58)
Running in Cluster Mode (15:32)
Submitting the Storm Jar (14:00)
Big Data Applications for the Healthcare Industry with Apache Sqoop and Apache S
Introduction to the Project (14:14)
Introduction to HDDAccess (14:48)
Sqoop, Hive and Solr (13:58)
Hive Usage (16:08)
Log collection and analytics with the Hadoop Distributed File System using Apach
Apache Flume and HCatalog (15:20)
Install and Configure Apache Flume (14:53)
Visualisation of the Data (14:53)
Embedded Pig Scripts (13:38)
Data Science with Hadoop Predictive Analytics
Introduction to Data Science (14:48)
Source Code Review (14:54)
Setting Up the Machine (15:11)
Project Review (15:12)
Visual Analytics with Apache Spark on Yarn
Project Setup (15:33)
Setting Up Java Dependencies (15:26)
Spark Analytics with PySpark (15:38)
Bringing it all together (13:50)
Customer 360 degree view, Big Data Analytics for e-commerce
Ecommerce and Big Data (15:01)
Installing Datameer (15:45)
Analytics and Visualizations (15:52)
Demonstration (13:31)
Putting it all together Big Data with Amazon Elastic Map Reduce
Introduction to the Project (15:57)
Configuration (15:31)
Setting Up Cluster on EMR (15:03)
Dedicated Task Cluster on EMR (15:28)
Summary
Summary (2:04)
Spark Analytics with PySpark
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