Search Results for "data capture framework"
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Showing 5 open source projects for "data capture framework"
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dispy
Distributed and Parallel Computing with/for Python.
dispy is a generic and comprehensive, yet easy to use framework for creating and using compute clusters to execute computations in parallel across multiple processors in a single machine (SMP), among many machines in a cluster, grid or cloud. dispy is well suited for data parallel (SIMD) paradigm where a computation (Python function or standalone program) is evaluated with different (large) datasets independently. -
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ForeIndex
Distributed Index with Apache Hadoop, Apache Lucene and Apache Tika
This is a distributed index framework using Apache Hadoop, Apache Lucene and Apache Tika, to index large volume of data. -
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Essence is a simple Java framework with modules for Quantitative Analysis and Distributed Data systems.
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A LDAP based cluster control system that allows the deployment and administration of heterogeneous clusters. An extremely generic framework designed to be extended as required by administrators for each cluster.
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UPDATE: Chromium is no longer updated or maintained. The project is frozen. Chromium is a flexible framework for scalable real-time rendering on clusters of workstations, derived from the Stanford WireGL project code base.
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