Difference between revisions of "Earth Science Data Analytics/Use Case Collection"

From Earth Science Information Partners (ESIP)
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'''Use Case Name''': MERRA Analytics Services
 
'''Use Case Name''': MERRA Analytics Services
  
'''Provided By''':  John Schnase (entered by Steve K)
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'''Provided By''':  John Schnase
  
'''Brief Description''': Combines iRODS-based Climate Data Server (CDS) capabilities with Cloudera MapReduce to serve MERRA analytic products
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'''Brief Description''': Enables Climate Analytics-as-a-Service by combining iRODS data management, Cloudera MapReduce, and the Climate Data Services API to serve MERRA reanalysis products.
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'''Key Analytics Needs''':  Store the MERRA reanalysis data collection in an HDFS to enable parallel, high-performance, storage-side data reductions; Manage storage-side <driver, mapper, reducer> code sets and realized objects for users; Provide a library of commonly used spatiotemporal operations (canonical ops) that can be composed to enable higher-order analyses; and Deliver end-user and application capabilities through the NASA Climate Data Services API.
  
'''Key Analytics Needs''':  Store the MERRA reanalysis data collection in an HDFS to enable parallel, high-performance, storage-side data reductions; Manage storage-side <driver, mapper, reducer> code sets and realized objects for users; and Provide a library of commonly used spatiotemporal operations (canonical ops) that can be composed to enable higher-order analyses.
 
  
 
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Revision as of 20:01, April 6, 2014

Use Case Collecting...


Please insert the pertinent information regarding your use case below. We can beef up the details later. Alternatively, e-map information to Steve Kempler (Steven.J.Kempler@nasa.gov)


Use Case Name: MERRA Analytics Services

Provided By: John Schnase

Brief Description: Enables Climate Analytics-as-a-Service by combining iRODS data management, Cloudera MapReduce, and the Climate Data Services API to serve MERRA reanalysis products.

Key Analytics Needs: Store the MERRA reanalysis data collection in an HDFS to enable parallel, high-performance, storage-side data reductions; Manage storage-side <driver, mapper, reducer> code sets and realized objects for users; Provide a library of commonly used spatiotemporal operations (canonical ops) that can be composed to enable higher-order analyses; and Deliver end-user and application capabilities through the NASA Climate Data Services API.




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