Leveraging Hadoop to Augment MySQL Deployments

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When you’re dealing with petabytes of data, even MySQL starts to struggle. Apache Hadoop can work alongside your current system, enabling you to perform complex analyses of your entire data set. Hadoop is not a replacement for a relational database. Instead, DBAs need to know when to leverage Hadoop alongside your MySQL database(s) for batch processing of structured or unstructured data. This talk will cover the tools available for importing and exporting data between relational databases and Hadoop as well as using known skills (SQL) to do complex data analysis in Hadoop. Outline:

  • What is Hadoop and what is it used for?
  • How is Hadoop different than a relational database
  • How to use tools to import and export data between MySQL and Hadoop
  • Learn about HiveQL, the SQL-like language for analyzing data in Hadoop
Photo of Sarah Sproehnle

Sarah Sproehnle

Cloudera, Inc.

Sarah Sproehnle is Dir. of Educational Services for Cloudera where she creates and delivers training on Hadoop. She has many years experience delivering training on various topics such as database administration, performance tuning, high availability, programming, and system administration.

  • EnterpriseDB
  • Amazon Web Services
  • Clustrix
  • Continuent
  • Facebook
  • HTI Consultoria e Tecnologia
  • Monty Program
  • Percona
  • Rackspace Hosting
  • Schooner Information Technology
  • SkySQL
  • Xeround

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