ZettaVox: Content Mining and Analysis Across Heterogeneous Compute Clouds__HadoopSummit2010

ZettaVox: Content Mining and Analysis across Heterogeneous Compute Clouds
Mark Davis
Kitenga, Inc.

The Company
The Problem
The Solution
Demo
Session Agenda

Kitenga 1,2 : (Maori) A view or perception
2004-present
CTO: Mark Davis, InXight Software (Business Objects/SAP), Microsoft, Defense R&D
CEO: Anil Uberoi, Lucid Imagination, Amdocs, Sun
Kitenga 1 also a region in Uganda 2 also a bed-and-breakfast in Clevendon, Auckland
Solutions for Information Overload
2953 Bunker Hill Lane, Santa Clara, CA

Support Prediction Logic, Inc.

The Never-Ending Problem Multimedia Data Video Imagery Audio Sensor Streams Biometric data 3D Text Email Web pages Tweets Posts Enterprise Data Enterprise data CDRs Financial records Access logs

Solving the Problem is Hard Content mining analysts Machine learning specialists Information retrieval specialists Software Engineers Expensive and hard to find Parallel Supercomputers Racked clusters Systems management Enterprise storage solutions Gigabit switches Power management Text analytics Ontologies Database reporting tools ETL tools Business intelligence Open source components

Convert raw data into actionable intelligence
Defense Intelligence Situation Reports Geotagged Imagery Improve Force Effectiveness ZettaVox Named Entity Extraction Image tagging Video analytics Linkage Analysis Network Visualization Search Hadoop, GPUs, HDFS, Hbase, SOLR

Increase speed of drug discovery
Pharmaceutical R&D Patents Genetic Sequence Data Journal Articles Faster Discovery ZettaVox Biological Named Entity Extraction Author Name Extraction and Normalization Linkage Analysis Timelines Facetted Search Hadoop, HDFS, Hbase, GPUs, SOLR

ZettaVox
Compose analysis workflows using out-of-the-box components
Interact with HDFS/Hadoop through Rich Internet Application
Monitor system progress
Visualize and analyze results
Batch mode via XML and JSON
Heterogenous compute resources

Heterogenous Compute Clouds 42 U ≈ 84-168 cores 2 PCIe slots 15 multiprocessors 480 cores $0.13-$0.35/Gflop Amazon AWS Rackspace Mosso Private Cloud

Author Analysis Solutions

Interact with HDFS

Monitor Analysis Jobs

Use and Visualize Results

ZettaVox Current Approach Slow analytics Methods don’t scale Expensive hardware Expensive software Capital investment Expertise investment Hadoop with GPU support Scalable SaaS Out-of-the-box expertise Rich user experience ZettaVox Internet-scale cloud and cluster-based content mining

Questions?
Mark Davis
[email_address]

ZettaVox: Content Mining and Analysis Across Heterogeneous Compute Clouds__HadoopSummit2010

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ZettaVox: Content Mining and Analysis Across Heterogeneous Compute Clouds__HadoopSummit2010 Presentation Transcript