Blur is a distributed search capability built on top of Hadoop and Lucene that is designed specifically for big data. It leverages the scalability, redundancy, and performance of Hadoop and Lucene. Blur stores data in tables containing rows and records with columns, and uses MapReduce to index data and shard servers to perform searches in a scalable and fault-tolerant manner. It overcomes challenges like reindexing large datasets and providing low-latency random access by leveraging features of its architecture. Future work includes more performance tuning, testing, documentation, and new query capabilities.