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This project contains artifacts that provide utility functions for Cloud Bigtable client readers and writers in Google Cloud Dataflow. Dataflow includes a different version of the cloud bigtable client, resulting in a need to have a separation of concerns and an abstraction. More importantly, there is a need for shading and renaming of packages so that Dataflow nad bigtable-hbase-dataflow's two sets of shading (needed for a variety of reasons) don't clash with each other. This submodule does package renaming which is needed for bigtable-hbase-dataflow and alleviates some issues related to developing that module.

This powerful reporting library aims to simplify producing reports using iText. The most demanding and coding intensive tasks when producing reports with iText are how to get from data to report elements, how to style those blocks and how to evaluate (debug) the resulting report layout. Exactly those three tasks are simplified by this library: xml configuration and/or annotations to transform existing Java data objects into report block, provide styling information (css like, syntax independent) seperate from code, a firebug like debug mode to help evaluate your report.

ELKI is an open source (AGPLv3) data mining software written in Java. The focus of ELKI is research in algorithms, with an emphasis on unsupervised methods in cluster analysis and outlier detection. In order to achieve high performance and scalability, ELKI offers many data index structures such as the R*-tree that can provide major performance gains. ELKI is designed to be easy to extend for researchers and students in this domain, and welcomes contributions in particular of new methods. ELKI aims at providing a large collection of highly parameterizable algorithms, in order to allow easy and fair evaluation and benchmarking of algorithms.

The Jenkins Maven Plugin allows to use the Jenkins CLI (command line interface) from within a Maven build. It allows the execution of any command supported by the CLI, see https://wiki.jenkins-ci.org/display/JENKINS/Jenkins+CLI for further information. Therefore, it downloads the current jenkins-cli.jar from ${project.ciManagement.url}/jnlpJars/jenkins-cli.jar and uses that artifact for interacting with the Jenkins server. The architecture of the Jenkins Maven Plugin follows the UNIX philosophy "do one thing and do it well": it does not provide any logic for specific tasks, for instance creating job configuration files. This can be done with another, more appropriate plugin and its result can then be specified as stdin to the Jenkins Maven Plugin.

A timer using the crontab syntax and additional binary input to provide a resolution of one second (1000 ms / 1000 millis / 1s). The timer uses the whiteboard pattern to notify the clients. There are only a few dependencies to commons-codec, osgi and osgi-blueprint. The bundle 'org.i3xx.step/org.i3xx.step.clockmongo' provides a store for the clock configuration based on mongodb. The additional dependency is 'org.mongodb/mongo-java-driver'. The bundle 'org.i3xx.util/org.i3xx.util.whiteboard' can be used to avoid a dependency to bundles used. In other words, your bundle can use the clock but need no dependency to the bundle 'org.i3xx.step.clock'. Take a look at the description there.

RBFNetwork implements a normalized Gaussian radial basisbasis function network. It uses the k-means clustering algorithm to provide the basis functions and learns either a logistic regression (discrete class problems) or linear regression (numeric class problems) on top of that. Symmetric multivariate Gaussians are fit to the data from each cluster. If the class is nominal it uses the given number of clusters per class. RBFRegressor implements radial basis function networks for regression, trained in a fully supervised manner using WEKA's Optimization class by minimizing squared error with the BFGS method. It is possible to use conjugate gradient descent rather than BFGS updates, which is faster for cases with many parameters, and to use normalized basis functions instead of unnormalized ones.

benerator is a framework for creating realistic and valid high-volume test data, used for testing (unit/integration/load) and showcase setup. Metadata constraints are imported from systems and/or configuration files. Data can imported from and exported to files and systems, anonymized or generated from scratch. Domain packages provide reusable generators for creating domain-specific data as names and addresses internationalizable in language and region. It is strongly customizable with plugins and configuration options.