Video description
In this course, you’ll learn how to integrate Hadoop components to implement big data solutions for a variety of use cases, including clickstream analytics, time series problems, transferring data between Hadoop and relational databases, and applications in the finance sector.
Table of contents
- Introduction to Clickstream Case Study
- Requirements
- Data Modeling
- Data Ingest
- Data Processing Engines - Part 1
- Data Processing Engines - Part 2
- Data Processing Patterns
- Orchestration
- Putting It All Together
- Demo
- Q
- Introduction
- Kafka
- Spark
- Spark Streaming
- Cassandra
- Spark and Cassandra
- Real World Use Cases
- Introduction
- Hadoop Basics
- Hadoop Distributed Filesystem (HDFS)
- Yarn
- MapReduce
- HDFS Data Import And Export
- Spark Basics
- Spark Built-In Libraries
- Hive And Pig
- Hadoop In The Cloud
- Ecosystem
- Wrap Up
- Introduction to Sqoop
- Importing Data To Hadoop From A Relational Database
- Sqoop Hands-On: Exporting Data From Hadoop To A Relational Database
- Advanced topics
-
Course summary
- Wrap Up
- Continuous curation of event data for a customer event hub - Arvind Prabhakar (StreamSets)
- Big data governance - Steven Totman (Cloudera), Mark Donsky (Cloudera), Kristi Cunningham (Capital One), Ben Harden (CapTech Consulting)
- Preventing a big data security breach - Sam Heywood (Cloudera), Nick Curcuru (MasterCard Advisors), Ritu Kama (Intel)
- Hive + Amazon EMR + S3 = Elastic big data SQL analytics processing in the cloud, a real-world case study - Jaipaul Agonus (FINRA)
Product information
- Title: Understanding Tool Integration for Big Data Architecture
- Author(s):
- Release date: December 2016
- Publisher(s): O'Reilly Media, Inc.
- ISBN: 9781491978634
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