The system is currently hard coded with one tokenizer and one analyzer. This can easily be changed. The searcher returns the document and the score it received but not where the term is, or any information on how to 'highlight' the result. This is doable by adding in the required information into the match embedded document and processing it out in the Map Reduce phase. There is no query caching in this system. Paging through the results will result in duplicate work. It would be best to actually cache the output of the map reduce into Redis using a sorted set. The Redis key would have to be derived from the query.
via NoSQL databases