SBIR/STTR Research Award

A MapReduce-like Data-Intensive Processing Framework for Native Data Storage and Formats

Award identifier 70175dab8b2805679c7138c337f1746789a55083d05c67a8bd4183ae8dce80d2Awarding agency Department of Energy

Award amount

$150,000

Program and phase

STTR · Phase I

Award year

2014

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Award details

Awarding agency
Department of Energy
Branch
Not reported
Recipient company
RNET TECHNOLOGIES INC
Proposal award date
2014-02-18
Contract end date
2014-11-17
UEI
RLPGQ5UY9ED3
Solicitation number
DE-FOA-0000969
Topic code
01c

Research abstract

MapReduce is a very popular data analytic framework that is widely used in both industry and scientific research. Despite the popularity of MapReduce, there are several obstacles to applying it for developing some commercial and scientific data analysis applications. The project will develop a Native data FOrmat MapREDuce-like framework, iNFORMER, based on OSUs SciMate architecture. The framework allows MapReduce-like applications to be executed over data stored in a native data format, without first loading the data into the framework. This addresses a major limitation of existing MapReduce-like implementations that they require that data be loaded into specialized file systems, e.g., like the Hadoop Distributed File System (HDFS). The overheads and additional data management processes required for this translation can prevent MapReduce from being used in many commercial and scientific environments. Commercial Applications and Other Benefits: There are two large classes of users will benefit from the iNFORMER product. The first are current users of MapReduce-like frameworks. MapReduce is used extensively in commercial applications and is a major component of many Cloud infrastructures. As an example of the extensive use of MapReduce, the linkedin group Hadoop Users currently has more than 30,000 members. The second class of customers that will benefit from iNFORMER includes users who currently use alternative data layouts and desire to use a MapReduce-like framework. These users are likely to currently process this data using alternative frameworks, as the overhead to convert the data into a format suitable format for MapReduce processing is too expensive. Therefore, we expect a subset of these users to be interested in iNFORMER. There are extensive users of these low-level data formats who will be potential customers. For instance, users of HDF and NetCDF users including groups from academia, industry, and national laboratories who could potentially benefit from iNFORMER. HDF is used by over 600 organizations, with over 200 different data types, and millions of users.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

77 SBIR/STTR records share this UEI (2004–2025). Reported award amounts total $27,646,046. Reported amounts are not federal obligations.

Phases: Phase I, Phase II

Agencies: Department of Energy, Department of Defense, National Aeronautics and Space Administration, Department of Health and Human Services, National Science Foundation

Agency intelligence

Department of Energy

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