Databases Reference
In-Depth Information
Big Data scale
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Unlimited data retention, never purge patient data
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Ability to curate 40+ billion clinical and operational data points over 13 million individuals
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35 TB multistructured data
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Growing to 70 TB by 2013
Advice to new hadoop users
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Leverage lessons learned from early adopters and Apache community.
Case study 4: Improving customer support
Company: Cloudera
Customer: NetApp
Program: NetApp improves customer support by deploying Cloudera Enterprise
Industry: Data storage
Business applications: AutoSupport operations: monitoring, troubleshooting, and health checks of
customer storage systems
Impact:
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Database query on 24 billion records reduced from four weeks to less than 10.5 hours.
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Previously impossible database query on 240 billion records runs in less than 18 hours.
Company overview
NetApp creates storage systems and software that helps customers around the world store, manage,
protect, and retain one of their most precious assets: data. To better support its customers, NetApp
offers AutoSupport, an integrated and efficient monitoring and reporting technology that constantly
checks the health of NetApp systems. Customers leverage the My AutoSupport portal on the NetApp
Support site for proactive systems management capabilities and insight into storage configuration,
capacity, utilization, efficiency, and health-check information.
Business challenge: processing massive volumes of data
AutoSupport collects over 600,000 data transactions weekly, consisting of unstructured logs and sys-
tem diagnostic information. Approximately 40% of that data is transmitted during an 18-hour period
each weekend, creating the potential for I/O bottlenecks that could affect SLA windows.
As the NetApp customer base is expanding, AutoSupport data is growing at approximately 7 TB
per month. Related storage requirements are doubling every 16 months. NetApp's AutoSupport team
proactively identified the need to upgrade its storage environment to accommodate continued growth.
NetApp's CIO Cynthia Stoddard explained, “I sit on thousands of customers' data and what I do with
that data is essential to the company. I need to react and help customers do more with their systems.”
AutoSupport needed a Big Data storage and analytic solution that would allow it to store, manage,
and analyze increasing volumes of unstructured data; gain insights from these large, complex data
sets; and scale for continued growth.
