Hello, I commonly find myself needing to cook up data for Solr or (not-so-commonly) needing to validate data integrity (detect corruption/data deviation scenarios). To that effect, I recently vibe coded a couple of repos over several iterations of testing and feature-additions.
solr-datagen <https://github.com/rahulgoswami/solr-datagen> : Generate and index realistic documents into Apache Solr at scale, or reindex existing documents in-place. Given a Solr URL (with collection/core name), solr-datagen can either generate synthetic documents with realistic data across all field types and index them in parallel batches (index mode), or read existing documents from the collection and write them back in-place (reindex mode) index_validator <https://github.com/rahulgoswami/index_validator> : Detect field-level data loss and value corruption by comparing two Solr indexes (or a pre-operation snapshot against a live index) document-by-document. I have found them useful for scale testing and data validation and so thought of sharing with the community if it helps anyone. These originated as scratch-work tools and gradually evolved to handle scale and support more features as needed. So I'm sure there are a lot of ways these can be improved (eg: solr-datagen doesn't necessarily have to be specific to Solr and can be decoupled to work with other engines). Sharing here in their present form nevertheless if it helps others. Best, Rahul
