Silicon Valley Code Camp : October 5th and 6th 2013

Sastry Vedantam

Oracle
About Sastry
Sastry has 16+ years of rich, robust and diversified IT and Functional experience in multiple technologies spread across various domains, businesses and verticals. His strengths are in pre-sales/program/delivery/account management and on time and on budget delivery of large projects adhering to the quality norms and to the utmost customer satisfaction. He also has strong and proven expertise in providing Architectural Consultancy to global projects. Joined Sun Microsystems in 2008 as Enterprise Solution Architect handling Deployment Architecture using JavaCAPS ( Middleware) applications. After MySQL Merger in to Sun and then later into Oracle worked different technologies including MySQL , Fusion Middleware Solutions. Currently working as sr. technical Consultant in the MySQL team.
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Speaking Sessions

  • CON1170 - Improving MySQL Performance with Hadoop

    3:30 PM Saturday   Room: 4302
    Apache Hadoop is a software framework that supports data-intensive distributed processing across clusters of computers using a simple programming model. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Hadoop can be integrated with MySQL to take advantage of this framework for data intensive applications, and this talk will demonstrate the integration of Hadoop with MySQL. As a Java Programmer you can use Map Reduce in Hadoop to improve the performance of MySQL. In this session, we will illustrate the Advantages of Integrating Trasactional Data from MySQL ino the Hadoop HDFS file system in Batch and Real time Methods so that the Trasactional Data combined with other non-structrured data will be avaialable as a single source of truth to perform the analysis. In this session will demonstrate the capabilities of MySQL Hadoop Applier and Sqoop components along with the NoSQL Capabilities with in MySQL for Buld Data loads and at the same tiem retaining the ACID compinace to the data.