Showing 4 open source projects for "problem a"

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  • 1
    Genie

    Genie

    Distributed Big Data Orchestration Service

    Genie is a completely open source distributed job orchestration engine developed by Netflix. Genie provides REST-ful APIs to run a variety of big data jobs like Hadoop, Pig, Hive, Spark, Presto, Sqoop and more. It also provides APIs for managing the metadata of many distributed processing clusters and the commands and applications which run on them.
    Downloads: 1 This Week
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  • 2
    MyCAT

    MyCAT

    Active, high-performance open source database middleware

    ...In a word, MyCAT is a fresh new middleware of database. MyCAT ’s objective is to smoothly migrate the current stand-alone database and applications to cloud side with low cost and to solve the bottleneck problem caused by the rapid growth of data storage and business scale.
    Downloads: 11 This Week
    Last Update:
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  • 3

    wzd

    Powerful storage server, designed for big data storage systems

    wZD is a server written in Go language that uses a modified version of the BoltDB database as a backend for saving and distributing any number of small and large files, NoSQL keys/values, in a compact form inside micro Bolt databases (archives), with distribution of files and values in BoltDB databases depending on the number of directories or subdirectories and the general structure of the directories. Using wZD can permanently solve the problem of a large number of files on any POSIX compatible file system, including a clustered one. Outwardly it works like a regular WebDAV server.
    Downloads: 0 This Week
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  • 4

    iOVFDT

    iOVFDT algorithm of incremental decision tree

    How to extract meaningful information from big data has been a popular open problem. Decision tree, which has a high degree of knowledge interpretation, has been favored in many real world applications. However noisy values commonly exist in high-speed data streams, e.g. real-time online data feeds that are prone to interference. When processing big data, it is hard to implement pre-processing and sampling in full batches.
    Downloads: 0 This Week
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