Single-pass optimization engine for data extraction and transformation on z/OS.
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We’re accelerating GenevaERS’s adoption of open source and the transformation of the mainframe by focusing on a proof of concept: Integrate GenevaERS with Apache Spark. You can read about it at the GenevaERS Apache Spark POC page.
Open source contributions are more than just about source code. We need help of all kinds:
- Data preparation: We are working to build a data set that can be used on either z/OS or open systems to provide a fair comparison for either platform, but with enough volume to test some performance. Work here includes scripting, data analysis, and cross-platform capabilities and design.
- Spark: We want some good Spark code that uses the power of that system, and makes the POC give real-world results. Expertise needed includes writing Spark functions, data design, and tuning.
- Java JNI or Java Native Interface: The means by which one calls other language routines under Java, and thus under Spark. Assistance can be used in helping to encapsulate the GenevaERS utility functions to perform fast I/O for our test.
- GenevaERS: The configuration we create we hope to be able to extract as GenevaERS VDP XML, and provide it as a download for initial installation testing. A similar goal with the sample JCL that will be provided. GenevaERS expertise in these fields is needed.
- Documentation Repository Work: Since this project is in its infancy, there will be numerous items to contribute along the lines of documentation and workflow.
For more information, visit the GeneraERS GitHub or Community Page.