Showing 4 open source projects for "awscli-local"

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  • 1
    IoTDB

    IoTDB

    Apache IoTDB

    ...Due to its light-weight architecture, high performance and rich feature set together with its deep integration with Apache Hadoop, Spark and Flink, Apache IoTDB can meet the requirements of massive data storage, high-speed data ingestion and complex data analysis in the IoT industrial fields. In the scene of factories, there are tens of devices under LAN network. IoTDB can be installed on a local controller server in the factory to receive data from those devices. The local controller server (normal PC or workstation) with IoTDB can provide the ability to persist data and query data with SQL-like interface. In addition, with TsFile-Sync tool, TsFiles on the local controller can be transmitted to the data center equipped with IoTDB instance in the cloud.
    Downloads: 3 This Week
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  • 2
    SageMaker Spark Container

    SageMaker Spark Container

    Docker image used to run data processing workloads

    Apache Spark™ is a unified analytics engine for large-scale data processing. It provides high-level APIs in Scala, Java, Python, and R, and an optimized engine that supports general computation graphs for data analysis. It also supports a rich set of higher-level tools including Spark SQL for SQL and DataFrames, MLlib for machine learning, GraphX for graph processing, and Structured Streaming for stream processing. The SageMaker Spark Container is a Docker image used to run batch data...
    Downloads: 0 This Week
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  • 3
    FlowViewer

    FlowViewer

    FlowViewer is a web-based netflow data analysis tool.

    ...The FlowViewer tools provide additional graphing and tracking features by utilizing open source software including Thomas Boutrell’s gd, Lincoln Stein's GD, Martien Verbruggen's GD::Graph, and Tobias Oetiker’s RRDtool. FlowViewer v4.6 fixes non-UTC local time environments for FlowViewer and FlowGrapher, and $no_devices_or_exporters FlowMonitor_Collector problem. **Note: SiLK must be v3.8.0 or later. Version 3.9 handles sFlow data.
    Downloads: 4 This Week
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  • 4

    GLMNB

    GLMNB: a shape-based peak calling tool for ChIP-Seq data analysis

    This is the beta-version of a shape-based peak calling tool for ChIP-Seq data analysis. It is built using Generalized Linear Model with Negative binomial distribution. This tool accounts for the common peak shape, local variability of peak shifting distance and negative binomial background noise.
    Downloads: 0 This Week
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