Visual Analytics Sandbox for Big Data Insights
Explore the Visual Analytics Sandbox for advanced data processing, efficient resource management, and real-time decision-making in a Big Data environment. Discover tools for data ingestion, storage, processing, and visualization within the VA Sandbox. Accessible through university networks, this platform empowers users to analyze big data effectively.
Download Presentation
Please find below an Image/Link to download the presentation.
The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author. If you encounter any issues during the download, it is possible that the publisher has removed the file from their server.
You are allowed to download the files provided on this website for personal or commercial use, subject to the condition that they are used lawfully. All files are the property of their respective owners.
The content on the website is provided AS IS for your information and personal use only. It may not be sold, licensed, or shared on other websites without obtaining consent from the author.
E N D
Presentation Transcript
Visual Analytics Sandbox Satya Katragadda January 25, 2018
Agenda Why Big Data? Goals Visual Analytics Sandbox Traditional Workflow in a Big Data Environment VA Sandbox: Software Stack VA Sandbox: Execution Examples
Why Big Data? Reports, e.g., Track business processes, transactions Diagnosis, e.g., Why is user engagement dropping? Why is the system slow? Detect spam, worms, viruses, DDoS attacks Decisions, e.g., Decide what feature to add Decide what ad to show Block worms, viruses,
Goals Low latency (interactive) queries on historical data: enable faster decisions E.g., identify why a site is slow and fix it Low latency queries on live data (streaming): enable decisions on real-time data E.g., detect & block worms in real-time (a worm may infect 1mil hosts in 1.3sec) Sophisticated data processing: enable better decisions E.g., anomaly detection, trend analysis
Big Data Workflow Data Ingestion Data Management Data Processing Visualization Resource Management
VA Sandbox Stephens Hall Accessible through university network
Alternative Execution Environment HUE: Hadoop User Experience An open-source Web interface that supports Apache Hadoop and its ecosystem Component Applications Editor SQL, Pig, Spark Browsers YARN, Oozie, Impala, HBase, Livy Scheduler Oozie Dashboard Solr, SQL (Impala, Hive...)
Questions? Satya Katragadda RM 118, Abdalla Hall satya@Louisiana.edu
