Apache Lucene, initially developed as a text search engine, has evolved significantly to accommodate numeric range filters, enhancing its functionality beyond text tokens. Originally, numeric values were treated as textual tokens with left-zero-padding to ensure correct sorting, but this method was inefficient and inflexible. Uwe Schindler's introduction of numeric tries in Lucene 2.9 marked a turning point, offering improved numeric support with a more user-friendly API and faster query performance by indexing numbers at multiple precision levels. The evolution continued with Lucene 6.0's block KD (BKD) tree data structure, initially implemented for geo-spatial searches but later recognized for its efficiency in one-dimensional numeric filtering. This advancement supports complex data types, such as IPv6 addresses, and significantly improves performance and index size, surpassing previous methods. Elasticsearch 5.0.0 leverages these advancements, showcasing the collaborative and iterative nature of open-source development in enhancing search capabilities.