Angelo Rodriguez is a Full Stack Developer with eight years of experience building reliable data processing and integration features, based in Cocoa, Florida. He has a strong backend focus demonstrated by substantive open-source contributions to the Pentaho ecosystem—adding ORC output functionality, performance fixes, and stability improvements across Pentaho Hadoop Shims, Kettle (ETL), and the Big Data plugin. His work touches both core format shims and user-facing plugin dialogs, showing fluency from low-level file-format details (compression, stripe size, row index stride) to UX-oriented metadata injection. Colleagues benefit from his pragmatic approach to bug fixes and optimizations that directly improve data output correctness and throughput. Unusually for a full stack title, Angelo’s open-source history reveals deep expertise in big-data file formats and ETL internals rather than only front-end work.
Contributions:43 commits, 48 PRs, 29 pushes in 1 year 6 months
Contributions summary:Angelo primarily contributed to the implementation of ORC output functionality and related API definitions within the Pentaho Hadoop Shims repository. This included adding features like compression, stripe size, and row index stride configuration for ORC files. Further contributions focused on the addition of an overwrite existing flag for the ORC output step. The user's work involved modifications to both the core format shims and associated test cases.
Kettle plugin that provides support for interacting within many "big data" projects including Hadoop, Hive, HBase, Cassandra, MongoDB, and others.
Role in this project:
Back-end Developer
Contributions:52 commits, 58 PRs, 21 pushes in 2 years 1 month
Contributions summary:Angelo primarily worked on implementing and modifying features related to the ORC output step within the Pentaho Big Data plugin. Their contributions include creating UI dialog elements, integrating new options like rows between entries, and refining the user experience. They also made changes to the Avro and Parquet output steps, updating metadata injection and fixing issues related to file handling. These changes directly impact the functionality and usability of the plugin.
big-datacassandrahadoophbasehive
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