Download JAR files tagged by large with all dependencies

A cluster computing system for processing large-scale spatial data: Streaming API for Apache Flink. Apache Sedona is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.

A cluster computing system for processing large-scale spatial data: Python Adapter. Apache Sedona is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.

A cluster computing system for processing large-scale spatial data: RDD and SQL for Viz. Apache Sedona is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.

A cluster computing system for processing large-scale spatial data: SQL API. Apache Sedona is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.

A cluster computing system for processing large-scale spatial data: RDD API. Apache Sedona is an effort undergoing incubation at The Apache Software Foundation (ASF), sponsored by the Apache Incubator. Incubation is required of all newly accepted projects until a further review indicates that the infrastructure, communications, and decision making process have stabilized in a manner consistent with other successful ASF projects. While incubation status is not necessarily a reflection of the completeness or stability of the code, it does indicate that the project has yet to be fully endorsed by the ASF.

Simple Validation Parent Project: This is a simple library for quickly adding validation code to Swing user-interfaces. It handles validating user input when the user changes a component's value, showing error messages and decorating components to indicate which component is the source of the problem. It contains a large number of built-in validators to handle most common situations, such as validating numbers, email addresses, urls and so forth.

The chart-fx charting library is an extension in the spirit of Oracle's XYChart and performance/time-proven JDataViewer charting functionalities. Emphasis was put on plotting performance for both large number of data points and real-time displays, as well as scientific accuracies leading to error bar/surface plots, and other scientific plotting features (parameter measurements, fitting, multiple axes, zoom, ...). The library also contains a small set of math routines that can operate directly on the DataSet primitive for fitting, computing spectra, linear algebra, FIR/IIR filtering, and other functionalities common to signal processing.

This module groups all different output writers. Different output writers have different dependencies. To ensure that those dependencies do not leak to other output writer, or that we can limit to number of dependencies at runtime, output writers are split into separate modules based on the dependencies they use. For example, the CloudWatch output writers depends on the AWS SDK, which is quite large and not used by any other output writer. If you only want to send metrics to Graphite, there should be no need to have the AWS SDK in your classpath at runtime. Some dependencies are also problematic. They can introduce incompatibilities. For example, a few writers are based directly on log4j or logback. This direct dependence breaks the use of SLF4J. By isolating those output writers to a specific module, we can ensure this has minimal impact.