Search Results for "libusb-win64-devel-filter"

Showing 4 open source projects for "libusb-win64-devel-filter"

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  • 1
    CMAK

    CMAK

    A tool for managing Apache Kafka clusters

    ... delete.topic.enable=true in broker config). Topic list now indicates topics marked for deletion (only supported on 0.8.2+). Batch generate partition assignments for multiple topics with option to select brokers to use. Optionally enable JMX polling for broker level and topic level metrics. Optionally filter out consumers that do not have ids/ owners/ & offsets/ directories in zookeeper.
    Downloads: 5 This Week
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  • 2
    BFG Repo-Cleaner

    BFG Repo-Cleaner

    Remove large or troublesome blobs

    The BFG is a simpler, faster alternative to git-filter-branch for cleansing bad data out of your Git repository history. You can use it for removing crazy big files, and for removing passwords, credentials and other private data. The git-filter-branch command is enormously powerful and can do things that the BFG can't, but the BFG is much better for the tasks above, because is faster and simpler. The BFG isn't particularily clever, but is focused on making the above tasks easy. If you need...
    Downloads: 16 This Week
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  • 3
    apache spark data pipeline osDQ

    apache spark data pipeline osDQ

    osDQ dedicated to create apache spark based data pipeline using JSON

    This is an offshoot project of open source data quality (osDQ) project https://sourceforge.net/projects/dataquality/ This sub project will create apache spark based data pipeline where JSON based metadata (file) will be used to run data processing , data pipeline , data quality and data preparation and data modeling features for big data. This uses java API of apache spark. It can run in local mode also. Get json example at https://github.com/arrahtech/osdq-spark How to run Unzip the...
    Downloads: 0 This Week
    Last Update:
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  • 4

    Deem

    Analyze time-course data with significance tests, clustering, modeling

    Use statistical methods to analyze time-course data (gene expression microarray and RNA-seq data in particular, but not limited to). Apply significance tests to filter out only significant genes or time series. Cluster time series into similar groups. Generate network models, including linear or non-linear models. Variable selection and optimization routines included. Written in Scala and R. The application is a cross-platform desktop app with a simple GUI and is fully functional...
    Downloads: 0 This Week
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